As customer journeys become more connected and complex, gaps in execution can lead to inconsistent experiences, slower response times, and missed opportunities. The next frontier of customer experience is not generating more insights, but turning insight into coordinated action at scale.

This latest release of the solution portfolio helps organizations strengthen that foundation by connecting workflows across marketing, commerce, sales, and service鈥攅nabling more consistent, scalable execution across every customer interaction.

Explore the highlights of the Q2 2026 release. For full sub-solution details, see our recaps for the , , , , and solutions.

Turning customer intent into action

Customer interactions are becoming more conversational, connected, and immediate across channels and touchpoints. At the same time, organizations need faster access to information and simpler ways to take action鈥攚hether engaging customers, managing campaigns, or responding to changing business needs.

• Conversational AI shopping through a model context protocol (MCP) server: Enable secure integration between and AI agents that can guide or act on behalf of customers. AI assistants can query real-time product information, provide inventory updates, manage shopping carts, and complete transactions directly within chat or voice interfaces鈥攃reating more intelligent, conversational buying experiences beyond the traditional storefront. 

• Joule in 麻豆原创 Engagement Cloud (麻豆原创 Early Adopter Care): Bring 麻豆原创’s conversational AI directly into campaign workflows. Teams can ask product or campaign questions in natural language and get accurate answers without searching across multiple systems. They can also duplicate successful campaigns without starting from scratch, freeing more time for strategic thinking, creativity, and customer engagement.

• Rich communication services (RCS) in 麻豆原创 Engagement Cloud: Engage customers with rich, interactive messages supported by Google and featuring media, carousels, and action buttons within native mobile messaging experiences. Branded, verified messages help build trust and guide customers smoothly from discovery to purchase without requiring an additional application.

Scaling personalized engagement

Recognizing customer intent is only the beginning. As engagement channels expand, marketing teams need to respond quickly while delivering relevant, personalized experiences at scale. This requires frictionless campaign execution, timely insights, and the ability to tailor every interaction to each customer’s needs and preferences.

• AI-assisted content composer (pilot): Generate high-quality, on-brand campaign content in . Using Gemini models informed by audience, product, and campaign context, teams can quickly create and refine content variations so they can launch personalized campaigns faster and spend less time on manual content creation.

• Embedded audience builder: Enable marketers to access and activate rich data from directly within 麻豆原创 Engagement Cloud. With this capability, they can build advanced segments themselves without switching systems or waiting on data analysts. The precision and relevancy of omnichannel campaigns can be improved by combining behavioral, transactional, account, and profile data with operational data across the business.

Enabling consistent sales execution at scale

Success depends on turning insight into disciplined, repeatable actions that drive predictable revenue outcomes. As sales environments grow more complex, even small inconsistencies in data, priorities, or execution can undermine forecasts and cause opportunities to slip away. Acting with greater consistency and confidence calls for stronger data integrity, aligned behaviors, and clearer guidance.

• Agentic opportunity summary overview: Give sales teams the tools they need to quickly assess deal health. This capability in aggregates engagement signals, activity levels, and progress indicators into a real-time view, allowing teams to identify risks early, prioritize effectively, and maintain deal momentum.
• : Optimize sales velocity and help ensure the right product placement with retail execution enabled by intelligent, AI-enhanced processes that maximize revenue. Teams can improve visit planning and execution, harness insights to improve sales performance, and optimize interactions. For consumer products companies, this helps drive shelf availability, promotion compliance, and merchandising effectiveness across retail locations. Field teams gain greater visibility into store-level execution, enabling more consistent brand presence and stronger sell-through performance.

• 麻豆原创 Incentive Management: Improve sales team effectiveness by using the solution, which is part of solutions. It helps drive profitable behaviors that increase revenue and support business growth while providing real-time performance insights, dispute management, and motivating rewards. Teams can use flexible tools to streamline incentive compensation and quickly design, test, and launch sales plans. AI-supported recommendations are also available to guide organizations in optimizing plans, maximizing outcomes, and uncovering actionable insights.

• Consumer Products Intelligence (麻豆原创 Early Adopter Care program): Enable consumer product companies to turn the enormous amount of sales and trade data they generate into better decisions. It uses analytics and AI to help improve trade spend performance, increase sales revenue and margins, and reduce manual effort.
   

Standardizing service execution across the enterprise

Service teams are increasingly expected to deliver faster, more reliable support while managing growing complexity across channels and requests. Achieving this objective requires simplifying how services are accessed and helping ensure consistent processes across the organization.

• Self-service catalog: Allow employees to quickly find what they need without understanding backend processes. Through this guided, intuitive catalog for requests are automatically routed with the right context, reducing delays and improving resolution times.

• Content package framework: Leverage the framework for 麻豆原创 Enterprise Service Management to deliver rapid, scalable value across lines of business. Prebuilt, reusable configurations for case types, workflows, and catalogs help organizations deploy services more quickly while simplifying implementation across the business. With this approach, organizations can eliminate complexity, empower partners, and speed adoption. Content packages for HR service delivery will be coming soon. 
• Email editor in 麻豆原创 Service Cloud and 麻豆原创 Enterprise Service Management: Compose, edit, and manage customer communications more efficiently while maintaining high-quality service interactions. The modern, user-friendly email editor is built for an AI-first world.

• Creation of sales objects from customer hub: Let agents fully manage leads, opportunities, appointments, and sales orders directly from the service agent workspace of 麻豆原创 Service Cloud. This capability helps turn each customer interaction into an opportunity to deliver more value.

Accelerating connected order management

Turning insight into action requires connected systems that can adapt as the business evolves. As organizations expand order channels, fulfillment networks, and technology landscapes, they need integration and order management that can keep pace so teams can respond faster to change.

• Flow connector: Enables smooth data flow between the solution, other 麻豆原创 solutions, and third-party products. This predefined capability allows business users to configure custom business flows and integrations with minimal IT involvement, creating connected order management processes across the enterprise.

Execution at scale: the next customer experience advantage

As AI becomes embedded in daily operations, the differentiator shifts from insight generation to execution.

Our recently announced strategic partnerships with and Google Cloud help extend this execution-first approach by connecting AI-powered service, commerce, and engagement experiences directly to operational systems and business data. As a result, organizations can move from isolated interactions and insights to coordinated actions that drive faster resolutions, better customer experiences, and greater business impact.

Learn more about 麻豆原创 CX in Q2鈥�2026 

Read the 麻豆原创 Help documentation to get started with these new capabilities:

Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience and Consumer Industries at 麻豆原创.

But what if more or better software is not necessarily the answer? Each solution solves a real problem for a specific team. But collectively, they create a consequence no one planned for: every new tool builds its own data world, without a common language or context across them.

In a 2026 study by Oxford Economics, . Twenty-nine percent remain highly fragmented. Organizations with siloed CX tech are more likely to face an inability to connect customer needs to actionable data insights. Fifty-eight percent reported this challenge, compared to 47% among those with harmonized environments.

More than what tools businesses choose to add to their CX landscape, how they connect and interact with each other becomes even more important.

A unified data strategy sounds straightforward in principle. In practice, most businesses find that the obstacle is not ambition but rather execution. Every integration decision made without a clear data architecture becomes a future campaign mired in manual reconciliation, a customer journey that breaks at the handoff, or a personalization promise the disparate data sources cannot support. Implementation without a validated strategy creates new fragmentation inside the solution meant to eliminate the old. And without a structured way to pressure-test decisions before any commitment is made, even well-resourced organizations find themselves repeating the same cycle: invest, integrate, fragment, repeat.

The real barrier is not budget or technology

A Forrester study of more than 1,000 senior executives found that , ahead of budget, technology maturity, and talent. The same study found that 56% of respondents struggle with poor data quality; 55% face persistent data silos. This is not for lack of investment in technology, but because the connections between systems were not designed or maintained effectively.

What bridges that gap is not another platform, it is the expertise to think through data connectivity decisions before they are made and the ongoing guidance to ensure those decisions compound into measurable gains over time. The for solutions provides that guidance along every step of the journey.

Define what success actually looks like

The most common reason data unification projects fall short of expectations is not technical failure, it is a failure to define and measure what success looks like for the entire business before the work begins.

The value management session from the Advanced Success Plan for 麻豆原创 Customer Experience establishes that definition at the outset: What does a fully unified data strategy actually enable? It means running the next marketing campaign without manual data reconciliation, and presenting an AI readiness road map without caveats. Stakeholders will know, at every checkpoint, whether the investment is moving the business forward, not just moving the project forward.

Design the strategy before building the integrations

A robust data strategy starts with good design. Product guidance from the Advanced Success Plan for 麻豆原创 Customer Experience covers available out-of-the-box integrations, common usage scenarios, and pitfalls and how to avoid them鈥攁ll delivered in a live remote session by an 麻豆原创 expert who can answer questions in real time. The data strategy can be conceptualized and pressure-tested before any budget or technical commitments are made.

Validate every critical decision with expert guidance

With the technical assistance and functional assistance from the Advanced Success Plan for 麻豆原创 Customer Experience, businesses have continuous access to expert guidance at every critical decision point. Beyond resolving immediate questions, the ongoing access also shares insight on how 麻豆原创 thinks through problems, strengthening in-house expertise with every interaction. The result is an organization that makes better decisions not just now but for the future.

Measure whether the strategy is delivering

Adoption and innovation checkpoints conducted on a quarterly or semi-annual basis bring the measurement back to where it started: the business outcomes defined at the outset. Do campaigns run without manual reconciliation? Is the AI use case performing against its stated goals? A clear throughline from the value management success KPIs to the adoption and innovation checkpoints proves the benefits of the investment.

Where cycles and silos break

The cycle of invest, integrate, fragment, repeat is not inevitable. It is the predictable result of making technical decisions without an anchoring business imperative, and integration decisions without strategic expert guidance. Organizations that break the cycle do not necessarily have better technology than their competitors鈥攖hey have better judgment about how to use it.

The Advanced Success Plan for 麻豆原创 Customer Experience exists for exactly that reason: to put proactive and prescriptive guidance at every decision point where that judgment matters most. When data strategy is designed before it is built, validated before it is committed, and measured against real business outcomes, the technology investment already made starts working harder.

The stack was never the problem. When the thinking behind the technology finally matches its ambition, the personalized, seamless experience becomes a reality.

Tara Tracey, global product owner for the Advanced Success Plan for 麻豆原创 Customer Experience.
Ella De Torres, product manager for the Advanced Success Plan for 麻豆原创 Customer Experience.

The Advanced Success Plan version for 麻豆原创 Customer Experience solutions is designed precisely for this moment. It offers utilities customers a structured, continuously guided approach to maximizing value from 麻豆原创 Customer Experience (麻豆原创 CX) investments, from first adoption through to AI-enabled optimization.

A sector in motion: why customer experience has become strategic for utilities

Four converging forces are making customer experience a boardroom priority for utilities and increasing the demand for structured, expert-led adoption support.

• Energy transition and service complexity: Renewables, EV charging, solar feed-in tariffs, and demand response programs are adding new service dimensions. Customers expect their energy provider to manage this complexity seamlessly.
• Deregulation and customer switching: In liberalized energy markets, customers can, and do, switch providers. The cost of acquisition consistently exceeds the cost of retention. Superior service experience is a measurable retention lever.
• Smart metering and data volume: Smart meter rollouts generate billions of interval readings daily. This data can fuel proactive outreach and personalized billing, but only if the customer experience platform is correctly configured to act on it.
• Regulatory intensity: Billing accuracy mandates, complaint resolution timelines, and outage notification requirements are intensifying. The 麻豆原创 CX portfolio can support compliance when features are correctly activated and configured.

麻豆原创 in utilities: a significant and growing market

Utilities are not a niche segment for 麻豆原创. Understanding the scale of the 麻豆原创 utilities community frames why the Advanced Success Plan for 麻豆原创 Customer Experience solutions matters for this industry in particular. 麻豆原创 is trusted by hundreds of utilities customers globally and is . The investment in the relationship has been made. The question is whether customers are fully using what they have.

With the Advanced Success Plan, customers can turn the 麻豆原创 Customer Experience portfolio into a driver of growth and innovation. They can gain the confidence to act decisively, supported by unlimited expert guidance and intelligent insights that help ensure every feature can deliver measurable business value.

The business case: customer retention over acquisition

For utilities operating in competitive markets, retaining customers has become as strategically important as acquiring new ones. Customers can switch suppliers in minutes via a digital platform, complaint escalation processes are visible on social media, and billing errors in a smart meter world are harder to excuse and faster to escalate.

The 麻豆原创 CX portfolio can address these challenges across the full customer lifecycle. 麻豆原创 Engagement Cloud enables targeted, segmented communications. 麻豆原创 Service Cloud can centralize complaint management and agent interactions. 麻豆原创 Sales Cloud helps manage accounts, contacts, leads, and opportunities. 麻豆原创 Commerce Cloud is the听digital sales and self-service storefront layer and can handle how customers discover, compare, purchase, and manage energy products online. What the Advanced Success Plan for 麻豆原创 Customer Experience solutions does is help to ensure these capabilities are not just purchased but adopted, optimized, and continuously improved.

How the Advanced Success Plan structures the adoption journey

The Advanced Success Plan for 麻豆原创 Customer Experience solutions helps organize the adoption journey across four distinct phases, each with a defined purpose and a set of targeted services:

1. Introducing innovation: Identify and prioritize the right innovations for your business. Services here include product guidance sessions covering areas such as utilities session and agent desktop, intelligent selling, campaigns and segmentation, and AI foundation and use case navigator.
2. Adopting innovation: Plan and prepare for structured adoption with minimal risk. Services include the AI process fit-gap analysis, key feature advisory, release guidance, success expert engagement, service planning, value management, innovation checkpoints, and adoption checkpoints.
3. Activation and optimization: Enable hands-on activation of AI and customer experience capabilities in your environment. Services include activation sessions across 麻豆原创 Sales Cloud, 麻豆原创 Service Cloud, 麻豆原创 Marketing Cloud, and 麻豆原创 Engagement Cloud; AI agent activation; embedded AI activation; Joule activation; and technical and functional assistance.
4. Success measurement and continuous improvement: Measure outcomes and sustain momentum through ongoing engagement. Services include a continuous engagement model, release guidance, success expert, value management, innovation checkpoints, and adoption checkpoints.

8 services available to utilities customers鈥攁nd how each one helps

The Advanced Success Plan for 麻豆原创 Customer Experience solutions comprises eight distinct services. Each has a defined scope, a specific business need it addresses, and measurable benefits. For utilities customers, each service connects to a characteristic operational or strategic challenge.

Product guidance
Structured sessions introduce utilities teams to the capabilities most relevant to their context, from meter-read-driven billing notifications in 麻豆原创 Service Cloud to segmented communications in 麻豆原创 Engagement Cloud. The goal is to accelerate time-to-awareness, so teams know what exists before they have to find it.

Key feature advisory
This is curated, customer-specific guidance on which features to activate and in what sequence. For utilities, this means filtering a broad 麻豆原创 CX road map down to the capabilities that matter for smart metering, complaints management, and outage communications then discarding what does not apply.

Release guidance
Every 麻豆原创 CX quarterly release brings dozens of updates. Release guidance helps ensure utilities teams receive a focused brief on what is relevant to their industry context, not a generic list of all product changes, so adoption decisions can be faster and better informed.

Solution review
This is a structured review of the current solution configuration against best practice. For utilities, this commonly surfaces configuration gaps in complaint workflows, billing notification templates, or service agent desktop layouts that erode the customer experience over time if left unaddressed.

Transformation advisory
Strategic guidance connects 麻豆原创 CX capabilities to the outcomes utilities care about most: cost-to-serve reduction, complaint resolution improvement, and regulatory compliance. Transformation advisory helps move the conversation from features to business impact.

Activation
This is hands-on, expert-assisted activation of specific capabilities in the customer’s live environment. For utilities, this includes activating Joule for service agents and enabling AI-driven case categorization in 麻豆原创 Service Cloud. Many autonomous agents or assistants announced at 麻豆原创 Sapphire, once available, can be activated to help guide service agents to process cases.

Technical assistance
Direct technical support across all phases of the engagement covers integration architecture, performance guidance, load testing guidance for mass billing cycles, and resolution of complex system behavior. This service is especially critical for utilities given the high-volume, time-sensitive nature of meter-read processing and month-end billing runs.

Functional assistance
This comprises business process and functional configuration support throughout the engagement. Utilities-specific coverage includes complaint handling workflows, outage notification sequences, and the configuration of billing determinant displays in the service agent desktop, helping to ensure what is built serves the way utilities actually operate.

A practitioner’s perspective

Working directly with utilities customers shows first-hand how the Advanced Success Plan for 麻豆原创 Customer Experience solutions can drive meaningful business value, especially for organizations without deep technical or functional 麻豆原创 CX expertise in-house. Utility companies face a specific set of challenges: complex billing architectures, regulatory requirements, and high customer expectations for responsive service. The right services delivered at the right moment can be genuinely transformational. Four patterns stand out consistently:

1. Bridging the knowledge gap for business users: Unlike system integrators or technical consultants, many utility business teams may not fully grasp the functional nuances required to maximize their 麻豆原创 investment. Value-driven customer success manager engagement becomes critical here by translating technical possibilities into business outcomes, advising on feature adoption, and ensuring cross-team alignment across operations, IT, and customer management. The customer success manager acts as connective tissue between what 麻豆原创 CX can do and what the business needs to achieve.
2. Go-live checks are the foundation for seamless launches: Utilities cannot rely on generic go-live checklists. Are meter reads flowing end-to-end? Are billing determinants and rate structures properly mapped? Are customer service orders integrated with billing and meter management systems? Comprehensive go-live checks built for the utilities context eliminate the guesswork, giving teams confidence that key processes are functioning correctly from day one, not discovered to be broken three months into the first billing cycle.
3. Road map guidance enabling better design decisions: Each 麻豆原创 CX release brings dozens of new features, but only subsets are relevant for a given customer in a given market. Regular, curated road map guidance helps utilities focus on the features and design decisions that will most efficiently drive their specific outcomes, whether that is improving customer satisfaction, streamlining operations, or enriching digital self-service. This targeted approach prevents costly missteps and empowers business stakeholders to make confident decisions without requiring deep product expertise of their own.
4. Early-phase support building for reliability and performance: The early project phase is often when performance issues and integration risks are best addressed, but it is also where internal teams feel least certain. Proactive support that includes performance reviews spanning interconnected billing and service systems, high-level architecture guidance, and utilities-specific load testing helps ensure reliable operation under real-world peak conditions. Utilities processing millions of daily meter reads, running mass billing cycles at month-end, and handling seasonal demand spikes need to know their system will hold before the peak arrives, not after it has passed.

What stronger 麻豆原创 CX adoption looks like in practice

When utilities customers engage with the full Advanced Success Plan for 麻豆原创 Customer experience solutions at the right moments, the outcomes can be concrete and measurable:

• Adoption confidence: Teams understand the 麻豆原创 CX capabilities that matter for their industry and know how to use them. Adoption is driven by guided enablement, not trial and error.
• Configuration quality: Solution reviews and functional assistance can ensure complaint workflows, billing notifications, and service processes are correctly configured, reducing workarounds and support volume.
• Release relevance: Every quarterly 麻豆原创 CX update is assessed for utilities relevance. Teams receive a focused brief on what to adopt, not a generic list of all product changes.
• AI activation at pace: Joule, embedded AI agents, and 麻豆原创 Engagement Cloud intelligence features are activated with expert assistance, helping to move from available-in-catalogue to live-in-production for utilities use cases.
• Integration reliability: Standard integrations between 麻豆原创 Service Cloud and 麻豆原创 S/4HANA Utilities are correctly configured, giving agents real-time access to meter history, billing data, and service orders.
• Transformation clarity: Transformation advisory connects the 麻豆原创 CX road map to the outcomes utilities care about most: cost-to-serve reduction, complaint resolution improvement, and regulatory compliance.

A service portfolio built for the complexity of utilities

The 麻豆原创 investment in the utilities sector is substantial and well-established. Utilities organizations around the world have already deployed the 麻豆原创 CX portfolio and are running their customer operations on it. The question is not whether they have access to world-class customer experience capabilities, but whether they are fully using what they have.

The eight services described above, combined with customer success manager-led perspectives on go-live quality, road map relevance, and performance assurance, represent a comprehensive framework for utilities organizations to realize the full potential of their 麻豆原创 CX investment.

The Advanced Success Plan for 麻豆原创 Customer Experience solutions is not a generic offering. When applied with industry focus and customer success manager expertise, it becomes a strategic asset, one that helps utilities deliver on the promise of a superior customer experience in an increasingly competitive, regulated, and technically complex market.

Rajeev Ranjan is product manager for the Advanced Success Plan for 麻豆原创 Customer Experience.
Tara Tracey is global product owner for the Advanced Success Plan for 麻豆原创 Customer Experience.

For many 麻豆原创 Commerce Cloud and 麻豆原创 Engagement Cloud customers, this gap shows up in familiar ways: recommendation engines that surface generic results because behavioral data is not connected, e-mail campaigns timed by calendar rather than by individual habit, loyalty programs that reward transactions rather than relationships, and personalization rules that require significant manual effort to maintain at scale.

The ambition is there; the infrastructure to fulfill it, however, is often partial. Clean data is siloed, AI capabilities are underutilized, and the organizational discipline to run ongoing experimentation does not yet exist.

This is precisely the problem the version for is designed to solve.

What hyper-personalization actually requires

True hyper-personalization is not a feature you switch on. It is a capability you build systematically across three interdependent layers: data, decisioning, and delivery.

Data is the foundation. Hyper-personalization requires unified, consent-aware, real-time customer profiles consolidated across commerce transactions, engagement history, browsing behavior, service interactions, and loyalty activity. Without this foundation, even the most sophisticated AI models are operating on incomplete signals.

Decisioning听is where AI translates those signals into action鈥攖he next best product to surface, the right offer to present, or the optimal moment to reach out. This layer requires not just model accuracy but governance, knowing when to trust the algorithm and when human judgment should override it.

Delivery听is where the personalized experience reaches the customer, at the storefront, in the inbox, through a mobile push, or across a loyalty interaction. This layer requires orchestration across channels, consistent with the customer’s current context.

The Advanced Success Plan for 麻豆原创 Customer Experience solutions helps address all three layers simultaneously, providing the expert guidance, governance frameworks, and adoption acceleration needed to move from point capabilities to an integrated operating model.

Hyper-personalization in 麻豆原创 Commerce Cloud

麻豆原创 Commerce Cloud can provide the storefront execution layer for personalization at scale. The solution’s AI-assisted product recommendations capability enables organizations to show the most relevant products to each visitor at the right point in their shopping journey, from trending products and related items to complimentary products that support cross-sell and upsell motions. This can go beyond manual merchandising rules; it can respond dynamically to real-time behavioral signals, helping to improve conversion performance and drive product discovery at a scale no merchandising team could replicate manually.

Yet many 麻豆原创 Commerce Cloud customers have not yet activated the full depth of these capabilities. The blockers are predictable: data quality gaps that limit recommendation model performance, integration complexity between the commerce layer and upstream profile data, and an absence of the experimentation discipline needed to tune and improve models over time.

The Advanced Success Plan for 麻豆原创 Customer Experience solutions can bring targeted guidance to help address these barriers. Data readiness assessments can establish the quality baselines and integration patterns required to feed reliable signals into 麻豆原创 Commerce Cloud’s personalization engine. Adoption accelerators help teams operationalize experimentation, defining hypotheses, running A/B tests, and translating results into durable configuration changes. The outcome is a storefront that can continuously learn and improve, rather than one frozen at the point of initial configuration.

Hyper-personalization in 麻豆原创 Engagement Cloud

麻豆原创 Engagement Cloud, powered by 麻豆原创 Emarsys, can extend personalization beyond the storefront and into the full lifecycle of the customer relationship. This is where 麻豆原创 Commerce Cloud’s transactional signals combine with engagement history to help power cross-channel personalization that is individual rather than segment-based.

The solution’s AI-assisted send time optimization capability is a direct example of this philosophy in practice. Rather than sending campaigns on a fixed schedule, the capability can analyze each contact’s behavioral patterns鈥攊ndependently of time zone, language, or region鈥攁nd deliver messages at the precise time each individual is most likely to engage. This is not personalization as a concept; it is personalization as an automated, scalable operational process.

Paired with the 麻豆原创 Emarsys, AI-assisted campaign translator capability and omnichannel orchestration, 麻豆原创 Engagement Cloud enables marketing teams to move from building campaigns to orchestrating journeys where the system is continuously learning which signals should trigger which interactions and adapting those interactions based on what drives response.

The native integration between 麻豆原创 Commerce Cloud and 麻豆原创 Engagement Cloud is a critical accelerator here. By unifying commerce behavior and engagement data, organizations can drive increases in conversion rate, purchase frequency, and average order value in ways that neither system could achieve independently. The Advanced Success Plan for 麻豆原创 Customer Experience solutions helps customers realize this joint value by aligning integration architecture, data governance, and adoption milestones across both products within a single, coordinated engagement model.

How the Advanced Success Plan enables continuous improvement

Hyper-personalization projects are often treated as one-time implementations. The Advanced Success Plan for 麻豆原创 Customer Experience solutions is designed to make them repeatable, continuously improving programs. This means:

• Outcome-based governance: Co-defining the KPIs that matter, such as conversion rate lift, repeat purchase rate, engagement open rates, and average order value, and building work streams aligned to move them measurably.
• Prescriptive adoption patterns: Structured playbooks for activating AI-assisted recommendations, send time optimization, and next-best action logic, with clear milestones and measurable gates.
• Continuous enablement: Role-based coaching for the teams responsible for data, product ownership, and campaign operations, closing skills gaps that otherwise cause personalization programs to plateau or regress.
• Proactive telemetry: Regular adoption checks that surface underperforming configurations before they impact business outcomes, and AI-guided best practices that inform ongoing tuning.

Making the business case concrete

For 麻豆原创 Commerce Cloud customers, the value of operationalized hyper-personalization can be seen in storefront metrics: higher conversion from AI-surfaced recommendations, increased average order value through intelligent cross-sell, and improved product discovery that reduces bounce and exit rates.

For 麻豆原创 Engagement Cloud customers, the value can be seen in engagement quality: open rates and click-through rates that reflect individual relevance rather than list-wide broadcast, improved campaign ROI through AI-optimized delivery, and loyalty program engagement that reflects relationship depth rather than transaction volume.

Across both, the compounding effect of unified data and orchestrated decisioning is what transforms hyper-personalization from a POC into a sustained growth mechanism, one that gets measurably better over time.

Payal Sachdev is product manager for the Advanced Success Plan for 麻豆原创 Customer Experience.
Tara Tracey is global product owner for the Advanced Success Plan for 麻豆原创 Customer Experience.

Travelers nowadays have very strict requirements. From booking a ticket to arriving at a destination, they expect fast, convenient, and prompt assistance when they face issues along the way. No matter how perfectly a system is designed to meet needs, there will always be situations that can鈥檛 be avoided. Delays, confusing booking systems, long customer service wait times, and much more create frustration for travelers.

AI is reshaping how the travel and transportation industry is doing business. It delivers more avenues to provide customer care aside from the typical communication channels such as e-mail, short messaging services, and social media. AI provides smarter, faster, and more personalized customer experiences, leading to happier customers and therefore growth in revenue for the business. AI is no longer optional, it is now becoming a necessity.

Beyond tickets and timetables: how AI orchestrates the customer journey

Previously, travelers preferred travel agents over booking apps, relied on printed tickets, and valued personal service and human interaction. However, mobile apps for bookings, check-ins, and payments are now widely used. Travelers also expect real-time updates and personalized recommendations that provide seamless, end-to-end experiences.

麻豆原创 delivers an ecosystem that can provide the tools needed to meet these expectations. Using 麻豆原创 Service Cloud, organizations can manage cases, complaints, and information requests efficiently. AI can respond within seconds, unlike traditional customer service processes that rely on manual handling of support tickets. AI-powered chatbots can also manage a high volume of customer conversations simultaneously. Here is an example integration strategy:

Intelligent selling services for 麻豆原创 Commerce Cloud

Intelligent selling services for 麻豆原创 Commerce Cloud are AI-powered services that leverage machine learning and artificial intelligence to help deliver personalized customer experiences and optimize booking strategies. These services help analyze customer booking patterns, provide contextual data across customer touchpoints, and offer recommendations that can lead to increases in revenue.

Travel accelerator

The travel accelerator for the 麻豆原创 Commerce solution is an industry-specific solution designed to enable travel companies to deliver omnichannel digital traveler engagement through 麻豆原创 Commerce Cloud. For customers that already have an existing 麻豆原创 Commerce Cloud solution, they can use the travel accelerator to help tailor it for travel business demand. It can provide real-time information to offer personalized customer experiences and reinforce customer loyalty.

Loyalty management program through integration

Organizations may need a system to reward customers for coming back, like earning points, perks, or special treatment when you repeatedly book with the same travel company. For this, an integration to a loyalty management program, either 麻豆原创 Customer Loyalty Management or a third-party solution, can be used.

The way forward

can help you achieve your business goals. As a starting point, we can create a service engagement plan that provides a tailored approach to meeting your KPIs. During this phase, we also deliver sessions to help you set up 麻豆原创 Sales Cloud, 麻豆原创 Service Cloud, and 麻豆原创 Commerce Cloud while working to ensure that travel and transportation industry best practices are followed.

With AI capabilities available across every solution, you can now categorize your customer base based on travel behaviors and patterns, as well as perform sentiment analysis on customer reviews and support tickets. The Advanced Success Plan can serve as a strategic partner in helping achieve AI objectives. Our experts, backed by deep industry knowledge, can provide guidance on the most effective path forward.

To deliver services that are aligned with each customer’s specific goals, we have organized our offerings into four phases: implementation, pre-go-live, post-go-live, and continuous improvement.

Implementation

During the implementation phase, our focus is on providing adoption guidance to help set up the solutions, from front-end applications to back-end systems. We work alongside the team to establish core capabilities needed for a successful implementation and to help ensure the solution is aligned with business requirements.

This includes, but is not limited to, application user management, key user extensibility, the 麻豆原创 CX AI Toolkit, integrations, security considerations, and other essential platform capabilities. Our goal is to help build a solid foundation that supports scalability, maintainability, and future growth while enabling teams to get the most value from the platform.

Pre-go-live

In the pre-go-live phase, our focus is to validate and safeguard the solutions that have been built throughout the implementation. The goal is to make sure systems are configured correctly, performing as expected, and ready at go-live.

This includes conducting detailed reviews of business configuration settings, evaluating system performance, validating integrations, reviewing security and user access setups, and assessing analytics and reporting capabilities. We also help identify potential risks, gaps, or areas for optimization before launch, working to ensure issues are addressed proactively.

In addition, we work with teams to confirm readiness across key functional and technical areas, helping ensure that testing has been completed successfully, critical business scenarios have been validated, and the solution is aligned with operational requirements. Performing an adoption checkpoint during this phase helps reduce risk, improve system stability, and support a smoother go-live experience.

Post-go-live

During the post-go-live phase, we work closely with the team to help ensure that recommendations and best practices identified throughout the implementation have been properly configured and are delivering the intended results.

As users begin working in the production environment, new questions, opportunities for optimization, and minor challenges often emerge. During this stage, we provide continued guidance and support to help address those items, whether they are related to business processes, system configuration, integrations, extensibility, analytics, or overall solution adoption.

Our functional and technical experts remain available to review issues, provide recommendations, and help navigate any areas that require additional attention. We also help identify opportunities for further improvements and knowledge transfer, working to ensure the organization is well-positioned to maintain, enhance, and scale the solution over time.

Continuous improvement

Finally, as part of the continuous improvement phase, we help stakeholders remain informed about new innovations and enhancements introduced through 麻豆原创 release cycles. By staying up-to-date with the latest capabilities, the team can continue to maximize the value of the solutions and drive ongoing business success.

Tara Tracey is global product owner of the Advanced Success Plan at 麻豆原创.
Geoffrey Arado is product manager for 麻豆原创 Customer Experience.

They see a personalized ad, explore a product through an AI assistant, respond to an offer in their inbox, and open your app expecting everything to simply work. They expect relevance, continuity, and immediacy across every interaction in their entire journey.

Instead, they hit friction:

• They鈥檙e asked to repeat information they already shared.
• Promotions don鈥檛 reflect inventory availability.
• Fulfillment updates arrive late or not at all.
• And when support is needed, no one has the complete picture.

These are not isolated breakdowns. They are systemic customer experience failures.

In the era of agentic AI, those moments compound quickly. Customers now assume brands understand who they are, what they need, and what is happening in real time, and they expect businesses to act on that intelligence instantly across the entire customer journey.

The agentic era is accelerating this shift dramatically.

This goes beyond surfacing insights or recommendations. Agentic AI systems are increasingly capable of planning, reasoning, decision-making, and coordinated action across networks of agents. AI is fundamentally reshaping how customer experiences are created, delivered, and optimized in real time.

But it also exposes a fundamental truth: when AI moves faster than your data, systems, and processes, it reveals everything that鈥檚 broken.

That tension鈥攂etween rising customer expectations and disconnected CX reality鈥攊s exactly what 麻豆原创 and Google Cloud are solving together with .

The customer experience reality: ambition outpacing execution

Most organizations want to deliver seamless, connected experiences, but they struggle to operationalize those moments.

According to 麻豆原创 research, 78% of businesses say AI will be essential for retaining customers in 2026. Yet fewer than two in five share their customer data across CX (37%) or CRM (39%) platforms.

This is an enterprise operations problem, and its impact is felt across the entire CX business. And when these touchpoints are disconnected, the customer feels it first. And by the time the company feels that friction, it may be too late to win that customer back.

A new model for customer experience built on trusted enterprise data

麻豆原创 Customer Experience plays a key role in the expansion of 麻豆原创 and Google Cloud’s partnership to enable a fundamentally new approach to CX鈥攐ne that connects data, AI, engagement, and commerce in real time.

鈥淎gentic customer experience starts deeper in the stack than the customer ever sees鈥攊n the quality of the data, the way processes run, and the strength of the platform underneath. With 麻豆原创 and Google Cloud, we鈥檙e building that foundation together, so AI moves beyond insight to action. This delivers continuous, intelligent experiences with the control, context, and execution required at enterprise scale.鈥�

Muhammad Alam, Member of the Executive Board of 麻豆原创 SE, 麻豆原创 Product & Engineering

麻豆原创 Commerce Cloud endorses Universal Commerce Protocol: powering the next era of agentic commerce

As digital commerce enters the age of AI-driven experiences, a new standard is emerging to reshape how consumers discover and purchase products.

The Universal Commerce Protocol is an open standard designed to enable AI agents to manage the entire shopping journey, from product discovery to checkout and even post-purchase support.

Unlike traditional commerce integrations that rely on fragmented APIs and bespoke connections, UCP creates a shared language for retailers, payment providers, and AI systems. This allows intelligent agents to interact directly with commerce platforms, dramatically simplifying how products are surfaced, evaluated, and purchased.

In essence, UCP transforms commerce from a series of disconnected steps into a unified, agent-driven experience.

, long known for powering enterprise-grade digital commerce for global brands, is now aligning with this new paradigm. As part of the growing UCP ecosystem, 麻豆原创 plans to work with Google to enable its customers to participate in AI-native commerce experiences that extend beyond traditional storefronts and help its merchants鈥� products be discovered and purchased across the Gemini app and Google Search, including AI Mode.

鈥淥ur goal with UCP is to build an open, trusted standard for the future of AI-driven commerce,鈥� said Ashish Gupta, VP/GM, merchant shopping at Google. 鈥淗aving a leader like 麻豆原创 endorse the protocol is critical as we work toward bringing seamless, secure agentic commerce to everyone.鈥�

For merchants, this means dramatically lower integration costs, faster onboarding into new AI-driven channels, and the ability to reach new customers beyond their storefront experiences.

In addition, 麻豆原创 Commerce Cloud will leverage Google Gemini capabilities to power a Shopping Assistant that brands can deploy directly to their own customers. This enables organizations to offer a real-time, AI-driven shopping experience across their digital touchpoints. The Shopping Assistant engages shoppers through chat, voice, and text to help them discover products, answer questions, and turn intent into transactions.

Unlike traditional storefront interactions, the Shopping Assistant can create a persistent, conversational experience that follows the customer across the shopping journey, continuously refining recommendations and guiding decisions in real time.

It can also curate creative ideas鈥攕uch as themed outfits or complete event concepts鈥攂y intelligently combining products based on customer requests. By unifying behavioral signals, real-time inventory, and promotional intelligence, it can increase conversion rates, improve average order value, and ensure every recommendation is both relevant and fulfillable.

麻豆原创 Engagement Cloud and Google Cloud: how agents work together for marketing

This new expanded partnership comes alongside another historic milestone for 麻豆原创 and Google Cloud, announced earlier this year. A fundamentally different approach to marketing execution is now offering marketers a new model for engagement that is built on trusted enterprise data.

By combining customer data and real-time signals like inventory, orders, and fulfillment status with operational truth, marketing teams can now build, launch, and optimize personalized customer engagements, grounded in business context and executed at scale through an autonomous multi-agent framework.

At the heart of this partnership:

• 麻豆原创 Business Data Cloud听(麻豆原创 BDC) connects semantically rich data across the enterprise with AI to help enable real-time insights and drive personalized interactions grounded in business context. This includes 麻豆原创 Business Data Cloud Connect for Google BigQuery with bidirectional, zero-copy data access and built-in enterprise-grade governance and security.

• Google BigQuery听unlocks real-time signals across the Google ecosystem, such as geolocation, weather, ad engagement, and rich analytics, for AI-driven segmentation, personalization, activation and analytics.

• 麻豆原创 Customer Experience听solutions can provide the real-time behavioral context: customer profiles, transactions, orders, service interactions, and consented engagement data.

• 麻豆原创 Engagement Cloud can activate enterprise data, AI insights, and predictions through intuitive tools and AI agents to help securely orchestrate real-time, personalized interactions across the entire customer life cycle.

Why this partnership matters

The collaboration between 麻豆原创 and Google reflects a broader shift in how commerce and marketing teams operate.

For commerce leaders:

• From search to agents: Consumers are no longer just searching. AI agents are acting on their behalf, making decisions, and completing purchases.
• From channels to ecosystems: Commerce is moving beyond owned channels into distributed, AI-powered environments like search, assistants, and chat interfaces.
• From integration to interoperability: Open standards like UCP eliminate the need for one-off integrations, enabling scalable participation in the AI economy.

With UCP, AI agents can seamlessly access product catalogs, manage carts, process payments, and handle post-purchase workflows, all without forcing retailers to rebuild their infrastructure.

For marketing leaders:

• From prompt to performance: Agentic intelligence becomes operational where business goals, enterprise signals, and marketing processes direct AI agents, translating into real customer interactions and automated lifecycle journeys.
• From manual to generative: Advanced generative capabilities powered by Google Gemini models, such as Nano Banana 2, introduce new agentic skills that help marketing teams dynamically generate messaging, imagery, and campaign variations.
• From dark data to unified data context: With every interaction grounded in business context and continuous engagement signals, messages become truly dynamic. Text messages can turn into immersive conversations with Google Rich Communication Services (RCS) and advertising creative and offers can continuously evolve.

Agents collaborate across 麻豆原创 and Google Cloud to personalize, activate, and continuously optimize campaigns in real time across engagement channels and media networks.

鈥淲ith this partnership, 麻豆原创 and Google Cloud bring together connected AI and a unified data foundation to create real-time understanding of the customer and business context. This enables organizations and CX teams to move from fragmented interactions to continuous, intelligent execution鈥攅mbedding AI into end-to-end processes and unlocking meaningful gains in productivity, speed, and business impact.鈥�

Jan Gilg, Global President Customer Success & Americas, Member of the Extended Board

Unlocking new value for enterprises

For 麻豆原创 Commerce Cloud customers, this partnership can unlock several strategic advantages:

• Increased discoverability in AI-driven shopping experiences
• Faster time-to-market through standardized integrations
• Ownership of customer relationships, even in third-party AI environments
• Future-proof architecture aligned with emerging commerce standards

As AI continues to compress the distance between intent and transaction, accessibility to agents becomes just as important as visibility in search results. In this new model, success in commerce is no longer defined by storefront experience alone鈥攊t鈥檚 defined by how effectively your products, data, and systems can be accessed, interpreted, and transacted on by AI agents.

For customers, this partnership unveils a new network of interoperable AI agents, grounded in enterprise data and shared context听across 麻豆原创 and Google. Organizations can achieve measurable outcomes, including:

• Faster speed-to-market through autonomous campaign and content generation
• Lower operational overhead by eliminating manual execution steps
• Always鈥憃n optimization that continuously improves performance
• Higher ROI through relevant, timely, and consistent engagement at scale

Marketers can spend less time managing workflows and more time shaping strategy, creative direction, and customer value.

鈥淲hat matters is delivering real value to our customers. As customer experience becomes more agentic, organizations need to move faster, stay connected, and operate consistently across every interaction. By bringing commerce, marketing, and service together, we help our customers reduce complexity, respond more quickly, and deliver more relevant experiences that strengthen engagement and drive sustainable growth.鈥�

Manos Raptopoulos, Global President Customer Success Europe, APAC, Middle East & Africa and Member of the Extended Board 麻豆原创 SE

The future of AI-driven commerce and marketing: what this means for your CX strategy

The partnership between 麻豆原创 and Google for marketing and commerce听marks a foundational shift toward what many are calling an agentic revolution鈥攁 world where AI doesn鈥檛 just assist CX teams and shoppers but actively participates in the buying process and shapes their customer experience.

For enterprise CX leaders, the message is clear: success in this new era will depend on how well your commerce and marketing platform can communicate with AI agents. With 麻豆原创 and Google Cloud, 麻豆原创 Customer Experience is positioning itself鈥攁nd its customers鈥攖o thrive in that future.

Across industries, customers are moving from pilots to production. They are investing in systems that can run pricing, orders, fulfillment, and service end-to-end, with AI actively driving decisions and outcomes. They are not looking for more tools. They are looking for results.

This is where 麻豆原创 has a clear point of view. Customer experience (CX) only works when it is connected directly to execution.

麻豆原创 Customer Experience is integrated with 麻豆原创 Cloud ERP across pricing, order management, fulfillment, billing, and service. AI operates inside these processes using real business data. That means every customer interaction can reflect what the business can deliver.

This is the shift now underway, and it is creating immediate opportunities for partners.

麻豆原创 partners are the ones who bring this to life. They take product capabilities and turn them into working solutions that improve conversion, increase fulfillment accuracy, and reduce service cost.

The next wave of growth will be led by partners who move quickly and build on this foundation.

Customer experience is now measured by what gets done

Customer experience is no longer judged by engagement metrics alone. It is judged by outcomes. Customers expect:

• Accurate pricing at the moment of purchase
• Real product availability, not estimates
• Orders that are fulfilled as promised
• Service that resolves issues without repetition or delay

When these things work, the experience works. When they fail, the problem is immediately visible.

AI is increasing the speed of every interaction. It is also exposing execution gaps faster than ever before. If pricing, inventory, or order data are inconsistent, customers see it instantly.

This is why customer experience and execution can no longer be separated.

AI is now driving actions, not just insights

AI is already acting inside key business processes. As seen in the , in 麻豆原创 CX today:

• Marketing, content, and campaign assistants can orchestrate segmentation, content creation, and optimization based on live performance signals.
• Commerce, merchandising, shopping, and order management assistants can connect discovery, conversion, and fulfillment to real-time inventory and pricing.
• Sales assistants help guide deal qualification and deal execution by linking pipeline signals to pricing, availability, and fulfillment data.
• Case and service management assistants help automate routine interactions while maintaining full context across orders, entitlements, and history.

These are not future scenarios. These capabilities are available and in use. But they only work when they are connected to trusted business data.

Without that, AI creates errors at scale. With it, AI drives measurable improvement.

Autonomous CX connects experience to execution

Autonomous CX connects core products and processes across the business, operating on a shared business context. It brings together 麻豆原创 Commerce Cloud, 麻豆原创 Sales Cloud, 麻豆原创 CPQ, 麻豆原创 Service Cloud, 麻豆原创 Field Service, 麻豆原创 Engagement Cloud for marketing, and 麻豆原创 Cloud ERP across finance, supply chain, and order management.

This is not a set of disconnected applications. It is a unified system where customer interactions and operational processes run on the same data foundation. Pricing, inventory, orders, and service are consistent across every touchpoint.

As a result, AI can move from recommendation to execution, working to ensure that every interaction is grounded in what the business can deliver. It can also remove the integration gaps that slow down CX execution.

麻豆原创 CX partners are moving faster from projects to outcomes

This shift is changing what customers expect from partners. Customers are not asking for system implementations. They are asking for outcomes such as:

• Faster time to deploy
• Higher conversion rates
• Improved order accuracy
• Lower cost to serve

麻豆原创 provides a strong starting point with embedded assistants, standard integrations, and prebuilt industry scenarios. Partners are building on this to deliver complete solutions. This is where differentiation happens.

Where partners are creating value today

The opportunity is not theoretical. It is already visible in active partner work.

Across 麻豆原创 CX:

• The cloud ERP edition of 麻豆原创 Commerce Cloud can connect storefront, pricing, ordering, and fulfillment in one model.
• 麻豆原创 Revenue Growth Management and 麻豆原创 Retail Execution support trade planning and in-store performance.
• Intelligent applications help package AI use cases across marketing, sales, and service.
• 麻豆原创 Service Cloud with partner integrations such as Parloa enables automated, context-aware service interactions.

麻豆原创 CX partners are turning these capabilities into repeatable offerings. Examples include:

• Industry packages for retail and CPG combining commerce, pricing, and fulfillment
• Preconfigured deployments of 麻豆原创 Sales Cloud and 麻豆原创 Service Cloud that reduce time to go-live
• Integration connectors linking 麻豆原创 CX with existing commerce, loyalty, and service platforms
• Extensions to CPQ and sales workflows that improve deal margin and approval speed
• Service automation scenarios that reduce manual case handling using real order and entitlement data
• AI-driven discovery connected directly to 麻豆原创 Commerce and 麻豆原创 Commerce, order management

These are practical, deployable solutions that can deliver measurable results.

The ecosystem is expanding what鈥檚 possible

麻豆原创 is strengthening this model through partnerships. Recently announced partnerships with companies such as Amazon Web Services, Google Cloud, Parloa, and Vercel enable new interaction models like conversational commerce, AI-driven search, and composable digital experiences.

What matters is that these experiences connect back to 麻豆原创 for execution. Orders, pricing, fulfillment, and service remain consistent across every channel. This gives partners the freedom to innovate on the experience layer while relying on 麻豆原创 for reliable execution.

A new economic model for partners

The economics for partners are changing. With Autonomous CX, partners can build:

• Industry solutions that can be reused and scaled
• Implementation packages that shorten delivery timelines
• Extensions and integrations that apply across customers
• Ongoing services for AI optimization and governance
• New offerings built around AI assistants, AI agents, and orchestration
• Higher-value transformation programs that combine AI, data, and process design

This creates a more predictable and repeatable revenue model. It also strengthens long-term customer relationships.

Now is the time to act with 麻豆原创 CX

Customers are making decisions now. They are selecting platforms and partners that can deliver AI-driven execution across customer experience. They are looking for partners who can:

• Connect CX to ERP processes
• Deliver solutions that work out-of-the-box and scale
• Improve measurable business outcomes

麻豆原创 provides the foundation. The platform is in place. The capabilities are real. The next step is execution.

Partners who move now can define the use cases, build the offerings, and lead in their industries. The momentum is already building. This is the moment to accelerate it.

What partners should do next

To move from opportunity to execution, partners can act now.

• See what is available today. Explore the latest AI-driven CX capabilities and partner opportunities in the .
• Understand the foundation for Autonomous CX. Learn how 麻豆原创 connects experience to execution with the .
• Deepen expertise and accelerate readiness. Gain a stronger understanding of Autonomous CX and partner use cases:
• Engage now and shape the next wave. Join the upcoming executive briefing to understand how to position and deliver these solutions:
  • June 18:
• Strengthen credibility and scale impact. Advance your go-to-market and positioning through certification:

麻豆原创 is not asking partners to start from scratch. The platform, capabilities, and ecosystem are already in place. The opportunity now is to build, differentiate, and lead.

Karl Fahrbach is chief partner officer at 麻豆原创.
Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience.

The results, which are driven by authentic customer feedback, highlight the strength of 麻豆原创 CX, particularly in the enterprise segment.

鈥淓arning a Leader position in a G2 Report is highly competitive and rooted in verified customer reviews,鈥� said Godard Abel, co-founder and CEO, G2. 鈥淐ongratulations to 麻豆原创 Customer Experience for achieving this distinction. Buyers can be confident this ranking reflects the authentic experiences of real users.鈥�

Following are a few standout achievements:

• :听Reigned supreme in the commerce space, achieving the coveted听#1 Rank听in the听Enterprise Grid庐 Report for Order Management. It was also recognized as a Leader for E-Commerce Platforms and Omnichannel Commerce.
• :听Showcased its versatility and power, earning a Leader position in multiple reports for CRM and Sales Analytics. It secured an impressive听#2 Rank听in the听Enterprise Grid庐 Report for CRM.
• :听Named a Leader in the highly competitive听Enterprise Grid庐 Report for Help Desk, solidifying its position as a top-tier solution for customer service excellence.
• : Dominated the marketing and engagement space, earning a whopping 51 G2 Summer 2026 badges, including #1 in the Momentum Grid庐 for Location-Based Marketing and #1 in the Enterprise Grid庐 for Email Deliverability, up from #3. Also recognized as a Leader in Marketing Automation, Personalization Engines, Customer Journey Analytics, SMS Marketing, and Loyalty Management, with new country reports added across Spain, Italy, and France.

This verified success is powered by pioneering work in agentic AI with Joule, 麻豆原创鈥檚 generative AI copilot. They鈥檝e moved beyond simple automation to deploy autonomous AI agents that can reason, plan, and act across the entire customer journey.

Customers are enthusiastically adopting these intelligently automated capabilities. The is transforming keyword searches into conversational discovery and guided purchases, while the is autonomously resolving inquiries, improving satisfaction, and reducing contact center load.

The shift to AI-driven engagement is delivering real-world value and simplifying complex processes. Using , customers can embed AI-powered guidance directly into workflows, transforming employees into experts. By enabling teams to work smarter and faster across 麻豆原创 Commerce Cloud, 麻豆原创 Sales Cloud, 麻豆原创 Service Cloud, and 麻豆原创 Engagement Cloud, unlocking the full potential of your 麻豆原创 investment and delivering the exceptional outcomes that customers demand has never been easier. By automating routine and complex workflows with out-of-the-box AI agents, teams are freed to focus on strategic, high-value customer interactions, driving unprecedented efficiency and loyalty.

G2 SUMMER 2026 Grid庐 Reports: What 麻豆原创 CX customers are saying

麻豆原创鈥檚 commitment to delivering exceptional customer experiences is reflected in the high praise for听麻豆原创 Commerce Cloud, 麻豆原创 Sales Cloud, 麻豆原创 Service Cloud, and 麻豆原创 Engagement Cloud. This recognition is a true testament to the trust our customers place in 麻豆原创 CX when it comes to powering their most critical business functions.

Here鈥檚 what users said about 麻豆原创 Commerce Cloud:

鈥淚 like 麻豆原创 Commerce Cloud’s ability to handle extreme complexity while unifying diverse business models (B2B, B2C, B2B2C) on a single platform. Its unified approach allows us to manage operations on a single technology stack, eliminating data silos, reducing operation costs, and giving us total visibility into our entire supply chain.鈥�

– Suryakant G, Managing Director ()

鈥淭he onboarding resources and 麻豆原创 support ecosystem make implementation easier, while its AI-driven recommendations, search optimization, and customer behavior insights help deliver more personalized experiences and smarter business decisions.鈥�

– Vedant G., Manager ()

Here鈥檚 what users said about 麻豆原创 Sales Cloud:

鈥淲hat really clicks for me with 麻豆原创 Sales Cloud is how effortlessly it syncs sales and marketing data in one smart dashboard. It gives me crystal-clear insights into customer behavior and pipeline status, which is pure gold for crafting targeted, automated email campaigns that feel timely and personal.鈥�

– Grecia L., Marketing Automation Specialist ()

鈥淚t addresses inefficiency and lack of visibility in the sales cycle. The main benefit is a faster, more predictable revenue stream, supported by AI and real-time data integration.鈥�

– Kuldeep D., Senior Technical Specialist ()

Here鈥檚 what users said about 麻豆原创 Service Cloud:

鈥淚 appreciate its automated processes and great SLA tracking, which helps the team to keep track of time and not miss deadlines. I also like the AI replies that enable quick responses by searching through the knowledge base. The automatic ticket routing is a valuable feature as it aids in queue management, ensuring efficient handling of customer issues.鈥�

– Kelvin E., Support Engineer ()

鈥溌槎乖� Service Cloud addresses the challenge of fragmented customer service data by consolidating all interactions and cases into one platform. This gives me clearer visibility into customer history, helps resolve issues more quickly, and supports consistent omnichannel service.鈥�

– Rekha S, Content Creator ()

Here鈥檚 what users said about 麻豆原创 Engagement Cloud:

鈥淚 love how 麻豆原创 Engagement Cloud personalizes campaigns at scale and automates customer journeys using real-time data and AI insights.鈥� ()

Shaping the future of customer experience, together

The G2 leadership awards validate the 麻豆原创 CX strategy, while investment in agentic AI defines the future.

Users can share feedback on G2 for听, for听, and听for .听

The version for , part of the 麻豆原创 Services and Support portfolio, is the helping organizations adopt, activate, and scale the 麻豆原创 Customer Experience and AI innovations announced at 麻豆原创 Sapphire.

The proactive, expert-led engagement model is built to de-risk transformation, accelerate time to value, and sustain measurable outcomes across customer experience initiatives. It combines guided adoption, prescriptive functional and technical assistance, AI-powered best practices, and continuous value realization aligned to the realities of modern customer experience (CX): AI at the core, unified data, omnichannel at scale, retention over acquisition, service-led growth, and persistent skills gaps in a rapidly evolving digital landscape.

At its heart, the Advanced Success Plan for 麻豆原创 Customer Experience brings together the right expertise at the right time, program governance, solution experts, value advisors, and adoption specialists. This helps teams execute faster and smarter with 麻豆原创 Customer Experience.

What sets the Advanced Success Plan apart

• Outcome-based: Business outcomes and key value indicators are co-defined with teams, with milestones and workstreams aligned to deliver measurable Autonomous CX results.
• Proactive by design: AI Assistants, adoption checks, and innovation accelerators are embedded throughout, reducing risk and compressing time to value as agentic capabilities evolve.
• Continuous enablement: Role-based best practices and coaching are tied directly to the Autonomous CX road map, closing skills gaps at pace as new AI and platform capabilities become available.
• Cross-solution orchestration: Unified processes and shared business context across marketing, commerce, sales, and service break silos and enable enterprise-scale execution.

This is the first of a planned series to deep dive on the topics below. Here, we start with introducing how the Advanced Success Plan for 麻豆原创 Customer Experience helps operationalize seven macro trends shaping modern customer experience.

1. AI鈥憄owered customer experiences

AI now underpins everything from next best engagement to intelligent service resolution. The Advanced Success Plan embeds AI adoption patterns directly into the delivery approach, identifying high value use cases, calibrating data prerequisites, and guiding model governance.

The results are prioritization of high鈥慽mpact starting points, a plan to scale with guardrails, accelerating time from pilot to production and grounding every decision in 麻豆原创鈥檚 CX AI capabilities and product road map.

2. Hyper鈥�personalization at scale

Personalization demands more than algorithms; it requires clean, consent鈥慳ware data, robust decisioning, and experimentation discipline. The Advanced Success Plan delivers:

• Data readiness assessments and integration patterns to enrich customer profiles and segments
• Governance and testing playbooks to validate personalization hypotheses at scale
• Prescriptive journeys to operationalize next best action across every customer channel

The result: hyper personalization moves from proof of concept to standard operating model.

3. Unified customer data and breaking down silos

Siloed data undermines CX. We help establish a unified data foundation and harmonized identities, aligning business, data, and integration teams. With technical guidance and adoption accelerators, users can move faster toward a single view of the customer to fuel analytics, personalization, and service excellence.

The results are unified profile use cases, data quality baselines, and source鈥憃f鈥憈ruth decisions to reduce duplication and latency.

4. Omnichannel commerce and B2B digital transformation

Modern buyers expect seamless journeys across web, mobile, marketplace, and partner portals, especially in B2B. The plan accelerates omnichannel capability build鈥憃ut by uniting commerce, order sourcing, pricing, and fulfilment patterns, supported by outcome鈥慴ased governance.

The result: Channel consistency, catalogue and contract complexity, and the alignment of service and sales motions are all addressed, driving measurable improvement in conversion rates and repeat purchase.

5. Customer retention over acquisition

Acquisition costs are rising and retention is the new growth engine. The Advanced Success Plan helps operationalize retention strategies, churn prediction, intelligent engagement, loyalty, and proactive service across the CX stack.

The result: We align metrics such as retention rate, customer lifetime value, and service鈥憈o鈥憆evenue contribution, and ensure the data foundation supports them.

6. Service as a revenue driver

Service is no longer a cost center; it鈥檚 a growth channel. We guide users to productize services, monetize value鈥慳dded offerings, and embed outcome鈥慴ased contracts. The plan includes:

• Playbooks for cross鈥憇ell/upsell from service interactions
• Knowledge and field service patterns to improve first鈥憈ime fix and attach rates, KPI frameworks for service鈥憀ed growth

The result: With prescriptive governance and AI鈥慸riven intelligence, service organizations move from reactive cost management to consistent, measurable contribution to top鈥憀ine revenue and customer retention.

7. Navigating digital transformation complexity and skills gaps

Large transformation programs falter on orchestration and capability enablement. The Advanced Success Plan addresses both by:

• Establishing a cadence of value sprints and decision forums
• Providing role鈥慴ased enablement covering functional and technical assistance, data, product ownership, end-user adoption, and change management
• AI-guided best practices embedded throughout delivery to eliminate rework and accelerate quality outcomes across Industry AI scenarios

Organizations execute with confidence, even amid shifting requirements, resource constraints, and rapidly evolving agentic AI capabilities.

Measurable outcomes

• Accelerated time to first value through prioritized, AI-ready use cases aligned to capabilities
• Higher adoption and sustained performance via continuous enablement
• Reduced program risk through proactive governance, telemetry, and structured decision forums
• Measurable gains in conversion rates, customer retention, and service-led revenue contribution across the full CX stack

Getting started

• Define Autonomous CX priorities: Identify two to three priority outcomes for the next two quarters facilitated by the 麻豆原创 Value Management service.
• Assess readiness: Evaluate data, integration, governance, and enablement gaps to define a 12 to 18 month engagement plan.
• Engage the Advanced Success Plan: Align workstreams, milestones, and metrics with our expert team.听
• Industrialize and scale: Convert proven delivery patterns into reusable accelerators, deployable across regions and lines of business.

This series will examine each of the seven trends in depth, demonstrating how the Advanced Success Plan for 麻豆原创 Customer Experience translates CX strategy into repeatable execution and measurable business outcomes.

Tara Tracey is a global product owner at 麻豆原创.

AI is what brings that ambition within reach. It helps companies act faster, personalize at scale, and engage in new ways. But it is also raising expectations. Every interaction now reflects how well the business runs.

When a customer places an order or asks for help, the experience depends on what happens behind the scenes. If pricing is inaccurate, inventory is uncertain, or fulfillment falls short, the experience breaks.

That is why customer experience is now defined by execution. Customers do not experience systems or intent. They experience outcomes.

Agentic AI can increase speed, intelligence, and personalization. But speed alone does not improve customer experience. It amplifies what is already there. When execution is aligned with process, data and governance, AI drives better outcomes. When it is not, AI exposes the disconnect.

Aligning experience and execution

Autonomous CX brings agentic AI directly into the processes that run the business instead of layering it on top of disconnected systems. It connects AI assistants across marketing, commerce, sales, and service onto a shared business context across 麻豆原创 CX, 麻豆原创 Cloud ERP, supply chain, and connected systems. Orders, inventory, pricing, and financials are defined once and used consistently, so decisions are based on live operational reality.

At the center of this shift are AI assistants and autonomous agents. Assistants coordinate multiple agents across end-to-end customer workflows, from discovery to fulfillment, engagement to service, and issue to resolution.

At 麻豆原创 Sapphire, we highlighted assistants that make this real across the portfolio:

• In marketing, Content Assistant and Campaign Assistant orchestrate intent understanding, content creation, segmentation, optimization, and campaign execution within governance controls.
• In commerce, Merchandising Assistant, Shopping Assistant, and Order Management Assistant connect discovery, conversion, and fulfillment to operational reality.
• In sales, Sales Assistant, Deal Qualification Assistant, and Deal Closing Assistant move sellers from signal to execution.
• In service, Case Management Assistant and Service Management Assistant improve resolution and service quality, with additional assistants purpose-built for self-service, HR service, and accounts receivable workflows.

AI-driven discovery and engagement grounded in business reality

麻豆原创鈥檚 collaboration with Google follows the same principle: connect AI-driven discovery and engagement to business execution.

Together, 麻豆原创 and Google are focused on three priorities: first, applying the latest AI models, including Gemini, to deliver high-quality customer experiences; second, supporting industry standards and open protocols to enable interoperability across ecosystems; third, enabling seamless, personalized journeys across channels and Google surfaces such as Shopping and Gemini.

By combining 麻豆原创鈥檚 governed business data with Google鈥檚 AI capabilities, assistants and agents can connect customer intent from storefronts, search, and AI-driven channels to 麻豆原创 commerce and order processes. This ensures that what customers see reflects what the business can fulfill.

This is also why 麻豆原创 is adopting and expanding how 麻豆原创 product data can power AI-driven experiences wherever customer intent originates. This keeps experiences aligned with pricing, inventory, and fulfillment in real time.

麻豆原创 Commerce Cloud innovations

麻豆原创 continues to be recognized in analyst evaluations, including the Gartner庐 Magic Quadrant™ for Digital Commerce, where 麻豆原创 has been positioned as a Leader for 11 consecutive times.

, trusted by the largest enterprises, now extends to mid-market and growing companies on 麻豆原创 Cloud ERP. The new 麻豆原创 Commerce Cloud, cloud ERP edition delivers a standardized, end-to-end approach, reducing complexity, leveraging AI natively, and accelerating time to value. It connects discovery through fulfillment via tight integration with 麻豆原创 Cloud ERP.

For digitally mature organizations, 麻豆原创 is expanding composable commerce with new and modular cart and checkout services. These services integrate with core processes such as pricing, promotions, loyalty, tax, payments, inventory, sourcing, and order management across 麻豆原创 and non-麻豆原创 touchpoints. This helps organizations modernize their architecture while maintaining end-to-end execution.

麻豆原创 is also expanding its ecosystem with Vercel to accelerate storefront development and deployment with optimized performance, scalability, and composable front-end experiences.

In payments, 麻豆原创 Unified Payment, powered by Adyen, embeds global processing directly into the commerce flow to simplify integration and improve conversion. 麻豆原创 also continues to enhance its open payment framework with pre-integrated providers, such as Checkout.com and PayPal, giving customers flexible provider choices that are easy to configure and use.

Together, these capabilities reduce total cost of ownership, speed deployment, and make it easier to deliver better experiences at scale.

Sales execution turns insight into action

Customer experience extends into sales execution, where teams need clear next steps and confidence those actions can be fulfilled.

We introduced new innovations, including field sales capabilities for retail execution processes in consumer goods companies and other field-selling environments. These capabilities provide rich mobile experiences that work offline, making it easier to plan store visits, capture in-store activity, and manage execution in real time.

Sales leaders gain connected insights tied directly to pricing, inventory, and order processes, leading to more consistent execution and better outcomes.

Scaling trusted autonomous service

Autonomous CX is strengthened through partnerships that extend execution while preserving trust and governance.

Our combines its agentic AI-driven voice and digital self鈥憇ervice with service, order, and entitlement data from 麻豆原创 Service Cloud. AI-driven automation can handle routine interactions with full context, escalating seamlessly and with continuity to service teams when human expertise is needed. This approach helps organizations scale service without breaking trust and ensures customer interactions remain connected to real business processes.

麻豆原创 is also expanding its partnership with Amazon to scale AI-driven service across voice and digital channels, enabling faster, more consistent resolution while keeping service execution grounded in real-time business data.

Industry AI in action

We are also showcasing Industry AI scenarios that demonstrate how assistants and autonomous capabilities operate in real business environments.

Autonomous Revenue Growth Management supports trade planning teams and key account managers in consumer products companies that sell through retailers, with applicability to agribusiness and wholesale distribution. Industry鈥憇pecific Joule Assistants provide AI鈥慸riven insights across trade planning and execution, helping teams identify growth opportunities, optimize commercial terms and respond more quickly to performance signals. The result is more predictable growth with fewer downstream exceptions.

Unified commerce supports merchandising and operations teams across retail, wholesale, and direct-to-consumer models. Unified commerce connects demand, inventory, and customer data across channels, with Joule Assistants guiding decisions on assortment, pricing, and placement. The result is more consistent execution and faster decisions.

The next phase of customer engagement

Across these innovations and Industry AI scenarios, the pattern is clear. AI delivers value only when it acts on shared, trusted context. When experience and execution stay aligned, speed becomes a source of trust instead of risk.

This is how 麻豆原创 is approaching the future of customer experience: as a coordinated system where every decision is visible, and every promise can be kept.

Balaji Balasubramanian is president and chief product officer of 麻豆原创 Customer Experience.

The CX innovations and Industry AI scenarios highlighted here are planned for general availability in Q3 2026.
The capabilities announced as part of 麻豆原创鈥檚 Autonomous Enterprise run across 麻豆原创 Cloud ERP, including 麻豆原创 Cloud ERP Private.
Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner鈥檚 business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.
Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates.

Instead, they immediately encounter friction. They鈥檙e asked to repeat information they鈥檝e already shared across multiple channels and departments. Then they see an offer for the item they just purchased, rather than something similar or new. And when they encounter an issue down the line, customer support doesn鈥檛 recognize their history.

Micro moments like these do not feel minor to customers anymore. They feel inexcusable. Customer expectations have changed faster than most brands can keep up. Customers now assume brands know who they are, what they need, and what鈥檚 happening right now. And they expect brands to act on that knowledge instantly.

At the same time, businesses are embracing a new era of AI. Dubbed “agentic AI,” it represents a paradigm shift where AI doesn鈥檛 just analyze or recommend products, but increasingly plans, decides, and acts through a network of agents. This creates a massive opportunity for customer experience (CX) leaders today, in particular marketers, who, according to McKinsey, are leading in AI adoption amongst business functions. But it also raises the stakes.

Because when AI moves faster than your data, systems, and processes, it exposes everything that鈥檚 broken. That tension鈥攂etween rising expectations and disconnected reality鈥攊s exactly what 麻豆原创 and Google Cloud are addressing together.

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The marketer鈥檚 reality: ambition outpacing execution

According to recent , more than half of marketers say fragmented or outdated data prevents them from acting in the moment. Insights arrive too late. Activation requires manual stitching across tools. And even the best strategies stall before they ever reach customers.

It is clear that most organizations genuinely want to deliver great customer experiences. But fragmentation is what stands in the way of delivering connected, meaningful engagements.

On one side: Customers expect effortless, relevant, and real-time experiences. On the other hand, organizations still operate with fragmented data, siloed teams, and delayed insights.

Our latest reveals that customers are increasingly frustrated: 45% say brands can鈥檛 keep up with changing expectations, and 44% say interactions feel less personal than before.鈥�

AI accelerating the engagement divide 

The disconnect between what customers feel and what businesses believe is the “.” Customer signals live across disconnected systems. Data arrives late or without context. Execution happens separately from insight. And while customers feel this friction immediately, many companies do not realize how disconnected their experiences truly are in their customers’ eyes. Now, AI is accelerating this divide.

Agents can generate content, launch campaigns, and optimize engagement at unprecedented speed. But when those agents act on incomplete, outdated, or fragmented data, they only exacerbate inconsistency and poor customer experiences.

When talking to our customers, it鈥檚 clear that there is no shortage of ambition when it comes to AI. In our research, 78% of brands say AI will be integral to their customer retention efforts this year. But only 46% of brands can connect their data in a way that is accessible to power AI sustainably.

The real challenge for CX leaders today is ensuring that AI has the right foundation: trusted data, unified context, and direct connection to execution.

New model for engagement built on trusted enterprise data

麻豆原创 and Google Cloud are expanding their partnership to enable a fundamentally different approach to marketing execution, one grounded in trusted enterprise data and real-time signals, accelerated with multi-agent coordination, and delivered at scale through 麻豆原创 and Google鈥檚 customer engagement solutions.

麻豆原创 provides both operational truth for elements such as inventory, orders, and fulfillment status, and deep customer knowledge across customer experience interactions. Google Cloud brings additional real-time signals and analytics, along with advanced AI. Combined, they create a shared, real-time understanding of the customer, grounded in business and situational context.

At the heart of this partnership:

• 麻豆原创 Business Data Cloud (麻豆原创 BDC) connects semantically rich data across the enterprise with AI to enable real-time insights and drive personalized interactions grounded in business context. This includes 麻豆原创 Business Data Cloud Connect for Google BigQuery.
• Google BigQuery unlocks real-time signals across the Google ecosystem, such as geolocation, weather, and rich analytics, through bidirectional, zero-copy data access with 麻豆原创 BDC, while ensuring enterprise-grade governance and security.
• 麻豆原创 Customer Experience applications provide the real-time behavioral context 鈥� customer profiles, transactions, orders, service interactions, and consented engagement data.
• 麻豆原创 Engagement Cloud activates enterprise data and AI insights and predictions to securely orchestrate real-time, personalized interactions across the entire customer life cycle.

With these innovations, marketers can finally move from insight to execution automatically.

To realize the full potential of agentic AI, businesses need their systems to speak the same language. By uniting 麻豆原创’s enterprise data and customer engagement platform with Google Cloud’s AI, we鈥檙e enabling marketers to move beyond simple automation to multi-agent orchestration, driving dynamic campaigns that reason and adapt to market shifts in real time.

Kevin Ichhpurani, President, Global Partner Ecosystem at Google Cloud

From prompt to performance: how agents work together for marketing

Another critical element of this new execution model is agent interoperability. Gemini Enterprise acts as a central hub for multi-agent coordination, enabling  customers鈥� agents to securely exchange context and take action across platforms. Meanwhile, Joule acts as the engagement layer within 麻豆原创 applications, executing tasks, orchestrating campaign and content workflows, and optimizing marketing outcomes. Working together, 麻豆原创 and Google are enabling true multi-agent orchestration connected to trusted enterprise data.

Within this broader CX transformation, 麻豆原创 Engagement Cloud is where agentic intelligence becomes operational for marketing teams. It is the environment where enterprise signals, generative media, and AI agents translate into real customer interactions and automated lifecycle journeys.

Advanced generative capabilities powered by Google Gemini models, for example, Nano Banana 2, introduce new agentic skills that help CX teams dynamically generate messaging, imagery, and campaign variations. Through assistants and agents in Joule, these capabilities become embedded directly into marketing workflows, allowing brands to adjust tone, localize content, and respond instantly to changing conditions.

It is not just content generation and personalization that are being rewired. With unified data context and interoperable agents, mobile messaging can turn into immersive conversational experiences with Google Rich Communication Services (RCS) and advertising audiences, and creative, which can continuously evolve based on real-time performance and business signals, transforming campaigns into intelligent, self-optimizing systems.

And through this multi-agent network, marketers will not need to build every step of a campaign manually. Instead, they define the goal, gain more time to focus on strategy and creativity, and let agents handle the rest.

For example, a marketer can prompt:

• 鈥淚ncrease repeat purchases from customers in the last 30 days.鈥�
• 鈥淢aximize customer lifetime value while reducing campaign operational costs.鈥�

And from there:

• Joule Agents coordinate content production, grounded in customer and enterprise data, understand business context, customer history, and constraints
• Google鈥檚 Gemini Models and agents generate creative variations, messaging, and channel-specific content
• Agents collaborate across 麻豆原创 and Google Cloud to personalize, activate, and continuously optimize campaigns in real time across engagement channels and media networks

This is more than a data integration. It鈥檚 a leap forward for AI agents that can collaborate naturally and execute seamlessly. By combining 麻豆原创 Business Data Cloud Connect for Google with interoperable AI agents across 麻豆原创 and Google, we鈥檙e giving organizations a path from AI experimentation to AI-empowered customer experience at scale. Marketers can spend less time on manual tasks and more time shaping the customer journey.

Balaji Balasubramanian, President and Chief Product Officer, 麻豆原创 Customer Experience and Consumer Industries

Clear business outcomes for marketing teams

By enabling a network of interoperable AI agents and grounding them in enterprise data and shared context across 麻豆原创 and Google, organizations can achieve measurable outcomes, including:

• Faster speed-to-market through autonomous campaign and content generation
• Lower operational overhead by eliminating manual execution steps
• Always鈥憃n optimization that continuously improves performance
• Higher ROI through relevant, timely, and consistent engagement at scale

Marketers can spend less time managing workflows and more time shaping strategy, creative direction, and customer value.

Beyond campaigns: continuous engagement at enterprise scale

While marketing is a natural starting point, this is just the beginning. Customer engagement does not live in one system or team. Engagement spans commerce, service, sales, supply chain, and operations. A brand promise made in a message must be fulfilled by inventory. A personalized offer depends on pricing, availability, and delivery. And a single customer service interaction can shape the future of customer loyalty and lifetime value.

This multi-agent model is designed to support high-value use cases across the 麻豆原创 Customer Experience portfolio, laying the foundation for an AI-driven customer experience powered by trusted, unified, real-timedata.

In an AI-driven world, customer experience goes beyond any single interaction鈥攊t’s defined by every touchpoint a customer has with your company.

Customers can deploy Joule Agents in 麻豆原创 CX Solutions to build, launch, and optimize marketing campaigns

Gemini Enterprise acts as a central hub for agents to take action across 麻豆原创 and Google Cloud platforms

LAS VEGAS 鈥� (NYSE: 麻豆原创) and Google Cloud today announced a new partnership that will help marketers put AI agents to work at scale.

Through new integrations between the 麻豆原创 Engagement Cloud, 麻豆原创 Customer Experience (麻豆原创 CX) and Joule solutions and Gemini Enterprise, joint customers can now deploy agents that securely access unified data stored across both ecosystems to execute complex marketing strategies based on high-level goals defined by the user.

Together, 麻豆原创 and Google Cloud provide a unified foundation for data and AI agents to operate across both ecosystems. Gemini Enterprise will act as a central hub for data integrations and multi-agent coordination, allowing agents to take action across a customers鈥� 麻豆原创 and Google Cloud solutions. These integrations will be supported by the 麻豆原创 Business Data Cloud Connect solution for Google and BigQuery, which enable bidirectional, zero-copy data access between the two platforms, with enterprise-grade security and governance. Capabilities across both Gemini Enterprise and agent gateway APIs from 麻豆原创 will allow customers鈥� agents to more securely exchange context, trigger actions and optimize outcomes across platforms, enabling true multi-agent orchestration.

The integration allows marketers to prompt an agent within 麻豆原创 Engagement Cloud with a clear objective like, 鈥淚ncrease repeat purchases from the last 30 days,鈥� or 鈥淢aximize customer lifetime value while reducing campaign operational costs.鈥� An agent, like a Joule Agent, will handle the end-to-end process鈥攆rom content personalization to visualization to conversational engagement.

鈥淭his is more than a data integration; it鈥檚 a leap forward for AI agents that can collaborate naturally and execute seamlessly,” said Balaji Balasubramanian, President and Chief Product Officer, 麻豆原创 Customer Experience and Consumer Industries. 鈥淏y combining 麻豆原创 Business Data Cloud Connect for Google with interoperable AI agents across 麻豆原创 and Google Cloud, we鈥檙e giving organizations a path from AI experimentation to AI-enabled customer experience at scale. Marketers can spend less time on manual tasks and more time shaping the customer journey.

鈥淭o realize the full potential of agentic AI, businesses need their systems to speak the same language,鈥� said Kevin Ichhpurani, President, Global Partner Ecosystem at Google Cloud. 鈥淏y uniting 麻豆原创鈥檚 enterprise data and customer engagement platform with Google Cloud鈥檚 AI, we鈥檙e enabling marketers to move beyond simple automation to multi-agent orchestration, driving dynamic campaigns that reason and adapt to market shifts in real time.鈥�

According to from 麻豆原创 Engagement Cloud, more than half of marketers say fragmented, outdated data prevents them from acting in the moment. 麻豆原创 and Google Cloud are helping remove that roadblock by unifying data and letting AI agents turn insights into action. Using Joule with 麻豆原创 Engagement Cloud, campaigns can move from planning to activation automatically without manual stitching across tools.

Customers will benefit from autonomous campaign generation, optimization and continuous improved performance. Businesses will achieve faster speed-to-market, lower operational overhead and always-on optimization that drives higher ROI, while giving teams more time to focus on strategy and end-to-end campaign execution.

While marketing is the first example, and will be available to customers in H2 2026, this multi-agent orchestration model is designed to support high-value use cases across the 麻豆原创 CX portfolio, laying the foundation for AI-driven customer experience, powered by trusted, unified real-time data and interoperable agents.

For more information about 麻豆原创 Customer Experience solutions, visit .

For more information about Gemini Enterprise, visit .

Visit the . Get 麻豆原创 news via  and .

About Google Cloud

Google Cloud offers a powerful, optimized AI stack 鈥� including AI infrastructure, leading models like Gemini, data management capabilities, multicloud security solutions, developer tools and platform, as well as agents and applications 鈥� that enables organizations to transform their business for the Agentic Era. Customers in more than 200 countries and territories turn to Google Cloud as their trusted technology partner.

About 麻豆原创

As鈥痑 global leader in enterprise applications and business AI, 麻豆原创 (NYSE:麻豆原创)鈥痵tands at the鈥痭exus鈥痮f business and technology. For over 50 years, organizations have trusted 麻豆原创鈥痶o bring out their best by uniting business-critical鈥痮perations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.

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The problem is not the promise of AI. It鈥檚 the gap between intelligence in the system and connection in the moment. Customers are increasingly disengaging because intelligence is not being applied where it matters most.

Technology, particularly AI, has fundamentally changed what customers expect. They assume brands can recognize them across channels, understand context in real time, and anticipate their needs. When that doesn鈥檛 happen, the miss feels less like oversight and more like indifference. Timing is off. Service lacks continuity, and personalization stops at the surface, despite all the data behind it.

While many enterprises are trapped in siloed systems and disconnected data, consumer expectations are growing. Brands that don鈥檛 deliver the expected experiences are quickly abandoned.

In addition, global socioeconomic factors are increasing rapidly and unpredictably, challenging bottom lines and making customer loyalty more critical than ever鈥攁t a time when consumers are less loyal than ever.听

When economies falter, companies usually take one of two approaches. Some hunker down, cut costs and staff, and hope to survive. Others zero-in on differentiators like to drive growth and boost profitability.

The importance of CX for key metrics like churn, retention, loyalty, new sales, and competitive differentiation is well-established, so not investing in customer experience could be considered akin to saying you are willing to let those mission-critical metrics falter.

The following 15 takeouts from 麻豆原创’s highlight some of the most common CX pitfalls and opportunities.

1. 82% of consumers say a brand has disappointed them

Modern customers do not go quietly into the bad experience night. A whopping 82% of consumers say a brand has disappointed them, even when the product itself meets their needs. The issue isn鈥檛 the product or service; it鈥檚 the experience of purchasing and post-purchase care.

This is the essence of the 鈥溾��: the distance between what customers expect in the moments that matter, and what brands are actually delivering.

2. 60% do not pay attention to brands anymore and 48% care more about experience

Consumer attention in a difficult economy has shifted from logos and taglines to experiences that feel useful, contextual, and personal. So, what鈥檚 a brand to do when 60% of consumers say they simply don鈥檛 pay attention to brands and 48% care more about the experience than the product?

This is where CX outcomes become clear: engagement is no longer about shouting louder; it鈥檚 about showing up better and building experiences powered by unified data and intelligent orchestration.

3. Left unread: only 16% of customers skim email headlines, while 29% read one or two sentences

Consumer behavior in the inbox shows just how fragile engagement is:

• Most consumers only read the subject line
• Others will read one to two sentences before deciding whether to delete or engage further

Combined with the fact that 58% of consumers think most marketing emails they receive aren鈥檛 relevant, brands are staring down a massive relevancy problem. Sending more emails into the engagement abyss doesn鈥檛 solve this problem, but gaining a holistic understanding of your customers as individuals does.

4. 37% do not think brands personalize to their needs

For well over a decade we鈥檝e been talking about the importance of personalization, but today 37% of consumers believe brands don鈥檛 personalize engagements to their needs. Surface-level personalization鈥攏ames in subject lines, basic segmentation鈥攊s no longer enough.

This aligns with our assessment that 79% of companies have low or moderate CEM scores, meaning teams can access portions of shared data and deliver basic personalization, but coordination across marketing, sales, service, commerce, and product teams remains limited. Experiences often feel disconnected, forcing brands to rely on short-term tactics rather than building deeper relationships.

Consumers expect real-time, behavior-driven personalization based on context, intent, and history, not just boiler-plate persona buckets. Customers can see and feel investments in personalization and it matters.

5. 46% say customer service feels too impersonal, while 41% believe brands do not understand them as a person

Considering how much data brands collect, it鈥檚 striking that nearly half of consumers (46%) say customer service feels too impersonal.

Customers are asking a simple, and valid, question: 鈥淚f you have all this information about me, why isn鈥檛 my experience better?鈥� When data doesn鈥檛 translate into empathy and action, it starts to feel like surveillance, not service.

With 46% of consumers saying service isn鈥檛 personal, it should be no surprise that a nearly equal amount (41%) believe that brands don鈥檛 understand them as a person. However, 34% agree that AI can help brands better understand them and what matters most to them.

This presents brands with a real-time opportunity: use AI and data to close the perception gap. Instead of just predicting purchases, enterprises should also be anticipating customer needs and reducing friction.

6. 78% of brands say they deliver seamless cross-channel engagement, consumers disagree

Seventy-eight percent of brands say their engagement strategies offer seamless multichannel experiences with glowing outcomes like increased CLV, retention, and advocacy, but consumers are simultaneously reporting little emotional connection and frequent disappointment. In fact, 44% say that brand interactions feel less personal and more generic than ever before.

The takeaway: internal dashboards can create a if not tied directly to real customer sentiment and behavioral signals across channels.

7. 54% of enterprises cannot access and use real-time data, and 66% still rely on third-party data

Fifty-four percent of enterprises can鈥檛 access and use real-time data. On top of that, 60% suffer from 鈥渄ark data,鈥� which is information that鈥檚 collected but not used throughout the customer journey.

Without real-time, connected data, brands are mostly flying blind. AI, personalization, and omnichannel orchestration don鈥檛 fail because the ideas or execution are wrong; they fail because the foundations are.

Although privacy regulations and legislation are increasing while third-party cookies decline, a majority (66%) of enterprises are still heavily reliant on third-party data. Simultaneously, 55% say their data is too unstructured to use effectively.

The lethal combination of overreliance on external data plus underutilized internal data keeps brands from building strong, first-party relationships rooted in trust and value.

8. 78% of brands say AI is essential for customer retention in 2026

AI is everywhere, and 78% of brands view AI as critical to retaining customers in 2026. However, 66% report they can鈥檛 use AI to optimize campaign performance in practice, while many also note they can鈥檛 utilize real鈥憈ime AI optimization in day鈥憈o鈥慸ay campaigns.

A quick translation of the above stats: an AI strategy is crucial, but execution is lagging because of fragmented systems, poor data quality, and integration issues.

9. Only 30% share engagement data with a CX or CRM platform

Despite the collective agreement that a comprehensive customer profile is important, only 30% of brands share their customer engagement data within a CX or CRM platform. This means that most brands are attempting to deliver personalized experiences without having a unified engagement core.

If engagement data lives in campaign tools, service systems, commerce platforms, and ERP, but never gets connected via CX or CRM, customers will feel every fracture along their journey.

10. 30% of consumers have used AI agents that act on their behalf

AI is not just an enterprise capability; it鈥檚 also a customer behavior. Thirty percent of consumers say they鈥檝e used AI agents to make decisions and act on their behalf when buying from brands.

This is a game-changer when it comes to engagement. Brands are now engaging not only with humans, but also with AI buyers that ruthlessly and continuously optimize for relevance and value. If your systems can鈥檛 keep pace, AI will select your competitor whose systems are operationalized for success.

11. When it comes to customer engagement maturity, 79% of brands have yet to integrate data, systems, and teams across their business; only two in five decision-makers see their departments as actually coordinated

The Customer Engagement Maturity (CEM) scoring model assesses how well brands align people, processes, and technology to deliver cohesive, intelligent experiences. Looking at the 麻豆原创 Engagement Maturity Index:

• 16% of brands reside at low maturity
• 63% sit in the moderate middle
• 21% have high maturity

Despite year-over-year progress, most organizations are stuck in developing or evolving mode, able to execute campaigns but not orchestrate truly connected, enterprise-wide engagement. And leaders agree, with only two in five decision makers believing there is effective collaboration across departments.

12. Just 21% of brands are high-maturity, and they are gaining ground against their competition

High-maturity brands rise above the competition because they connect data and intelligence across marketing, service, sales, commerce, and operations. They use AI and automation to deliver personalized, omnichannel engagement in real-time, at scale.

And the maturity gap is becoming a performance gap. As top performers turn real-time intelligence into growth, the cost of competing with them rises for everyone else.

13. Personalized means personal: 58% of consumers respond positively to localized content

Personalization is more than a word or industry term. It means actually understanding and empathizing with your customer, including their regional traditions and social norms.

When engagement is done right, consumers respond:

• 63% say their favorite brand delivers seamless, connected experiences across mobile, web, and in-store
• 58% value localized content and product recommendations
• 55% appreciate highly personalized content
• 50% believe their favorite brand uses data to make interactions better

Customers aren鈥檛 against data or AI at heart. However, they are opposed to wasted data collection and bad experiences. It鈥檚 the job of brands to provide a great CX. If that job isn鈥檛 taken seriously, you can bet that other brands are willing to roll up their sleeves to fill the gap.

14. 77% of businesses plan to invest in AI-powered engagement in 2026

When it comes to the future state, 77% of businesses plan to invest in AI-powered customer engagement in 2026, and 76% are investing in omnichannel engagement technologies. At the same time, 29% say their top priority is connecting customer and stakeholder data across marketing, sales, service, commerce, and ERP systems.

The signal is clear: investment alone won鈥檛 close the Engagement Divide. The winners will be the brands that invest in connection鈥攐f data, teams, and systems鈥攏ot just in tools.

15. 15% say seamless integration will be the biggest driver of success

Lastly, and possibly most importantly, 15% of businesses believe seamless integration of engagement systems will be the single biggest driver of success. While that may sound like a small number, it captures a critical strategic shift: engagement is no longer a marketing problem or a channel problem. It鈥檚 an enterprise discipline that depends on unified data, coordinated teams, and embedded AI.

Artificial intelligence provides an evolving service for businesses. Employing cloud-based systems that can store, analyze, and route data will be the differentiator for brands in the marketplace.

Loyalty is transactional, and driven by great CX and a connected enterprise

Digital engagement has raised the bar when it comes to customer expectations, with more demands and a plethora of competitive choices if a brand doesn鈥檛 deliver.

It鈥檚 not a big leap to state that better customer experiences increase customer loyalty, which in turn leads to more purchases, augmented product utilization, and increased brand affinity and sentiment. And let鈥檚 not forget that an enhanced CLV lowers customer acquisition costs.

After all, loyalty is transactional and forged by the experiences customers encounter. In my conversations with customers across the globe, it鈥檚 clear that only the brands with truly at the heart of their operations will retain and grow their customer bases in the enterprises of the future.

That ambition relies on a technology foundation that can consistently deliver those experiences at scale. For British-founded luxury fragrance brand Molton Brown, moving from legacy systems to 麻豆原创 Commerce Cloud provided a high鈥憄erformance platform built for peak鈥憇eason resilience and continuous innovation. The impact was immediate: 100% uptime during peak trading, even as volumes surged to one order every three seconds during major events.

This kind of reliability is increasingly critical as the moments that shape experience and loyalty expand beyond owned channels. As product discovery shifts to social platforms and AI鈥憄owered assistants, consistent content and availability help the brand remain visible and trusted wherever customers engage. 麻豆原创鈥檚 evolving agentic commerce innovations are designed for this reality, keeping products discoverable, credible, and actionable across both human and AI interactions.

Ultimately, technology and AI are not the goal鈥攖he experience is. The brands that succeed will be the ones that use AI to show up more human, not less, turning insight into relevance and automation into trust.

The future of CX is for companies that operationalize intelligence across the enterprise鈥攃onnecting data, systems, and teams so AI can orchestrate experiences, not just analyze them.

Manos Raptopoulos is global president of Customer Success Europe, APAC, Middle East & Africa, and a member of the Extended Board 麻豆原创 SE.

AI alone is no longer a differentiator: What matters is where intelligence鈥痮perates鈥痠nside of a business. As demand volatility increases, fulfillment windows tighten, and customer expectations鈥痳ise,鈥痮rganizations need more than insights or task鈥痑ssistance. They need intelligence inside quotes, product content, service interactions, and campaigns, guiding decisions as they happen and continuously adapting as conditions change.

This shift lays the foundation for a new generation of executional AI, where capabilities evolve from supporting users to actively鈥痬onitoring鈥痜lows,鈥痑nticipating鈥痳isk, and over time acting as intelligent agents within core customer-facing processes.

With the Q1 2026 release of鈥� solutions, 麻豆原创 advances this shift by bringing AI closer to day-to-day customer-facing execution across sales, service, commerce, and engagement. Intelligence now operates closer to where outcomes are realized鈥攈elping organizations protect revenue, reduce friction, and deliver consistent, trusted experiences at scale.

Below, explore more of the highlights from the Q1 2026 release. And for full sub-solution details, see recaps for听,听,听,听, and听.

Optimize revenue streams with confidence

Revenue becomes more reliable when customer intent is captured early and executed consistently across sales and commerce workflows. The execution depends on speed and accuracy: accurate product information, relevant content, and seamless handoffs from inquiry to quote creation. When these are disconnected, teams face delays, manual rework, and missed revenue opportunities.

From customer inquiry to executable quote

• Email to quote with AI:鈥疉utomatically add SKUs from a deal using opportunity and email data with the Microsoft Outlook add-in for 麻豆原创 Sales Cloud. Users can choose to generate a quote, and the quote is quickly created in 麻豆原创 Sales Cloud in just a few clicks. After review, sellers can hit send; it is that easy.  
• Deep research: Accelerate account planning and reviews by synthesizing 麻豆原创 Sales Cloud and 麻豆原创 Service Cloud data with external market intelligence. For example, the deep research capability can deliver a detailed brief that can be used to better understand the account, their industry, and other crucial information like news and SWOT. Sellers will be able to engage prospects and buyers more effectively while customers will have more relevant and personalized information delivered.  
• Media attachments for product descriptions: Use AI to extract details from product documents, such as manuals, spec sheets, and PDFs, and automatically generate or enrich product descriptions in 麻豆原创 Commerce Cloud. This accelerates catalog updates and improves product data quality so that shoppers, search engines, and agentic commerce are rich with the most accurate product descriptions鈥攅nsuring product descriptions are detailed, differentiated, and discovered.

Delivering鈥痳别濒颈补产濒别鈥痵ervice at鈥痵肠补濒别

• Digital Service Agent handoff鈥痜or case creation: Connect every step of the service journey from conversational AI self-service to field resolution so service teams can resolve customer issues鈥痜aster and provide personalized service engagements that build trust.鈥疷sing conversational cues, Digital Service Agent鈥痵ummarizes intent identification for ticket creation while capturing essential information required for handoff to underlying solutions like 麻豆原创 Service Cloud.
• : Give service teams a single, real-time command center in 麻豆原创 Service Cloud, consolidating cases, tasks, and service orders into one view with visual workload insights so agents can prioritize faster, stay on top of commitments, and resolve more issues per day. 
• Retail Intelligence (麻豆原创 Early Adopter Care): Announced at NRF, Retail Intelligence provides one closed-loop, AI-enhanced retail supply chain planning environment that ties together planning, execution, and engagement. The result: human and agentic teams that don鈥檛 just execute tasks but reshape strategies, reimagine retail supply chain planning, and master autonomous growth and lasting differentiation.
  Learn more at the session.

Orchestrating engagement across the customer life cycle

Customer engagement spans browsing,鈥痯urchasing, fulfillment, and service across multiple channels. 麻豆原创 CX connects engagement directly to operational context.鈥�&苍产蝉辫;

• delivers鈥痯ersonalized, AI-personalized communications and interactions across every channel powered by connected customer and operational data all fully integrated across 麻豆原创. Teams鈥痗an鈥痙eliver consistent, intelligent engagement that builds loyalty and drives鈥痓usiness鈥痠mpact.

• :鈥疎xtend conversational analytics to SMS campaigns. A new data context model narrows analysis to the right dataset, returning faster, more precise answers to natural language questions, such as 鈥淲hat was SMS revenue last month?鈥�

• :鈥疨redictively鈥痠dentify鈥痗ontacts鈥痺ho are鈥痩ikely in the next鈥�30 days to engage,鈥痓ecome inactive, or remain inactive,鈥痵o marketers can target outreach鈥痺here it will deliver the strongest results.鈥��&苍产蝉辫;

Accelerate transformation鈥痺颈迟丑鈥痶丑别鈥痑dvanced success plan鈥痜or 麻豆原创 CX

To鈥痑ssist鈥痗ustomers鈥痮n their鈥痶ransformation鈥痡ourneys, 麻豆原创 launched the new Advanced Success Plan in the鈥�. This will鈥痟elp customers increase the value of individual applications, accelerate cloud transformation across 麻豆原创 Business Suite,鈥痑nd enable consistent adoption of new innovations and 麻豆原创 Business AI.

With expanded coverage with additional 麻豆原创 CX solutions, including and , the advanced offering is comprised of three powerful elements:

• Success expert: Regular 麻豆原创 expertise driving strategic customer outcomes
• Adoption guidance: Structured, AI-driven enablement accelerating adoption
• Activation and optimization services: Hands-on services to maximize performance and impact

Check out the鈥痺ebinar鈥痶o learn how the new service offering unlocks more of the transformative value of 麻豆原创 solutions:鈥�.

Intelligence where execution happens鈥�&苍产蝉辫;

With 麻豆原创 Customer Experience, AI moves beyond isolated鈥痑ssistance鈥痶o鈥痮perate鈥痙irectly within business execution flows. Intelligence is embedded where work happens鈥攊nside quotes, product content, service interactions, and campaigns鈥攈elping organizations respond in real time and deliver consistent customer outcomes at scale.

Learn more about 麻豆原创 CX in Q1鈥�2026鈥�&苍产蝉辫;

Read the 麻豆原创 Help documentation to get started with these new capabilities.鈥�&苍产蝉辫;

Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience and Consumer Industries.鈥�

These critical pre-purchase moments generate interest and open pathways toward deeper customer relationships. Organizations that convert interest into measurable outcomes with clarity, accuracy, and speed strengthen the overall customer experience, thereby boosting loyalty and bottom lines.

CX becomes even more meaningful as opportunities progress into clear agreements supported by accurate configuration, pricing, and quoting. This transition from opportunity to agreement represents one of the most consequential stages in the customer journey.

Lead-to-cash represents a coordinated motion across sales engagement, pricing precision, service alignment, and performance visibility. When these capabilities operate together, organizations deliver consistent customer experiences while maintaining operational clarity.

Eight years running: a leadership signal at the heart of lead-to-cash

Within the lead-to-cash journey, quoting connects sales engagement, performance management, service continuity, and ERP alignment. It represents a critical moment where customer intent is translated into accurate pricing, configuration, and agreement terms.

When 麻豆原创 CPQ operates within 麻豆原创 Customer Experience, it becomes part of a connected lead-to-cash motion that spans 麻豆原创 Sales Cloud, 麻豆原创 Service Cloud, sales performance management solutions, and 麻豆原创 ERP. Sales teams engage with structured opportunity data and guided pricing logic. Service teams inherit full visibility into agreed terms. Performance leaders access insights grounded in accurate pipeline and quoting data.

When it comes to this level of intelligent, real-time, connected processes, very few companies can compete. 麻豆原创 was again recognized as a Leader in the 2025 Gartner庐 Magic Quadrant™ for Configure, Price, and Quote Application Suites. This marks the eighth consecutive year 麻豆原创 has been positioned in the Leaders quadrant based on Ability to Execute and Completeness of Vision.

麻豆原创 CPQ supports organizations in producing accurate quotes — even in environments with advanced configuration and pricing requirements — helping accelerate sales cycles and improve sales execution across complex selling environments.

Extending CPQ leadership across 麻豆原创 Customer Experience

In modern enterprises, quoting connects directly to demand generation, pipeline management, contract processes, fulfilment, and service delivery. brings together commerce, customer data, marketing, sales, service, and sales performance management into an integrated portfolio designed to support truly connected customer journeys.

Within this portfolio, 麻豆原创 CPQ plays a pivotal role in the lead-to-cash journey. When integrated with 麻豆原创 CX solutions, it helps align pricing strategy, product configuration, customer agreements, and sales performance insights across the revenue lifecycle. The result is a more reliable transition from opportunity to revenue realization.

Connected lead-to-cash experience

For CX leaders, lead-to-cash is a core driver of experience differentiation and revenue execution. A connected lead-to-cash strategy ensures that:

• Customer intent is translated into accurate configuration and pricing.
• Sales engagements reflect approved pricing and product standards.
• Customer agreements are consistently captured and supported across systems.
• Sales performance and revenue outcomes remain visible and aligned across teams.

Business impact of connected lead-to-cash

Lead-to-cash determines how consistently organizations translate customer engagement into measurable outcomes.

By combining 麻豆原创 Customer Experience capabilities with a CPQ solution recognized for its ability to execute and completeness of vision, organizations strengthen alignment across sales, pricing, service, performance management, and ERP systems, transforming engagement into measurable outcomes with confidence and precision.

In today鈥檚 environment, customer experience and operational precision are closely connected. Strength in one reinforces performance across the other.

You can learn more about how 麻豆原创 CX connects 麻豆原创 Sales Cloud, 麻豆原创 CPQ, 麻豆原创 Service Cloud, sales performance management solutions, and 麻豆原创 ERP across the lead-to-cash journey .

Sindy Conway is senior Product Marketing consultant for 麻豆原创 Customer Experience.

In today鈥檚 omnichannel reality, delivering that elevated experience consistently and at scale is essential to protecting brand trust and loyalty. Peak moments like Black Friday and Cyber Monday amplify the challenge, when traffic surges and expectations for fast, personalized service are at their highest.

The team recognized that legacy systems couldn鈥檛 provide the speed, stability, or connected view required to meet those expectations at scale, prompting a shift to a modern customer experience (CX) foundation with 麻豆原创.

Modernizing the digital core with 麻豆原创 Commerce Cloud

Moving from legacy technology to gave Molton Brown a high鈥憄erformance engine designed for peak鈥憇eason reliability and continuous innovation. The results came quickly: 100% uptime during peak trade, even as volumes spiked to one order every three seconds during major events, freeing teams to focus on enhancing the customer experience rather than firefighting, and ensuring uninterrupted service for customers across global markets.

鈥淧eak performance isn鈥檛 a one鈥憈ime effort; it鈥檚 about reliability. We have to rely on technology operations to achieve 100% efficiency so the business can succeed, which in turn helps our customers succeed. Technology should enable business success, not block it鈥攁nd 麻豆原创 has proved that multiple times.鈥�

Naresh Krishnamurthy, Senior Manager 鈥� Business Transformation, Prestige, Kao UK Ltd

That stability also matters as product discovery increasingly begins beyond owned channels鈥攆rom social platforms to emerging AI鈥憄owered assistants鈥攚here consistent, trustworthy content and availability help the brand stay visible and credible wherever customers choose to engage. 麻豆原创鈥檚 evolving agentic commerce innovations anticipate this shift, ensuring products remain discoverable, trusted, and actionable across both human and AI agents.

A seamless luxury journey across channels

With and (formerly 麻豆原创 Emarsys) working together, Molton Brown aligns what customers see online with what they experience in store. Product categories, storytelling, and navigation are mirrored across channels; store associates can act on online browsing signals; and store teams are enabled with real鈥憈ime insight to deliver high鈥憈ouch clienteling experiences.

The result is an unbroken, premium journey that reduces friction and reinforces trust in the brand鈥攅xactly what luxury shoppers expect.

Personalization that builds loyalty, not just transactions

麻豆原创 Engagement Cloud helps Molton Brown deliver channel鈥慳ppropriate experiences, from mobile鈥慺irst engagement to email and in鈥憇tore clienteling, aligned to evolving customer preferences. These programs are complemented by thoughtful gifting moments, personalized birthday acknowledgments, and sustainability鈥慺ocused communications that strengthen repeat鈥憄urchase behavior.

Crucially, the team treats every holiday period as a data鈥憆ich learning cycle: months of performance testing, UX refinements, and campaign iteration inform what customers experience in the following season. Those insights help the team refine the experience so it remains consistent, intuitive, and premium, even under peak pressure. That consistency is what sustains loyalty, not just the promotions themselves.

As Naresh Krishnamurthy explains: 鈥淏lack Friday is not just about revenue; it鈥檚 about brand engagement and building the strong foundation that enhances the relationship through loyalty.鈥�

Ready for the next era of intelligent commerce

With a dependable CX core in place, Molton Brown is now exploring to anticipate risks ahead of campaigns, sharpen decision鈥憁aking, and streamline fulfillment鈥攁ugmenting the experience behind the scenes without compromising luxury standards.

This direction aligns naturally with 麻豆原创鈥檚 broader agentic commerce vision, where AI systems help interpret intent and keep trusted products discoverable and transactable across new surfaces鈥攁nother reason a reliable, 鈥渕achine鈥憆eadable鈥� CX foundation matters.

“Everything we鈥檙e doing ladders up to one goal: a truly connected customer experience鈥攑ersonal, consistent, and effortless in every channel.”

Molton Brown鈥檚 partnership with 麻豆原创 CX has reset what鈥檚 possible at peak, and every day after: dependable operations, consistent omnichannel experiences, and personalization that earns loyalty. The brand now scales confidently during its biggest moments, and stays ready for what鈥檚 next as AI changes how people (and agents) discover and buy.

This transformation positions Molton Brown to adapt quickly as customer expectations and digital commerce behaviors continue to evolve.

To explore how 麻豆原创 Commerce Cloud can elevate your customer experience, visit .

Our vision for agentic commerce is bold. In , we showcase a future where humans and AI agents collaborate to drive intelligent recommendations, proactive operations, efficient business processes, and deeper customer relationships. While this vision points forward, 麻豆原创鈥檚 focus is firmly grounded in helping retailers take practical steps today. This isn鈥檛 about flashy demos of a distant future鈥攊t鈥檚 about building the foundation now for how consumers will buy and retailers will sell in the years ahead.

Unlike traditional AI systems that respond to prompts, agentic systems act on intent. They learn from preferences, make proactive recommendations, and can complete transactions on a shopper鈥檚 behalf. These agents are increasingly becoming the starting point of the buying journey, reshaping how brands compete for visibility, trust, and loyalty.

This evolution introduces both opportunity and risk. As AI agents mediate more interactions between brands and consumers, retailers must rethink how they capture intent, transact with agents, and deliver post-purchase experiences that reinforce trust.

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Discovery is moving from search to assistants

Historically, product discovery revolved around search engines, marketplaces, and brand-owned storefronts. That model is shifting quickly. Answer engines and AI shopping agents are becoming new entry points for commerce鈥攐ften before a shopper ever visits a retailer鈥檚 site.

Like marketplaces before them, AI agents introduce a new layer between brands and customers. The difference is speed and autonomy. Agents don鈥檛 just surface options; they reason, decide, and act.

For retailers, success is no longer about ranking on a page. It鈥檚 about ensuring products are visible, understandable, and trusted by machines that influence purchase decisions on behalf of humans.

At NRF, 麻豆原创 expanded its agentic commerce vision with the announcement of the storefront MCP server for 麻豆原创 Commerce Cloud, planned for Q2 availability. The storefront model context protocol (MCP) server can enable channel-less commerce by allowing businesses to safely and reliably engage with multiple AI agents鈥攚hether embedded in a retailer鈥檚 own experiences or originating from third-party assistants like ChatGPT or Perplexity.

The storefront MCP server helps merchants surface products and can enable buying across channels for both people and machines. It鈥檚 the first of many steps 麻豆原创 is taking to help customers fully participate in agentic commerce by supporting MCP, ACP, UCP, and other emerging agentic protocols.

Product content becomes the currency of visibility

In an agent-driven world, product content is no longer just marketing鈥攊t鈥檚 operational infrastructure. AI agents cannot recommend what they cannot interpret. Every attribute, image, specification, availability signal, and proof point directly impacts whether a product is surfaced, compared, or selected.

This is where generative engine optimization (GEO) is evolving. Optimization must now serve two audiences: humans and machines. Product data must be structured, consistent, and enriched, so AI agents can confidently represent it to shoppers.

The in helps transform how merchants manage product data at scale. It can clean catalogs, enrich attributes, standardize details, fill gaps, and support multilingual content using real-time data. The agent can scale to catalogs with more than 10 million items, helping teams improve content 70% faster, increase data completeness by 5%, and reduce maintenance effort by 63%.

With AI-ready product data as its foundation, retailers can better match shopper intent, optimize merchandising by channel, and improve pricing and delivery decisions with precision.

Payments must evolve for autonomous commerce

As buying journeys fragment across devices, channels, and agents, payments must become more flexible and nearly invisible. Consumers expect to pay how and when they choose, including through agent-initiated transactions.

New payment rails like FedNow, RTP, and stablecoins are enabling faster, lower-cost transactions, while wallets and bank-based payments continue to converge. Networks such as Visa and Mastercard are already preparing for autonomous commerce by allowing consumers to set spending limits and controls for AI agents.

For retailers, the priority is delivering frictionless, secure payment experiences that integrate seamlessly into agent workflows.

The can enable this flexibility through a no-code, low-code approach. Its headless, extensible architecture helps support diverse payment methods, ensure compliance through automatic updates, and integrate natively with 麻豆原创 Commerce Cloud鈥攚orking to give retailers agility without sacrificing control or scalability.

Returns become a strategic intelligence engine

Returns are one of retail鈥檚 biggest challenges. According to IHL Group, global returns have surpassed US$1.9 trillion and are growing faster than sales. What was once a cost center is now a strategic differentiator.

The next phase of returns management is defined by intelligence. AI enables 鈥渒eep, reject, or return鈥� decisioning based on loyalty history, behavioral signals, margin impact, and lifetime value. Returns data becomes a feedback loop that improves forecasting, product quality, and merchandising decisions.

Complete, connected data is essential. 麻豆原创 can deliver this through native integration between 麻豆原创 ERP and 麻豆原创 Commerce Cloud, creating a single source of truth across inventory, costs, and transactions. found that organizations using both platforms achieved up to 80% lower TCO, up to 90% productivity gains, and 105%鈥�245% revenue uplift from hyper-personalized experiences.

can extend this foundation across the full returns journey, helping to orchestrate centralized rules, guided returns, real-time inventory visibility, and faster refunds鈥攖urning returns into a loyalty-building growth lever rather than a revenue drain.

Commerce is detaching from the storefront

As predicted at the end of 2025, AI agents are taking on more shopping tasks, pushing commerce beyond traditional storefronts. A shopper may simply state an intent and let an agent handle research, selection, and checkout.

Discoverability now depends on structured, trustworthy signals鈥攔eviews, ratings, social proof, and consistent data that agents rely on to evaluate quality and brand credibility.

Retailers must move beyond transactional efficiency to deliver connected, personalized experiences across every touchpoint. Loyalty programs must reward engagement, not just purchases. Inventory visibility, accurate delivery promises, and proactive issue resolution become table stakes.

can enable retailers to design adaptive loyalty strategies for this new environment, personalizing rewards and offers based on real-time behavior鈥攚hether purchases happen through traditional channels or AI agents. These insights can then feed transactional agents, helping to improve relevance and outcomes across the journey.

Operational reliability remains critical. 麻豆原创 Order Management Services help unify order, inventory, fulfillment, and POS data, while agentic innovations like the Order Reliability Agent can proactively resolve fulfillment issues before they impact customers.

Trust is the core retail responsibility

As agentic systems influence more of commerce, trust becomes the most valuable asset retailers can protect. Consumers must trust that their data, preferences, and payments are secure and governed responsibly.

Retailers and commerce providers increasingly act as AI trust custodians, balancing intelligence with deterministic constraints and governance. On-site AI can scale associate expertise and personalization while preserving brand integrity and customer confidence.

Commerce is becoming an ecosystem of intelligent interactions鈥攚here discovery, payments, fulfillment, and returns are connected by agents acting on behalf of shoppers and businesses alike.

The winners will be those who align product intelligence, flexible payments, data-driven returns, and trust across every touchpoint. Agentic AI can make commerce more personal, efficient, and scalable鈥攂ut only for those who build the right foundations today.

To learn more about how 麻豆原创 Commerce Cloud is powering AI-driven commerce, visit .

Kollen Glynn is global head of 麻豆原创 Commerce Cloud for 麻豆原创 Customer Experience.

This isn鈥檛 just a consumer trend; it is reshaping engagement models across industries.

The Q4 2025 (麻豆原创 CX) release propels this transformation further with new out-of-the-box agents designed for customer service and the ability to easily build custom agents with Joule Studio. Additionally, AI features like predictive segmentation and AI-assisted reporting expedite planning and decision-making鈥攆oundational catalysts for future-ready businesses.

With WalkMe Premium now available across 麻豆原创 CX applications, teams can upskill and reskill with in-the-moment guidance. And 麻豆原创 Customer Loyalty Management takes new engagement models to the next level, helping businesses strengthen relationships and drive long-term growth.

Here, explore more of the highlights from the Q4 2025 release. And for full sub-solution details, see recaps for , , , , and .

Better customer engagement with out-of-the box agents and custom tools

With 麻豆原创, customer experience applications, data and AI come together as one鈥攑owered by 麻豆原创 Business Technology Platform. Whether it鈥檚 resolving an issue or managing inventory, CX applications connected to 麻豆原创 ERP keep processes running smoothly. AI agents take it further, by reasoning and acting directly in core processes, turning complexity into clarity. One of the most critical areas is in customer support.

• : Deliver instant and accurate self-service by putting knowledge at customers鈥� fingertips. Deflect common inquiries, resolve complex questions with AI, and escalate seamlessly to human agents when needed鈥攔educing contact center load while improving customer satisfaction.
  
  Digital Service Agent can be combined with , creating one conversational AI that handles the entire journey鈥攆rom product discovery and transaction to post-sales support. Customers can ask questions, get answers, and complete purchases in a single frictionless interaction. Together these agents unlock agentic commerce and intelligent service, which strengthens customer relationships and deliver experiences that truly stand out.

• : Create custom, business-ready AI agents for 麻豆原创 Customer Experience Cloud applications鈥攆ast and without complexity. Joule Studio, a part of , gives developers a powerful low-code, no-code environment to create and deploy AI agents and connect them seamlessly to Joule, 麻豆原创 CX apps and third-party systems. These agents can retrieve information, complete tasks, and run autonomous actions grounded in enterprise data from 麻豆原创 CX, 麻豆原创 Knowledge Graph, and non-麻豆原创 systems.
  
  For example, users can build a sales assistant agent that instantly pulls historical purchase records, analyzes buying patterns, and recommends the most relevant products or offers鈥攈elping sales teams increase conversion rates and shorten sales cycles. Learn how to .

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Boost insights and workforce skilling with AI-powered guidance

AI is no longer optional; it鈥檚 the engine behind smarter, faster customer engagement. As digital experiences raise the bar, customers expect speed, personalization, and simplicity in every interaction. Meeting those expectations requires more than automation. It demands AI-driven insights and skills that scale across the organization.

• : 麻豆原创 is embedding AI upskilling into the core of customer experience applications with WalkMe Premium for 麻豆原创 CX solutions. This solution empowers employees to work smarter and learn faster, driving better outcomes from day one. With real-time, role-based guidance and automation across , , , and , teams can unlock the full potential for 麻豆原创 CX solutions without complexity.

• : Easily generate custom reports and comparisons in 麻豆原创 Emarsys, and uncover campaign and customer insights instantly.

• : Enable service agents in 麻豆原创 Service Cloud to quickly understand key consumption trends for a premise. With AI-generated summaries of consumption graphs, agents can immediately identify usage fluctuations, anomalies, and important patterns to support faster resolution for utilities customers.
• : Check the overall health of the sales pipeline in 麻豆原创 Sales Cloud and display opportunities based on quantity and probability score.
• Promotion and account plan configuration: In , customers can configure promotion types and account plan types, defining scope, levels, spend, and baseline management, in order to enable flexible planning and support future indirect promotions.

• Engagement events: In 麻豆原创 Emarsys, ingest inbound events from external data sources to further enhance segmentation and personalization throughout the journey.
• (pilot): Use predictive AI segments in 麻豆原创 Emarsys to reach audiences that are most likely to engage based on a contact鈥檚 behavior, status, or channel preference.

Build lasting connections with 麻豆原创 Customer Loyalty Management

Customer loyalty is more than a metric; it鈥檚 a long-term strategy for growth. As expectations rise, organizations need solutions that create meaningful, lasting relationships. 麻豆原创 Customer Loyalty Management helps businesses deliver personalized experiences, reward trust, and strengthen engagement at every touchpoint, turning everyday interactions into enduring connections.

• : Empowers businesses with AI-driven insights to capture and unify customer data in a dynamic, cloud-based loyalty profile. These profiles provide deep insights into individual motivations, enabling smarter segmentation and highly targeted marketing campaigns. From managing global programs on a unified platform to forming strategic alliances and scaling initiatives for impact, 麻豆原创 helps transform loyalty into a measurable, powerful engine for sustainable engagement and success. 麻豆原创 Customer Loyalty Management has integrations for 麻豆原创 Service Cloud and 麻豆原创 S/HANA Cloud Private Edition to make the transformation faster.

The future of engagement is here, get ready with 麻豆原创

How we engage is changing faster than ever. 麻豆原创鈥檚 Q4 2025 innovations in customer experience anticipate this shift on every level. 麻豆原创 CX is enabling organizations to move beyond reactive strategies and into a world of proactive, personalized experiences.

Businesses that embrace and integrate these new models throughout their enterprise, pairing agentic AI with human intelligence and creativity, will set new standards for customer loyalty and growth.

Learn more about 麻豆原创 CX in Q4 2025

Read the 麻豆原创 Help documentation to get started with these new capabilities.

• 鈥�&苍产蝉辫;
•   
•   

Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience and Consumer Industries.

NEW YORK 鈥� (NYSE: 麻豆原创) today announced a new generation of AI-enhanced retail innovations at NRF 2026: Retail鈥檚 Big Show.

麻豆原创 continues to infuse AI into the DNA of every part of its retail solutions, reinforcing its suite-first strategy and helping retailers operate with greater intelligence, resilience and trust while delivering better experiences for customers everywhere.

鈥淩etailers face a landscape where AI is no longer optional,鈥� said Balaji Balasubramanian, President and Chief Product Officer for Customer Experience and Consumer Industries, 麻豆原创 SE. 鈥溌槎乖� provides one closed-loop, AI-enhanced retail operating system that ties planning, execution and engagement together. We put data and AI at the heart of retail, delivering speed, personalization and growth across every channel and segment.鈥�

AI that turns retail data into actionable intelligence

The Retail Intelligence solution in provides accurate demand and inventory planning, leveraging retailers’ data from across 麻豆原创 software and third-party systems to drive profitable growth through actionable, real-time insights. Purpose-built for retailers and direct-to-consumer businesses, it will be generally available in the first half of 2026.

Harmonizing real-time data from sales, inventory, customers and suppliers, Retail Intelligence uses AI-generated simulations so planners can anticipate outcomes and optimize inventory. This improves forecast accuracy, reduces manual planning effort, lowers inventory costs and raises service levels. All this drives more seamless omnichannel engagements, which strengthen customer loyalty and enable growth without adding complexity for retailers.

鈥淩etailers are seeking built-in, embedded AI solutions to help balance daily operations, future planning and agility to manage a dynamic market,鈥� said Ananda Chakravarty, Vice President of IDC Retail Insights. 鈥淲hat sets 麻豆原创 apart is the holistic nature of its approach, offering an agentic operating system that works in the background, connects data and orchestrates agents. 麻豆原创 makes it an easy lift for retailers to achieve enterprise-wide intelligence, avoiding the complexity of many point solutions.鈥�

AI that streamlines modern retail operations

Retailers must make fast, confident decisions across assortments, pricing and planning. To meet that need, 麻豆原创 announced new AI-assisted assortment management capabilities, allowing planners to create, modify or retire assortments using natural language through the Joule copilot. This reduces the bottleneck on expert users, enabling faster responses to market shifts and freeing time for higher-value merchandising decisions.

麻豆原创 also introduced omnichannel sales promotions in sales orders, integrating the 麻豆原创 Omnichannel Promotion Pricing solution with the 麻豆原创 S/4HANA Cloud Public Edition, retail, fashion and vertical business solution. This enables advanced promotions such as bonus buys to be applied consistently across diverse channels, enabling a single source of truth for pricing and promotions in store and online, so retailers can deliver a consistent experience.

In addition, 麻豆原创 is delivering deeper merchandising, segmentation and manufacturing support in the solution, tailored to fashion wholesalers and manufacturers. These enhancements provide the data and process foundation needed for AI-assisted fashion operations across the business.

AI that drives better customer engagement

As shopping journeys increasingly begin with AI assistants rather than storefronts or search engines, retailers need new ways to be present wherever buying decisions are made. 麻豆原创 helps retailers connect products, pricing, inventory and promotions directly to AI-enabled discovery and shopping experiences, unlocking agentic commerce with its new storefront MCP server, part of the 麻豆原创 Commerce Cloud solution.

Retailers can now make their storefronts intelligible to AI, driving shopping experiences not only on their storefronts but also on platforms such as ChatGPT.听This creates a truly channel-less commerce experience, one where engagement, discovery and transaction happen more seamlessly across human and AI-assisted touch points.

AI that builds customer loyalty

As customer expectations rise and fulfillment networks grow more complex, retailers need confidence that every order will be delivered as promised, using AI solutions that provide proactive visibility and guidance to help keep operations running smoothly and at scale. And as brand visibility shifts in the age of agentic commerce, reliable and consistent shopping experiences are more important than ever to drive sustained customer loyalty and trust.

麻豆原创 announced Order Reliability Agent as part of the 麻豆原创 Order Management Services bundle, planned for release in the second quarter of 2026. The new agent proactively identifies and resolves potential order issues, helping associates answer common questions about order status, stock availability and fulfillment risks before they impact customers.

By combining agentic autonomy with human oversight where judgment matters, these innovations from 麻豆原创 drive insightful planning and improve operational efficiency, both enhancing the customer experience and driving profitable growth.

Visit the . Get 麻豆原创 news via  and .

Media contact:
Mallory Kuno, +1 (425) 239-9362,听mallory.kuno@sap.com, ET
麻豆原创 麻豆原创 Room; press@sap.com

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ.听 Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
漏 2026 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.

Seismic shifts are not new for retailers鈥攂ack in 1999, e-commerce was still an afterthought. By 2000, everything changed as retailers went all-in on digital.

In听2025,听we are听living in yet听another pivotal year.听This holiday season might feel familiar as you scroll through deals, compare brands, and race to beat shipping deadlines. But beneath the surface, something far more transformative is happening.听The year 2025 will听likely be听the last consumers shop as they do now.听听

Agentic AI is reshaping commerce by making shopping faster, smarter, and effortless. Discovery is moving from people browsing their favorite brands to intelligent orchestration. Instead of opening 10 tabs to hunt for the right deal, shoppers will simply ask: 鈥淔ind me the highest rated black, puffy winter coat, size 10, under $200 that ships in two days.鈥�

The agent will handle the rest鈥攕canning thousands of options, validating reviews, confirming delivery timelines, even factoring in loyalty perks. That future isn鈥檛 tomorrow; it鈥檚 already here, and by next holiday season, most shopping journeys will begin, evolve, or end with AI agents.

While this type of shopping creates convenience for shoppers, it creates a challenge for retailers that have focused on brand campaigns and poured millions of dollars into advertising to be the 鈥渂rand of choice鈥� in the discovery process. Decades of investment into SEO, paid traffic, and brand recognition are losing their edge. While not abandoning these strategies entirely, they must evolve for the AI-first world.

However, there is something that hasn鈥檛 changed over the course of decades: the need to create loyal customers who make repeat purchases and give the greatest share of their wallets. This, too, is more challenging than ever. In fact, 72% of consumers report that this holiday season they will only that consistently meet their needs in the moment.

Creating customer loyalty in the age of agentic commerce means conquering two critical fronts:

• Optimizing for discoverability: Agents will favor retailers that make buying seamless.
• Creating customer loyalty post-purchase: With discovery being augmented by AI agents, humans will now give their ongoing loyalty based on post-purchase experiences. On-time delivery, easy returns, and rewards that feel personal are the new battleground for brand equity.听 And with agents learning from human behavior, exceeding shopper expectations post-purchase can ultimately impact a brand鈥檚 likelihood of being recommended in the discovery phase.

The question remains: how do we move from esoteric AI conversations to practical strategies?

Discovery and loyalty: How to win in the age of agentic AI

• Make your catalog agent-ready: Treat AI as a new kind of shopper. Ensure product feeds are rich, structured, and machine-readable, complete with attributes, use-case-driven descriptions, real-time pricing, and accurate inventory. Clean, structured product data is now the foundation of intelligent discovery.
• Create solutions, not just SKUs: AI-driven traffic behaves differently. Design bundles, add-ons, and value stacks that solve specific problems and allow agents to match shoppers with outcomes, not just product lists.
• Build trustworthy, accessible information: Operationalize trust by surfacing verified reviews, transparent pricing, sustainability details, and clear return policies. Make this data accessible through well-structured APIs, not scraping, so agents and humans see the same reliable truth.
• Let prediction power personalization: Use unified data and AI to predict what customers want before they act, enabling real-time next-best-actions across email, SMS, push, in-app, and other emerging channels. This predictive intelligence turns fragmented campaigns into that deliver higher engagement and revenue.
• Make loyalty the thread that ties every experience together: Loyalty is no longer a program. It鈥檚 a relationship. Use every interaction to tailor meaningful, emotional moments that adapt, remember, and feel consistent across channels in order to help convert agent-driven traffic. Then, use personalized exclusives and perks to foster high-value relationships with those new customers.
• Deliver on your promises, every time: Eighty-eight percent of customers leave a brand after one bad experience. That鈥檚 why operational reliability is the new loyalty. Bring order, inventory, payments, and fulfillment into alignment, so customers receive what they were promised, when they were promised. Loyalty now begins at checkout.
• Prepare for the new return economy: Agent-driven buying makes it easy for consumers to purchase first and decide later. Set clear limits to protect margins and reduce friction in the returns journey because a seamless return can build more loyalty than the purchase itself.

麻豆原创 is already helping brands prepare for this future with AI-enabled technologies across , , , and .

A brand already building for the future

Global sports brand . Historically reliant on seasonal campaigns, Mizuno wanted a more sustainable way to engage its diverse customer base across 10 product categories and multiple channels. Mizuno unified its customer data and used AI to create personalized journeys, turning one-off interactions into long-term relationships.

The results speak for themselves:

• 52% year-over-year (YoY) increase in active customers
• 62% increase in revenue from premium customers
• 35% increase in customer win-backs
• 33% increase in the number of orders

麻豆原创: A partner built for scale, stability, and growth

As customer behavior evolves and AI reshapes what鈥檚 possible, one thing remains constant: 麻豆原创鈥檚 commitment to helping brands win their biggest commercial moments. This year鈥檚 holiday results make that clearer than ever. We鈥檙e not just helping brands plan for peak season鈥攚e鈥檙e helping them execute it with precision, intelligence, and confidence.

Nearly 20% YoY growth in total messages sent underscores the trust brands place in 麻豆原创 Emarsys to deliver at scale. Mobile and emerging channels surged鈥攊n-app (+61%), SMS (+32%), push (+27%), and inbox (+91%) all saw significant YoY gains鈥攁s brands met customers exactly where they were browsing and buying. Omnichannel maturity accelerated with brands using a richer mix of channels to create connected, high-value experiences across every stage of the shopping journey. And with 100% uptime and flawless reliability, teams executed independently and confidently, even during their highest-volume moments.

Paired with exceptional commerce performance, the story becomes even more compelling: brands used more intelligent engagement to guide shoppers toward higher-value purchases (+18% YoY average order value) and ultimately drove substantial YoY revenue growth (+40% gross merchandise value)鈥攁ll powered by a that delivered uninterrupted performance with 100% uptime through the holiday shopping rush, ensuring we鈥檙e here for our customers when it matters most.

This is what partnership looks like: scale, intelligence, reliability, and results so brands can focus on creating exceptional customer experiences, not managing technology.

Looking ahead

The year 2025 will be remembered as the last holiday season where brand mattered more than the overall experience.

This year, and 48% of shoppers would support brands bringing more AI into their buying experience. This sets the stage for growth in 2026 as AI agents deliver relevance, trust, and immediacy, making shopping simpler, smarter, and more satisfying for people everywhere.

The brands that win won鈥檛 be the ones shouting the loudest. They鈥檒l be the ones using 麻豆原创 to be most discoverable, dependable, and unforgettable.

By anticipating needs and creating better, personalized journeys, AI will enhance every stage of commerce. And 麻豆原创 is here to make that future happen.

Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience.

The solution helps businesses worldwide stay ahead of changing customer expectations with a powerful, future-ready platform that delivers unified commerce through connected data, intelligence, and AI innovation.

Organizations across industries use 麻豆原创 Commerce Cloud to unlock sustainable growth through personalized commerce at scale.

麻豆原创 Commerce Cloud is embedding into the tools that employees and customers rely on every day. With AI built into key moments in commerce, the solution and its AI agents help create real business outcomes through faster response times and streamlined touchpoints. Agents like the bring the vision for a connected, intelligent business suite where applications, data, and AI work together in a continuous, virtuous cycle to anticipate needs, act in real time, and elevate experiences.

Another new innovation also helps support profitable growth: 麻豆原创 recently launched the . Natively integrated with the 麻豆原创 ERP application, it makes ordering, invoicing, and promotions more intuitive while giving business buyers a positive digital experience.

, a global leader in wood products and furniture, relies on 麻豆原创 Commerce Cloud as an integral part of managing a complex supply chain. The Chilean forestry company connects customers with on-demand insight into their orders through a self-service portal.

鈥溌槎乖� Commerce Cloud provided us with the tools to create a portal that has exceeded our customers鈥� expectations again and again,鈥� said Diego Tuleski, director of IT at ARAUCO North America Inc.

Other global leaders are realizing measurable impact as well. uses 麻豆原创 Commerce Cloud to streamline complex service orders and improve customer account management. For , 麻豆原创 Commerce Cloud helps digitalize and manage complex order processes, making them intuitive experiences through integration with existing ERP applications. delivers favorable guest experiences across theme parks, hotels, and retail with 麻豆原创 Commerce Cloud, enabling millions of transactions on a single commerce platform integrated with 麻豆原创 Cloud ERP solutions.

To learn more about 麻豆原创鈥檚 position as a Leader and see an in-depth analysis of the digital commerce landscape, .

Kollen Glynn is global head of 麻豆原创 Commerce Cloud, 麻豆原创 Customer Experience.

_{Gartner, Magic Quadrant for Digital Commerce, Aditya Vasudevan, Ant Duffin, Mike Lowndes, Sandy Shen, Jason Daigler, Penny Gillespie, 3 November, 2025.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.}

_{麻豆原创 was recognized as 麻豆原创 Hybris in 2014, 2016 and 2017.}

This weekend, the golf drama will unfold at the storied Bethpage Black Course in New York, as rivalry and camaraderie collide. For the first time, 麻豆原创 will be at the heart of the action as a Worldwide Partner of the 2025 and 2027 Ryder Cup.

Transforming the Ryder Cup fan experience

Since its inception in 1927, the Ryder Cup has united millions of fans around unforgettable moments. Yet behind the emotion and spectacle lies immense complexity. Two distinct organizations, the PGA of America and Ryder Cup Europe, must come together every two years to deliver a seamless tournament experience.

Going into the 2025 event, the Ryder Cup turned to 麻豆原创 for help in transforming what it means to engage fans across the two organizations. With a goal of moving beyond a 鈥渙ne-day鈥� experience to building an 鈥渆veryday鈥� connection, the Ryder Cup wanted to ensure every fan — whether onsite or halfway across the world — feels immersed in the tournament, experiencing the excitement, emotion, and strategy as if they were on the course.

This partnership will allow the Ryder Cup to benefit from using 麻豆原创 technologies to further enhance the experience for fans. 麻豆原创 Customer Data Platform will unify fan data from multiple sources, creating a single, comprehensive profile for each fan. 麻豆原创 Emarsys will then use that data to deliver personalized content across marketing channels. 麻豆原创 Datasphere will harmonize customer and business data and help identify insightful correlations, making it ready for visualization in 麻豆原创 Analytics Cloud, where insights can be turned into action. 麻豆原创 Datasphere and 麻豆原创 Analytics Cloud are part of 麻豆原创 Business Data Cloud.

Together, these solutions will help the Ryder Cup gain a deeper understanding of audience behavior, drive engagement, and deliver personalized experiences at scale, while paving the way for future AI-driven innovation and a globally connected fan journey. Beyond tournament week, this 360-degree view of each fan will provide insights that benefit both organizations year-round, improving planning, marketing, and engagement that can be scaled across other professional tournaments.

Shared values in action

The Ryder Cup is more than a sporting event. It is a showcase of teamwork, resilience, and strategy — qualities that are equally essential in business. At its core, every Ryder Cup moment is defined by a challenge that demands a solution, whether it鈥檚 a player navigating tough conditions, making a critical decision under pressure, or leading a team to victory.

Through this partnership, 麻豆原创 highlights the performance and collaboration that drive success, inspiring organizations and individuals to bring out their best on the course and in business.

Looking ahead

As anticipation builds for Bethpage Black this weekend, fans will see and feel 麻豆原创鈥檚 presence throughout the tournament, from on-course signage to coverage on TV, online, and social channels.

Beyond the event, 麻豆原创 and the Ryder Cup are laying the foundation for a new era of fan engagement, connecting millions of fans around the world and helping to create moments that will be remembered long after the final putt.

These moments are the building blocks of delivering seamless and memorable experiences — and lasting loyalty.

At 麻豆原创, we believe every touchpoint is more than a chance to meet a need. It is an opportunity to deepen trust, demonstrate value, and strengthen the relationship between customer and brand. That belief is at the heart of the 麻豆原创 Customer Experience (麻豆原创 CX) portfolio — now infused with the power of AI.

Our Q3 2025 release reflects this vision. Intelligence is embedded across the entire customer journey. Generative AI helps service teams classify cases the moment they arrive. Autonomous agents in commerce guide customers to the right products with real-time stock visibility. For marketers, AI personalizes campaigns and generates segment descriptions and translations, ensuring relevance at scale. For sales teams, AI keeps data clean and actionable, eliminating duplicates and surfacing the right opportunities at the right time.

 AI isn’t just about efficiency alone; it is about elevating every interaction into a moment where trust can be deepened and loyalty earned.

Here are the highlights from 麻豆原创 CX in Q3 2025.

AI that drives results

From decision-making to customer engagement, AI-powered intelligence and agents streamline processes and remove friction. Teams gain the ability to respond faster, deliver smarter interactions, and grow with confidence while delivering customer experiences that feel effortless, reliable, and personalized.

麻豆原创 Service Cloud

• Business information extraction in cases: Save time by automatically extracting registered product information from the case description, using pre-delivered elements for business information extraction.

麻豆原创 Sales Cloud 

• Contact and individual customer duplicate checks: Maintain clean, accurate records by managing redundant and data. This generative AI capability checks for duplicates and returns a confidence score, leaving the decision-making in human hands.

麻豆原创 Emarsys 

• AI-assisted product finder: Enable marketers to use natural language prompts and keywords to quickly search and locate products for targeted campaigns. Automatic product catalog sync ensures you are always working with the most up-to-date data.
• AI-assisted segment description generator: Generate human-readable segment summaries to improve execution. This ensures that existing segments are easily discoverable with descriptions that are intuitive and straightforward.
• AI-assisted campaign translator (pilot): Translate email campaign copy flexibly and seamlessly within the editing workflow. Localize product descriptions across languages to quickly build, optimize, and launch multi-language campaigns.

麻豆原创 Commerce Cloud 

• Shopping Agent: Using product stock awareness to return real-time inventory data, the configurable Shopping Agent can display or hide out-of-stock products in its recommendations. This makes for smarter recommendations, reducing friction and abandoned carts. For B2B transactions, merchants can also choose whether the agent answers questions about bulk product availability.

麻豆原创 Revenue Growth Management

• AI-assisted promotion creation: Create new promotions quickly by getting recommendations for promotion names, when to run a promotion, what products to include, which spend type to use, and recommendations for discount type.

Scale smarter with greater flexibility

Scaling efficiently while providing flexibility for customers means optimizing operations, offering expanded channel options, and extending visibility to customers and partners.

麻豆原创 Emarsys 

• Microsoft Ads integration: Scale personalized ad experiences across the Microsoft Search Network, including Bing, Yahoo, AOL, and other Microsoft properties.
• Conversational messaging for LINE (): After expanding our offering to in the Q2 release, we now support the popular conversational channel LINE, giving marketers a direct way to connect with customers in the channels they use every day and making it easier to turn engagement into conversion.

麻豆原创 Commerce Cloud 

• Central order service: This feature for seamlessly integrates online and offline transactions, paving the way for flexible customer experience scenarios like “buy online, return in store” (BORIS) and “buy in store, return online” (BISRO).
• Availability push: now allows customers to proactively send real-time product availability information to external systems like webshops and marketplaces, ensuring they have the most current stock data without needing to request it.

麻豆原创 Sales and Service Cloud 

• 麻豆原创 Preferred Success: We are empowering our customers to make the most of their 麻豆原创 investments with the . This interactive workshop helps participants pinpoint which processes to optimize, outsource, or remove for the greatest impact. Learn how to identify critical processes, define roles and responsibilities, and establish a sustainable approach to process governance.
• Integration review V2: A comprehensive solution launch checklist for 麻豆原创 Sales Cloud and 麻豆原创 Service Cloud Version 2 integrations ensures successful rollouts and compliance with 麻豆原创 best practices. The checklist systematically evaluates authentication mechanisms, interface configurations, middleware settings, and 麻豆原创 Integration Suite implementation. 

麻豆原创 Enterprise Service Management

Updates to include:

• Case summary enhancements: Sentiment trend and sentiment graph can now be enabled in the interaction summary for additional information on a customer. Internal and external case notes can be configured and used to generate the resolution summary overview.
• Custom services: Gain more flexibility and extend capabilities without modifying the core application. Integrate external functionality into 麻豆原创 Service Cloud V2 with custom services.
• Template visibility and restrictions: Every document is also an opportunity to establish trust. Now you can strengthen document security by limiting template access to those who need it.

麻豆原创 Revenue Growth Management 

New to  are:

• Custom KPIs: Assess the performance of your account and promotion planswith custom KPIs, tracking metrics that suit your planning and reporting processes. Save time by creating KPI profiles to define a set of standard pre-defined KPIs.

• Promotion calendar export to PDF: Reduce uncertainty, lower costs, and build relationships with better alignment on annual promotions and EDLP agreements with customers. Key account managers can now share a promotion calendar and associated promotion details in a PDF file, making collaboration easier and decisions faster.

Trust advantage in AI-powered customer experience

AI is now woven into the fabric of the 麻豆原创 CX road map, guiding how data, processes, and experiences come together. This deep integration sets the stage for a new era of customer engagement, one where intelligence anticipates needs, adapts in real time, and continuously strengthens loyalty at every touchpoint.

Learn more about what is new in 麻豆原创 CX Q3 2025

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Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience.

This makes a lot of sense given that today However, the results aren鈥檛 always matching the hype.

A recent found that while enterprise AI adoption is rising, real impact is often elusive. The reason? Many businesses are still operating with disconnected systems and disjointed data. Without a strong foundation, AI can鈥檛 deliver what it promises.

Siloed systems aren鈥檛 just a technology problem鈥攖hey鈥檙e a business barrier.

The CX Disconnect: When Fragmentation Undermines Intelligence

Too many organizations still rely on a patchwork of tools for customer experience, supply chain, finance, and HR. While these point solutions solve individual challenges, they create friction and disconnect across the business. In an AI-powered world, friction is the enemy.

AI thrives on complete, clean, and . If your marketing, sales, service, and fulfillment teams cannot see the same data in real time, or trust that it鈥檚 accurate, your AI strategy will not be set up to succeed.

With the best intentions to embrace AI in an effort to achieve incredible efficiency, instead, customers will still lose valuable time on manual integration, inconsistent customer experiences, and AI outputs that are only as good as the (fragmented) feeding them. The delightful experience aspirations turn into trust lost and frustration all around.

Modular Innovation, Meet Enterprise Intelligence 

麻豆原创 has reimagined enterprise management with , representing a fundamental shift from traditional ERP systems to a modular, composable architecture that integrates AI, data, and applications into a unified platform.  

Grounded in harmonized, semantically rich data, this architecture allows businesses to make sense of data that has traditionally been scattered across systems and trapped in silos, so AI has the comprehensive data it needs to quickly generate meaningful insights.

麻豆原创 Business Data Cloud (麻豆原创 BDC) with native integration of 麻豆原创 Databricks, serves as a data backbone for business AI. It seamlessly connects all 麻豆原创 data and third-party data and provides integrated governance to enable real-time AI-driven decision making. 听

Companies do not lose precious time locating and preparing data for AI. AI systems work on trusted, contextualized data, not just generic data. This produces accurate, reliable, and actionable AI recommendations that enable organizations to scale AI innovation rapidly across business domains.听

麻豆原创 BDC is the foundation for , 麻豆原创鈥檚 AI copilot that acts as an intelligent orchestrator across the entire business suite. 麻豆原创 BDC ensures that Joule has structured business context for natural language processing and that its outputs are accurate so that Joule can provide always-on assistance to break down silos between business operations.听

For example, when a customer service or sales representative handles a complex order issue, Joule can: 

• Check real-time supply chain constraints

• Respond to RFPs faster
• Personalize the response by pulling in relevant customer history from
• Speed response with automated case routing and research

The results are faster resolutions, happier customers, empowered employees, and incredible business outcomes with less effort and overhead.

CX + AI + ERP = Real Results

Integrating CX AI with core ERP systems enables end-to-end process optimization that was previously impossible with fragmented systems. When CX systems connect natively to back-office systems, organizations gain:听

• Real-time personalization powered by operational data
• Intelligent workflows that prioritize high-value customers
• Predictive insights that help teams act before issues arise

The numbers speak for themselves. According to an , customers using this approach reported these benefits:

• Up to 60% reduction in the number of issues service and support teams deal with due to fewer manual errors, automated self-service support functions, automated self-service, and AI chatbots
• 25% to 50% improvement in time to resolution for issues that did require service or support resources
• 25% to 70% improvement in productivity of digital marketing and customer operations teams
• 50% to 90% improvements in sales team productivity by offloading smaller transactional sales, faster quote generation, and streamlined order management
• 20% to 40% increase in productivity of business operations due to less time spent on invoices, payments, shipments, and returns and more informed decision-making

This is not just incremental change; it鈥檚 enterprise transformation, driven by customer needs and powered by AI.

The Future of Intelligent Enterprise Operations 

Embedded within a composable business suite represents a bright future that takes the possibility of AI and makes it a reality.听

• Businesses can seamlessly orchestrate intelligence across all functions, delivering experiences that feel effortless to customers while optimizing operations behind the scenes.听
• Artificial intelligence won鈥檛 just automate individual tasks, but also orchestrate entire business ecosystems to deliver superior outcomes.听听
• Maintaining enterprise-grade reliability and enabling modular innovation will allow organizations to adapt to changing market conditions while creating competitive advantages.听

With the rise of AI, businesses face a pivotal moment in time. Taking advantage of all that technology has to offer demands more than point solutions and departmental optimizations; it requires unified platforms, complete clean underlying data, and a clear unified strategy.

Jessica Keehn is chief marketing officer of 麻豆原创 Customer听Experience.

Research from multiple industry sources indicates that this isn鈥檛 just an emerging trend — the emphasis on consolidation is growing at an unrelenting pace.

According to ADAPT’s CIO Edge , a comprehensive study of more than 140 CIOs, are planning to consolidate their vendor landscape.

This trend is not just about making minor adjustments to meet market demands; a majority of organizations are targeting a , which represents a significant and fundamental shift in how enterprises approach their technology ecosystems.

The urgency for CIOs to transform their vendor landscape is palpable across all sectors and industries. A of more than 1,000 technology professionals revealed that 90 percent of IT professionals identified software consolidation as a priority, with 73 percent predicting their organizations will continue growing software investments while simultaneously consolidating vendors.

This paradox — expanding capabilities while reducing complexity — defines the modern CIO’s challenge.

The false promise of best-of-breed

This vendor consolidation trend contrasts with movements like the MACH alliance, which  promotes a pure 鈥渂est-of-breed” approach. While its underlying architectural approaches (Microservices, API-first, Cloud-native, Headless) are sound and arguably have become table stakes in the SaaS world, MACH created unexpected challenges for enterprises.

Initially lauded for its flexibility and agility, MACH ended up creating significant complexity 鈥� more than most enterprises can handle 鈥� at a time when they are looking for simplicity more than ever.

The economic reality is stark: fully MACH implementations usually upfront compared to a unified solution that is pre-configured. Companies must consider not only the purchasing of multiple services, but also the cost and time required for employee training and adoption. Running MACH architecture requires people with highly specialized skills in cloud infrastructure, APIs, microservices, and tools designed to streamline development of the user-facing part of a website or web application. The job market for that talent is uber-competitive, even in the age of AI, meaning you’ll need to have the resources to pay them well or else your competitors will.

The hidden costs of fragmentation

Research reveals several critical drawbacks to the fragmented fully best-of-breed  approach:

• Increased complexity: Managing hundreds of microservices becomes exponentially daunting and expensive rather quickly, with system issues potentially impacting multiple services simultaneously. The management and expertise required to oversee such architectures can be daunting 鈥� and expensive. Once system issues are discovered, they could impact numerous services, which requires deep knowledge coordinated across multiple areas of expertise for troubleshooting and debugging. This can make resolution complicated and cost prohibitive.
• Integration challenges: Trying to make connections between services and systems that were not designed to work together requires additional development expertise, which is expensive.听 Incompatibilities between functions like search, customer service, catalog management, and OMS can lead to degraded customer experience and loss of loyalty.
• Security concerns: The beauty of MACH architecture is also the beast: all of the composable microservices, APIs, and cloud offerings represent security risks. Comprehensive security requires consistent implementation across all components, which can be challenging when using solutions from different vendors. Businesses must develop robust security frameworks and governance models to ensure protection across their entire MACH ecosystem.
• Vendor management complexity: Best-of-breed usually means working with dozens of vendors rather than a few, which can add vast complexity to development and customer support depending on the long-term viability of each vendor, which must provide critical functionality for services or tools that could be discontinued or significantly changed in the future.

The strategic advantage of unified platforms

As CIOs prioritize vendor consolidation, 麻豆原创’s approach to “Suite as a Service” or “best of breed as a suite” offers a pragmatic solution that addresses the fundamental challenges of fragmented architectures. Rather than forcing organizations to choose between flexibility and integration, the (麻豆原创 CX) portfolio provides both through a unified yet composable business suite that spans front and back-office operations, in conjunction with a pre-integrated and certified rich ISV ecosystem that allows businesses to compose with intention, wherever this makes sense business-wise.

The flywheel effect: applications, data, AI

The true power of consolidated platforms lies in what 麻豆原创 calls the “flywheel effect.鈥� In this model, applications generate data, data trains AI, and AI optimizes applications. This creates a virtuous cycle where:

• Better data feeds better AI
• Better AI feeds better applications
• Better applications generate better data

This integrated approach is only possible when organizations move beyond siloed point solutions to embrace unified platforms that can leverage the full spectrum of business data. Companies already invested in 麻豆原创 technologies have discovered that a to the data architecture that AI requires.

Quantified benefits: the economic case for consolidation

of 麻豆原创 CX solutions reveals compelling evidence for the vendor consolidation approach:

• Operational Efficiency Gains
  • Faster time to value: Organizations can fully connect and integrate their CX and ERP data in as few as six months
  • Reduced implementation time: Companies avoid roughly 25 to 50 percent of the time and effort required to build integrations from scratch
  • Improved productivity: Depending on job function, customers report 10 to 300 percent improvement in daily productivity
• Cost Optimization
  • Lower total solution costs: While individual solutions may appear cheaper, the holistic end-to-end solution approach is far more cost-effective
  • Reduced maintenance overhead: Organizations can eliminate up to 70 percent of the time required to manage and maintain systems
  • Resource optimization: Companies avoid having to grow teams by up to 2x to support custom development and integrations
• Strategic Advantages
  • Enhanced customer experience: Seamless connectivity between customer and operational data enables superior customer service
  • Faster innovation: End-to-end visibility enables quicker, more informed decisions leading to faster product launches
  • Reduced operational risk: Standard iFlows provide more reliable connections with fewer potential connectivity issues

The AI-driven imperative

AI is driving the consolidation trend as much as the need to reduce costs. AI models demand high-quality, accurate data to be useful. When — often the result of disconnected digital tools — AI efforts fall short of expectations or stall entirely.

麻豆原创’s unified approach addresses this challenge directly. By providing harmonized SLAs, UX, data models, and provisioning across the stack, along with embedded AI via 麻豆原创 Business AI and a unified and semantically rich data layer via 麻豆原创 Business Data Cloud, organizations can fully leverage AI capabilities across domains without the complexity of integrating multiple disparate systems.

The consolidation acceleration

The trend toward vendor consolidation is accelerating across multiple dimensions:

• Seventy-five percent of organizations pursued vendor consolidation in 2022, up from 29 percent in 2020, according to
• that by 2027, 70 percent of organizations will optimize cloud-native application vendors to a maximum of three
• For midsize companies, the average number of SaaS tools in the last two years

The path forward: strategic consolidation

The evidence is clear: 2025 marks a pivotal moment for CIOs. Organizations that embrace strategic vendor consolidation and choose unified platforms over fragmented point solutions will gain significant competitive advantages in operational efficiency, cost management, and AI readiness.

麻豆原创 CX represents the future of customer experience technology 鈥� not as a collection of disparate tools, but as a unified, intelligent platform that can adapt and evolve with business needs. As CIOs navigate the challenges of 2025, the choice between complexity and consolidation will define their success.

The question isn’t whether to consolidate; it’s whether to lead the trend or be left behind.

With 68 percent of CIOs already planning consolidation initiatives, organizations that act decisively on vendor consolidation will be best positioned to win when it comes to the future of enterprise technology.

Geert Leeman is chief revenue officer of 麻豆原创 Customer Experience.

Every moment in the customer journey is a chance to deliver value, earn trust, and build relationships. But delivering consistently great experiences means adapting to evolving trends and expectations with a connected approach to people, data, and systems. 

The Q2 2025 release of the (麻豆原创 CX) portfolio does just that. Whether engaging customers, streamlining operations, or empowering employees, this release delivers smarter, faster, more personalized experiences at scale. Powered by AI with harmonized data, it brings improvements across the customer experience life cycle, from first touch to long-term growth, with seamless, value-generating experiences across service, sales, marketing, commerce, and consumer industries.听听

Here are the highlights from 麻豆原创 CX in Q2 2025.  

Making every interaction count 

Everyday moments turn into meaningful engagements when experiences are connected, relevant, and effortless. This release helps users go beyond meeting customer needs to building trust and loyalty at every touchpoint.听

麻豆原创 Service Cloud  

• Business Information Extraction: and convert it into structured, usable documents 鈥� like auto-filling case descriptions from customer emails 鈥� saving time and manual effort.

麻豆原创 Commerce Cloud 

• B2B Self-Service Portal: Raise customer satisfaction and reduce service volume with this scalable, easily implemented . B2B customers can view order status, invoices, and delivery updates鈥攔egardless of how the order was placed. 
• AI Shopping Agent: to drive conversions and growth. With prompting questions and natural, conversational language, the agent guides product discovery and enables in-chat actions like add to cart as well as view order and shipping details.

麻豆原创 Emarsys 

• Enhancements 
  • Segmentation: Combine wallet and customer data to target the right people; for example, reengaging those who have not interacted recently with Mobile Wallet campaigns.
  • Expanded Wallet Delivery Channels: Reach customers anywhere with the new Mobile Inbox and Mobile Push channels.
  • Pass Notifications: Automatically deliver timely lock-screen updates for on-the-spot engagement and conversion with mobile wallet users or targeted customer segments. 
• WhatsApp Template Messaging: like promotions and order updates using the rich content, personalization, and multi-language support in 麻豆原创 Emarsys.
• Conversational Messaging for WhatsApp (): Have based on contacts鈥� responses.

Scale smarter, operate better 

Sustainable growth requires operational efficiency and built-in customer experience. With unified data connected to core business operations and AI-driven insights, these updates improve internal operations, enhance scalability, and set the foundation for differentiated customer experiences.听

麻豆原创 Commerce Cloud 

• B2B Self-Service Portal: Give customers transparency without committing to full commerce and scale when ready, without data migration or replatforming.听Launch this for B2B customers in just weeks with partner packages that simplify setup and accelerate time to value. Built as an ERP add-on, the portal connects natively with back-end systems to surface real-time order and invoice data, reducing support workload and improving the customer experience with accurate, always-on self-service. Out-of-the-box compatibility with 麻豆原创 S/4HANA and 麻豆原创 Cloud ERP means faster setup, less IT effort, and long-term flexibility.听
• Open Payment Framework: Support for brings unified checkout, reliability, and built-in security and validation to the payment experience, accelerating time to market and increasing conversions.听

麻豆原创 Sales and Service Cloud听

• : Accelerate time to value and maximize your investment in 麻豆原创 with services navigator for 麻豆原创 Sales Cloud and 麻豆原创 Service Cloud Version 2 implementations. Part of 麻豆原创 Preferred Success for 麻豆原创 Customer Experience solutions, the navigator helps users discover relevant services from their 麻豆原创 Preferred Success subscription for each stage of a project, align support offerings with project goals and timelines, and improve business outcomes with accelerated adoption and reduced risk.
• : Reduce the costs and complexity of internal issue resolution with unified service delivery. By centralizing and structuring inquiry management and response, out-of-the-box integrations of 麻豆原创 Enterprise Service Management with 麻豆原创 Business Suite applications break down silos to improve service delivery across finance, HR, marketing, facilities, sales, support, and more.听

麻豆原创 Revenue Growth Management听

New to in Q2 2025 includes:听听

• Fund management: Gain control over trade spend鈥攃reate funds, manage and adjust fund budgets, and track spending for promotions.
• Analytics dashboards: Get quick access to planning data and insights into P&L for individual promotions with embedded 麻豆原创 Analytics Cloud, 麻豆原创 Revenue Growth Management analytics dashboards.听

AI that accelerates impact

Across the experience life cycle, AI-powered embedded intelligence and autonomous AI agents help unlock faster decisions and better outcomes. This release helps teams move faster, engage smarter, and scale with confidence.

麻豆原创 Sales Cloud 

• Sales Order Summary: Enable sales managers to act quickly with like price changes, product substitutions, on-time delivery probability, and more 鈥� boosting accuracy and profitability.
• Account Duplicate Check: Protect data quality and reduce the manual effort of dealing with redundant data. Account Duplicate Check uses AI to so users can maintain clean, accurate records and drive smarter engagement.听

麻豆原创 Service Cloud 

• Registered Product Summary: Empower agents with a of a product鈥檚 service history, turning standard service calls into a strategic conversation. 
• Business Information Extraction: from unstructured documents using AI, helping unlock insights and action.听

麻豆原创 Emarsys 

• Natural Language Search for Product Curation: Enable marketers to using natural language search, helping them move faster and build the right use cases. 

Innovation that connects it all

From loyalty to growth to operational agility, these innovations help deliver more intelligent, connected experiences at every touchpoint 鈥� with the adaptability and scalability to grow lifelong customer value. 

Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience.

In the AI era, relying on standalone line-of-business applications limits growth. To unlock their full potential, businesses need a connected business suite, a unified data strategy, and a powerful data foundation 鈥� forming an integrated system that breaks down silos, empowers teams, and enables personalized engagement.

Foundation for intelligent growth

With more than 50 years of expertise in managing critical business data, 麻豆原创 helps companies unlock AI that is relevant, reliable, and responsible. This year at , we announced innovations for customer-centric, AI-powered growth 鈥� whether paired with 麻豆原创 or non-麻豆原创 solutions. These innovations build on the three critical growth drivers:

• delivers real-time insights and connections across systems and data. With built-in AI, it transforms complexity into clarity and enables fast, agile action.
• centralizes trusted internal and external data, breaking down silos to deliver real-time visibility and insights for personalized experiences.
• , is central to this growth strategy and brings AI into every interaction 鈥� from marketing to service 鈥� tapping into business-critical data to deliver seamless, context-rich experiences, while maximizing the value of existing 麻豆原创 investments.

This integrated approach enables smarter decisions, more responsive service, and long-term loyalty.

Our latest innovations expand upon this growth engine, helping companies stand out.

AI-driven automation for accelerated impact

Our expanding portfolio bridges the gap between intelligence and automation. These ready-to-use AI agents automate routine tasks deliver value quickly with minimal configuration. New agents include:

• Quote Creation Agent: Drafts structured, CRM-ready quotes, reducing response time from hours to minutes. Learn more about .
• Catalog Optimization Agent: Continuously improve SEO and product descriptions to improve discoverability and conversion. Learn more about .

Working seamlessly within existing 麻豆原创 CX environments, Joule Agents preserve human judgment where it matters most while automating the rest, freeing teams to focus on growth.

Connections that drive efficiency and growth

unifies service delivery across sales, marketing, HR, finance, procurement, and more, powered by AI and embedded across 麻豆原创 Business Suite. With its unique focus on user experience, it boosts productivity and operational excellence.

For 麻豆原创 CX users, it centralizes processes for sales inquiries and support, accelerating close rates and shortening deal cycles. This unified approach turns fragmented service into seamless, AI-powered orchestration.

Key capabilities across the 麻豆原创 portfolio include:

• : Self-service and AI routing of complex issues frees HR teams for strategic priorities
• Finance: Automates accounts receivable/payable inquiries, disputes, and discrepancies to improve accuracy, shorten AR turnover, and accelerate cash flow
• : Centralized, AI-driven sales inquiries and support, improves response times and boosts close rates

Automation and unified systems help streamline operations and strengthen customer relationships, fueling satisfaction and growth.

Smarter revenue management for maximized growth

Launching in the third quarter 2025, helps consumer packaged goods companies optimize promotions, budgets, and ROI with AI insights and real-time financial data. integration helps prevent overspend and supports 麻豆原创 Sales and Operations Planning with .

Key enhancements include:

• Visibility into revenue, margin, ROI, volume, and profit and loss data for account performance insights and better trade promotion decisions
• Promotion spend insights via integrated 麻豆原创 Cloud ERP
• More accurate forecasting with 麻豆原创 Integrated Business Planning and streamlined budget planning with
• Improved trade promotion budget management at customer and product levels, aligned to financial plans

By turning promotion data into demand signals, companies can optimize promotion strategies, reduce overspend, and deliver personalized, data-driven interactions at scale.

Scalable success: from self-service insights to full B2B commerce

, a powerful 麻豆原创 Cloud ERP add-on, gives B2B customers secure, 24/7 access to real-time order data from all sales channels. Designed for digital-first buyers, it reduces support workload and creates a solid foundation to scale and expand into full B2B e-commerce.

Key capabilities include:

• Native 麻豆原创 Cloud ERP integration for real-time order and invoice data across channels with no middleware or data duplication
• Omnichannel visibility — EDI, email, phone, fax, direct sales, e-commerce — for one-stop customer order data access
• Rapid time to value with preconfigured data models, UI templates, and our vetted partner ecosystem
• Faster issue resolution with user emulation, allowing support teams to see what the buyer sees
• Future-ready scalability that easily extends to full B2B e-commerce without re-platforming

With low TCO and deployable in just weeks, the portal supports digital-first convenience and long-term growth.

Easy, adaptable, future-ready payments

While 麻豆原创 B2B Self-Service Portal empowers B2B customers with real-time access to orders and transactions, 麻豆原创 Commerce Cloud, open payment framework modernizes payments. Its no-code, low-code architecture enables flexible support for methods like buy now, pay later and a wide range of third-party payment service providers, including Stripe, Adyen, Worldpay, and Airwallex. Announced in the first quarter, the solution allows rapid deployment and customized payment solutions.

Benefits include:

• Rapid customization of payment experiences for seamless experiences
• Flexibility to meet evolving buyer needs
• Seamless scalability while ensuring compliance and security
• Reduced complexity and time to value

Together, these capabilities form the foundation for long-term growth.

Real-time data intelligence for seamless experiences

As businesses gain control over payment experiences, they also need real-time visibility into the transactions driving their operations. Customers expect consistent, personalized experiences across channels, from in-store to mobile to online, at every touchpoint.

, a modular, cloud-native solution bundle, unifies point-of-sale and digital order data, processes high-volume transactions in real time, and ensures accurate inventory availability across locations. It supports flexible fulfillment and returns, such as buy online, pick up in-store (BOPIS), and return anywhere, and enables more intelligent inventory planning, sourcing, and channel-aware promotional planning.

These capabilities reduce operational friction, increase loyalty, and help businesses scale profitably and sustainably.

Turning customer experience into competitive advantage

These innovations enable a growth strategy that transforms customer experience into a powerful competitive advantage. By connecting data, processes, and interactions with AI-driven insights, businesses can deliver proactive, tailored experiences that foster loyalty and fuel growth.

麻豆原创 is committed to helping customers harness the power of customer experience. These innovations reflect our focus on delivering real-world value and unlocking new growth opportunities.

Learn more about our and how they can help your business grow.

Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience.

Behind the scenes, retailers struggle to deliver these experiences due to fragmented, outdated, and incomplete data that makes real-time decision-making nearly impossible and hampers engagement, operational efficiency, and, ultimately, profitability.

The hidden costs of disconnected data

When retailers鈥� data exists in silos, the problem is compounded from all angles. With sales, inventory, marketing, and customer engagement data living in separate systems, retailers lack the clear view of customer behavior and business insights they need to respond with critical actions in real time. Lack of context within the data means businesses struggle to extract meaningful insights.

Consider the impact:

• Limited inventory visibility leads to stockouts and overstocks, frustrating customers and eroding profits.
• Lack of real-time insights hinders personalized customer engagement, diminishing loyalty.
• Disconnected operations make omnichannel fulfillment鈥攕uch as buy online, pick up in-store (BOPIS) or hassle-free returns鈥攄ifficult to execute smoothly.

At a moment when retailers must optimize every facet of their business to remain competitive, a unified data strategy isn鈥檛 optional鈥攊t’s essential.

A data-driven future: Turning insights into action

To break these silos, retailers need a unified data foundation鈥攐ne that consolidates insights across all customer touchpoints, enabling real-time intelligence and business agility. 麻豆原创 Business Data Cloud (麻豆原创 BDC), as recently announced, is an integrated solution that can bring data together from all sources, owned and external, to help create a single, trusted source of truth.

With 麻豆原创 Business Data Cloud, retailers can have the total picture of data from sales, inventory, marketing, loyalty, service, and near-real-time statuses of third-party logistics.

With this holistic view, retailers can:

• Enable seamless cross-channel fulfillment, such as buy online, pick up in-store or return anywhere.
• Optimize operational efficiency for everything from intelligent sourcing and promotional planning to inventory visibility and availability across sales channels.
• Personalize customer engagement by leveraging data-driven insights to boost loyalty and increase revenue.

By shifting to a data-first approach, retailers can move beyond managing transactions to driving intelligent, customer-centric experiences for long-term loyalty and growth.

Why physical stores still matter鈥攎ore than ever

Despite the rise of e-commerce, more than 80% of retail interactions still take place in physical stores. Brick-and-mortar locations remain central to the retail journey, yet, as retailers鈥� largest cost center, they also encompass the biggest operational challenges鈥攆rom inventory carrying costs to labor and store operations.

Although today鈥檚 consumers are fluid in how they shop鈥攔esearching products across multiple platforms or buying online and picking up in-store, for example鈥攖hey still expect accurate, real-time visibility into inventory wherever they engage. In this landscape, data is the lifeblood that allows retailers to orchestrate orders, manage workflows, and ensure that customers can trust the information they see. Yet, according to , 51% of U.S. brands say their organization suffers from “dark data,” which is data that is collected but not effectively used.

To remain competitive, retailers must harness real-time transactional insights to optimize store efficiency, maximize revenue, and provide seamless customer interactions.

Bringing it all together: Intelligent order management

Retailers don鈥檛 just need data鈥攖hey also need actionable, real-time intelligence that helps them drive smarter decision-making. That鈥檚 why 麻豆原创 is integrating advanced order management capabilities as part of our broader data-driven customer experience strategy. 麻豆原创 has a long history of helping thousands of retail and B2C customers manage vast amounts of data. Today we鈥檙e tailoring this expertise, trusted by market leaders worldwide, to help meet the scale, flexibility, and time-to-value required by fast-growing organizations.

As part of the bundle, we are launching the 麻豆原创 Omnichannel Sales Transfer and Audit solution today at in Las Vegas, Nevada. This modular, cloud-native solution can empower retailers with real-time visibility into transactions and inventory, helping to reduce friction and improve customer satisfaction. 麻豆原创 Omnichannel Sales Transfer and Audit can unify POS data from multiple systems, process high-volume transactions in real time, and help ensure inventory accuracy across all channels to improve stock availability, financial reporting, and customer engagement鈥攚ithout the burden of complex, custom-built integrations.

Apart from omnichannel sales and audit capabilities, the 麻豆原创 Order Management Services bundle also includes additional modular, cloud-native capabilities including and the . The 麻豆原创 Order Management Services bundle is natively connected with 麻豆原创 S/4HANA, which can enable retail and consumer products organizations and other consumer brands to unlock real-time inventory visibility, streamline fulfillment, and reduce operational costs without complex and costly custom integrations. And, integrated with 麻豆原创 S/4HANA Cloud Public Edition, retail, fashion, and vertical business, announced at NRF earlier this year, the cloud-native capabilities of the 麻豆原创 Order Management Services bundle can be even more scalable, secure, compliant, and affordable, enabling retailers to realize value more quickly than ever before.

Other benefits of 麻豆原创 Omnichannel Sales Transfer and Audit include:

• Seamless POS integration can connect multiple POS systems with different data structures, working to eliminate silos and ensure data accuracy.
• Real-time inventory updates help keep omnichannel inventory accurate so customers can trust what they see online matches what’s available in-store.
• Smarter data processing and configurable data transfer and aggregation help update inventory, financials, and even loyalty programs effortlessly.
• Optimized sales data validation process can automate checks that are executed through configurable workflows.

By embracing a unified data strategy, retailers can eliminate complexity, reduce costs, and unlock new opportunities for growth鈥攁ll while delivering the frictionless experiences today鈥檚 consumers expect.

Hornbach: The future of omnichannel retail in action

For Hornbach, one of the largest DIY stores in Germany, . It needs to be able to add new channels quickly鈥攁nd to maintain a seamless customer experience over all channels. Hornbach adopted 麻豆原创 Order Management Services as a foundation for this vision, enabling the flexibility to address new markets quickly, connect new systems, process orders rapidly and efficiently, and adopt new innovations. With the addition of 麻豆原创 Omnichannel Sales and Transfer Audit, the Hornbach team expects to get more visibility in day-to-day operations, like checking fraud detection and the completeness of transactions.

鈥淭he most exciting thing will be the combination of all these new technologies we鈥檙e seeing: artificial intelligence, event-driven architecture, as well as native cloud solutions,鈥� said Carsten Mueller, head of Enterprise Architecture and Security, Hornbach. 鈥淭he combination will give Hornbach great power in the next year.鈥�

The future of retail is data-driven

The retail industry is evolving at an unprecedented pace, with AI redefining how businesses operate and interact with customers. According to the same 麻豆原创 Emarsys report, 89% of U.S. consumer product marketers believe AI will be essential for engaging new customers. However, the effectiveness of AI hinges on the reliability and accuracy of the data it processes.

Retailers that embrace AI-powered data intelligence will lead the next era of omnichannel excellence. The future isn鈥檛 just about connecting data鈥攊t’s about activating it in real time to drive seamless customer interactions.

To stay ahead, retailers must:

• Invest in AI-driven analytics to predict demand, optimize pricing, and personalize engagement at scale.
• Implement intelligent order and transaction management to automate fulfillment, reduce friction, and improve supply chain agility.
• Leverage AI-powered customer insights to create hyper-personalized experiences that drive loyalty and lifetime value.
• Enable real-time inventory intelligence to ensure products are available where and when customers need them.

As omnichannel complexity grows, brands that fail to unify their data risk falling behind. 麻豆原创 Business Data Cloud and intelligent order management solutions can provide the foundation for a future-proof transformation. As AI continues to evolve, retailers must shift from reactive decision-making to proactive, predictive commerce, where every transaction is optimized for efficiency and profitability.

The future of retail is here. Those who harness AI to unify, analyze, and act on their data will define the next generation of customer experience and retail success. I鈥檓 excited to partner with companies navigating this transformation and empower them to seize new opportunities for success.

Want to learn more? Stay tuned to see how leading retailers are leveraging 麻豆原创鈥檚 data-driven approach to optimize their operations and stay ahead of the competition and learn more about .

Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience and Consumer Industries.

Plenty of people have started a business in their garage. Few have chosen the laundry room of their parents鈥� clothing and home textiles store. But that is exactly what Kurt Ernsting did in 1967 when he set up minipreis, a low-price fashion shop that would later become a household name throughout Germany. Today, with its award-winning online presence and some 1,925 stores in Germany, Austria, and the Netherlands, Ernsting鈥檚 family鈥攁s the fashion chain is now known鈥攊s one of western Europe鈥檚 largest omnichannel clothing retailers.

Cloud-based pricing process

鈥淏ecause we aim to create seamless shopping experiences for our customers, we鈥檝e already been following an omnichannel strategy for a while,鈥� explains Hans-J枚rg Blaeser, director of Technology & IT Services at Ernsting鈥檚 family. 鈥淭his is why ensuring uniform pricing across all sales channels was the next logical step for us鈥攏ot least because we were redesigning our online shop and needed a new pricing engine and campaign management tool anyway,鈥� adds Dennis Re脽mann, head of Software Engineering at the company.

The fashion retailer opted for a cloud-based omnichannel pricing solution. 鈥淭he cloud architecture allows you to manage price queries centrally across all channels, use intelligent mechanisms to fine-tune price promotions, and integrate new stores and touchpoints with ease,鈥� says Patrick Pierron from implementation partner CAS.

Two components, one award-winning solution

The solution at Ernsting鈥檚 family consists of two main components. One is the omnichannel pricing solution itself. This is based on , which helps ensure consistent and uniform pricing across all customer touchpoints, such as online shops, brick-and-mortar stores, and customer and 鈥渆ndless shelf鈥� apps, even when Internet connectivity breaks down.

鈥淲e operate a dense network of stores, so we are far from immune to this modern-day reality,鈥� says Nils B枚hmer, senior IT coordinator for Sales at Ernsting鈥檚 family. Lines can be damaged during construction work, routers can fail, and LTE coverage can be patchy, so there are a number of compelling reasons for having offline capabilities. Ernsting鈥檚 family therefore uses local PPS (promotion pricing service) boxes, which are offline derivatives of the cloud solution. 鈥淭hese PPS boxes synchronize regularly with the cloud-based omnichannel pricing solution,鈥� Pierron says. 鈥淭his means that stores always have the latest prices and can process sales even when the Internet is down.鈥�

The second component of the new omnichannel pricing solution is a reduction tool. Based on consenso鈥檚 price engine, this tool manages price reductions dynamically according to local conditions, sales figures, and inventories鈥攔ight down to individual store level. According to Philipp Borgmann, senior team lead for IT Merchandising, and Marcel Ruholl, managing partner at consenso, 鈥淭his pays off in two ways. First, the system-driven price proposals have a positive effect on the balance sheet. And second, fewer stock transfers mean a lower carbon footprint.鈥�

Seamless interaction

Another benefit of the Ernsting鈥檚 family solution is the way it seamlessly integrates the reduction tool, 麻豆原创 Omnichannel Promotion Pricing, and 麻豆原创 ERP. Price reductions calculated in the tool are automatically transferred to the central 麻豆原创 system and distributed in real time to all the stores and to the online shop through 麻豆原创 Omnichannel Promotion Pricing. 鈥淭his is the best possible foundation for dynamic, error-free, and hyper-personalized pricing in real time,鈥� says Philip Konitzer, head of Industry Division Retail in 麻豆原创 Customer Services & Delivery Germany. During the project, he and his team were on hand to answer questions about the functions and performance of the 麻豆原创 components.

Key elements of success

Despite being highly complex, the new omnichannel pricing solution went live quickly and without incident. The implementation partners who worked on the project attribute this largely to the company鈥檚 transparent and effective approach to change management. 鈥淎ll the stakeholders鈥攆rom operational and strategic teams to management鈥攚ere fully on board from the get-go,鈥� Pierron recalls. This made it possible to define all the relevant requirements during the preliminary study, compare them with the capabilities in the 麻豆原创 products, and identify the necessary adjustments at an early stage. Some of these were co-innovated with 麻豆原创 and incorporated into the standard 麻豆原创 Omnichannel Promotion Pricing solution; others were developed exclusively for Ernsting鈥檚 family in 麻豆原创 Business Technology Platform (麻豆原创 BTP).

鈥淭he way the project participants interacted was exemplary,鈥� says Ernsting鈥檚 family project lead Mark Dinkhoff, head of IT Projects. And the proof is there for all to see: the solution is stable and running smoothly in both the online shop and at the company鈥檚 more than 1,900 stores in Germany and Austria. As part of its international expansion strategy, Ernsting鈥檚 family opened six new stores in the Netherlands at the end of last year. The roll-out went smoothly there too, confirming that the company鈥檚 award-winning omnichannel pricing solution is not only technically robust, but suited to international markets as well. This is great motivation for Ernsting鈥檚 family to push ahead with its expansion plans.

This was first published on the German 麻豆原创 News Center.

From the customer鈥檚 side, this experience could affect the reliability of future purchases. It could make them think twice before shopping there again, especially if they already had concerns about the difficulties in completing transactions. From the company鈥檚 perspective, a website outage implies significant losses, such as direct revenue loss due to a main sales channel being shut down, and a loss of organizational trust, potentially driving customers to competitors.

In retail and e-commerce business, customer experience is paramount. A company whose e-commerce frequently experiences downtime could receive a negative market reaction from investors.

These experiences highlight the importance of robust support readiness programs, especially during holiday seasons when businesses strive for more sales and revenue through their digital platforms. With customer expectations at an all-time high, businesses need reliable, scalable, and innovative solutions to deliver exceptional shopping experiences. Proactive support measures can considerably reduce system failures during peak times, which not only reinforces customer satisfaction but also protects organizational trust and revenue. 麻豆原创’s holiday support readiness program is designed to address these needs. It offers a strategic, data-driven approach to help businesses thrive during peak periods.

The holiday support readiness program is a customer experience program by 麻豆原创 to help safeguard and establish strong support for digital commerce and retail customers during high shopping times. Key features of the program include:

• 鈥�Comprehensive coverage: It can cover events ranging from Singles Day in China and El Buen Fin in Mexico to Black Friday, Cyber Monday, Christmas, and New Year鈥檚.鈥�
• Extensive participation: Last year, 143 customers with 200 tenants used 麻豆原创鈥檚 holiday support readiness program to navigate the holiday rush successfully.鈥�
• Early preparation: Preparation begins 4鈥�6 months in advance, involving collaboration among customer support, cloud operations, and product engineering teams.鈥�

The focus on customer experience has increased due to the expansion of interfaces through which customers interact with companies. , 70% of respondents bought products or ordered services electronically in the preceding 12 months. For corporations, this online influx depicts a figure of more than . To approach these complexities, companies have steadily turned to advanced technologies such as artificial intelligence (AI) to strengthen their support systems.

In 2024, 麻豆原创 introduced a preventative care model under the transformation blueprint, aimed at delivering predictive, proactive, bi-directional support integrated with AI-driven insights and automation, allowing teams to predict potential problems and address them before they impact customers鈥攁nd potentially millions of users. 麻豆原创鈥檚 proprietary AI tools are deployed to help streamline support processes, enhance operational insights, and enable predictive and proactive engagement.

This represents a pioneering shift in the industry, positioning 麻豆原创 as a front-runner in AI-driven, predictive, and proactive support solutions.鈥疶he model provides a comprehensive, 360-degree customer support profile, helping to accelerate issue detection and anticipate potential problems, with AI-integrated features like a virtual support assistant, resource and鈥痺eb traffic predictions, a鈥痳ecommendation engine, case history analysis, issue correlation, and pattern recognition.

To operationalize this model, 麻豆原创 leverages collaboration approaches among product engineering teams, cloud operations鈥攄atabase administrators and technical operations managers鈥攖echnical support, and mission-critical teams to convey comprehensive case analysis reports and detailed recommendations and action plans for each customer. This can allow 麻豆原创 to identify and resolve future issues before customers are affected, helping to reinforce system stability during peak sales periods. For example, the proactive support process for the 2024 Black Friday and Cyber Monday sales events involved holistic health checks for over 143 customers鈥痑nd 200 production environments, setting a new standard in holiday readiness.

When aligned with the organizational strategy, a support program can foster a more positive customer journey, resulting in improved customer loyalty. “The holiday support readiness program isn’t just about managing the current peak; it’s about preparing for the next one. Our focus on preventative, AI-driven support means that our customers can focus on their business, not on system stability,” says Stefan Steinle, executive vice president and head of Customer Support & CLM at 麻豆原创.

For enterprises, joining the holiday support readiness program can also offer the following advantages:

• Minimize downtime: It helps ensure e-commerce platforms are ready when it matters most.鈥�
• Optimize performance: It uses AI and automation to help maintain peak system health and customer satisfaction.鈥�
• Stay ahead: Proactive monitoring and predictive support help keep organizations one step ahead of potential outcomes.鈥�

Looking forward, preparing for upcoming retail peak seasons cannot be overstated. 麻豆原创 Sapphire in 2025 will hold dedicated sessions to help ensure customers are well-equipped for these challenging periods. From live demos to expert interactions, attendees will be able to witness firsthand how 麻豆原创’s tools help keep businesses running smoothly and engage directly with solution experts.

Our commitment at 麻豆原创 Sapphire in 2025 is to equip customers with the knowledge and tools needed for uninterrupted success during every peak period. The holiday support readiness program is about turning challenges into opportunities for growth. With these resources, businesses will be better prepared to face uncertainties and use favorable circumstances in demanding times, ensuring sustained development and customer satisfaction.

Don’t wait until the next holiday season to find last-minute solutions. Be a part of the holiday support readiness program now and secure your business’s performance for future peak sales periods.