Complexity is not always the problem. Unmanaged, and often self-created, complexity is.

A practitioner’s perspective

Some years ago, after helping turn around a large global Â鶹ԭ´´ Customer Experience program, I was contacted by several customers asking a surprisingly simple question: what did you do differently?

My answer was a set of practical keys to success, which I refined through discussions and workshops with customers over the years. The pattern was remarkably consistent. Weak governance and pragmatic change management were recurring problems. But an even more fundamental issue appeared again and again: many organizations had invested in a solution without a sufficiently clear and shared understanding of what they wanted to achieve with it.

Once that first question is unclear, everything downstream becomes harder.

Start with the outcome, not the transformation

Transformation programs tend to generate activity very quickly.

Workstreams are created. Governance boards appear. Solution workshops are scheduled. Backlogs grow. Training plans are developed. New roles and responsibilities are defined.

All of that may be necessary. But before asking how to transform, organizations need to be able to answer a much simpler question: what are we actually trying to improve?

Is the ambition profitable growth? A fundamentally different customer experience? A new service or business model? Greater operational resilience? Better use of data across the enterprise? The ability to scale into new markets?

Without that shared value intent, different teams start optimizing different things. Business stakeholders describe desired outcomes, implementation teams focus on solution scope, and users are eventually trained on functionality without always understanding what should change in their daily work. The result can be a very busy transformation program with surprisingly little transformation.

Keep the business, solution, and people connected

Over time, I started using a simple model to explain this: the transformation triangle.

A transformation needs three perspectives to stay connected:

• Business: Why are we changing? What outcomes, value drivers, processes, and measures matter?
• Solution: What capabilities, technology, integrations, data, and implementation choices are needed?
• People: Who needs to work differently, what support do they need, and how will adoption be sustained?

None of these works well in isolation. A technically excellent solution with weak business alignment becomes an expensive implementation. A strong strategy without a workable solution remains a presentation. And a well-designed process that people do not understand or adopt remains, at best, another PowerPoint slide.

This thinking later became part of the Cloud Mindset Workshop, available to order in the Advanced Success Plan version for Â鶹ԭ´´ Customer Experience solutions. The workshop helps translate the business, solution, and people perspectives into practical topics covering business outcomes, governance, processes, rollout, change management, enablement, and adoption.

A skills gap is not always a training gap

This also changes how we should think about skills gaps.

The immediate reaction is often to provide more training or bring in more technical specialists. Sometimes that is exactly what is needed, but many transformation gaps are broader capability gaps.

A project may have excellent product experts but still struggle because nobody can translate business objectives into process priorities. A strong implementation team may still fail if decision rights are unclear. End users may know how to navigate a solution but not understand why their role has changed.

Skills therefore span all three sides of the triangle: business judgement, process knowledge, product expertise, data and integration capability, governance, change leadership, and adoption.

The objective should not be to create experts in everything. It should be to make sure the organization has the right capabilities at the right moment, and that those capabilities work together.

Governance should reduce complexity, not add to it

Governance is another area where organizations can accidentally create more complexity than they remove.

Good governance does not mean more meetings, more steering committees, or larger RACI matrices. It should make a few things very clear: Who decides? What needs to be decided? Based on which outcomes and measures? How are dependencies and risks escalated? And when should the plan change?

Governance needs to come early because execution becomes difficult when ownership, priorities, and decision-making remain ambiguous. The purpose of transformation governance is not to manage complexity for its own sake. The purpose is to make complexity manageable.

Autonomous CX raises the stakes

AI and autonomous capabilities add another dimension.

Autonomous CX can increasingly use AI agents across Â鶹ԭ´´ Sales Cloud, Â鶹ԭ´´ Service Cloud, Â鶹ԭ´´ Commerce Cloud, and Â鶹ԭ´´ Engagement Cloud to help interpret context, recommend actions, and execute parts of customer-facing processes.

That can remove effort and accelerate execution. But, increasing autonomy does not remove the need for business clarity, governance, process alignment, or people enablement. It increases it. This is also why AI initiatives need to stay connected to business outcomes, process design, governance, and adoption. The more autonomous the technology becomes, the less ambiguity the organization can afford. An AI agent can execute a process faster. It cannot decide what the organization should value, resolve unclear ownership, repair a broken operating model, or create trust by itself.

Most transformation challenges can be traced to a few recurring themes.

Organizations struggle to maintain alignment on outcomes, connect strategy with execution, close the right capability and adoption gaps, and establish governance that supports decisions rather than slowing them down.

The Advanced Success Plan for Â鶹ԭ´´ Customer Experience solutions can help address these challenges in a structured way. The Cloud Mindset Workshop can provide a holistic overview of the key dimensions of transformation across business, solution, and people, using practical concepts and customer examples to help teams reflect on their own approach. From there, more focused expert-led services can go deeper where needed.

Clarify the value intent

Use value management, for example through the value management expert session, to align business stakeholders on outcomes, value drivers, and meaningful measures.

Understand the operating reality

Examine end-to-end processes, ownership, dependencies, and the capabilities required to deliver the intended outcomes. Services such as business process best practices can help teams assess and improve the way processes are designed and executed.

Close the relevant capability and adoption gaps

Bring in targeted expertise where it is needed. This can include services such as the time to value accelerator, technical expert services, AI-focused guidance to identify and apply relevant use cases, and focused support for organizational change and adoption to close both capability and adoption gaps.

Govern and adapt

Use the engagement plan and recurring checkpoints to review progress, make decisions, and adjust priorities as the transformation evolves.

Transformation will never become simple. But it can become understandable, governable, and executable. And in our experience, that is usually where success starts.

Raf Dille is product manager for the Advanced Success Plan for Â鶹ԭ´´ Customer Experience.
Tara Tracey is global product owner for the Advanced Success Plan for Â鶹ԭ´´ Customer Experience.

Service-led growth is one of the seven macro trends within Autonomous CX, Â鶹ԭ´´’s vision introduced at Â鶹ԭ´´ Sapphire in 2026. At its core is a simple principle: every customer promise must be backed by the operational reality needed to deliver it.

highlights a growing gap between customer expectations and the operational reality of service delivery. Disconnected handoffs, fragmented information, and pressure to adopt AI make service a business-model question, not just a technology one.

A practitioner’s perspective

More than twenty years ago, I was part of a global service organization that wanted to move beyond viewing service as a cost of doing business.

At the time, our primary objective was cost recovery. Service was necessary to support the product business, but it was not really seen as a business in its own right.

We started changing that by introducing new professional services and finding ways to monetize expertise we already had. Remote device monitoring, for example, allowed us to organize support across time zones and offer profitable after-hours services to customers who depended on continuous operations.

A few years later, I was asked a more fundamental question: could the service organization survive as an independent business?

To explore that question, we used an early version of what later became widely known as the business model canvas. We looked beyond service operations and examined the complete picture: our value proposition, customer segments, channels, activities, resources, costs, and revenue streams.

Looking back, that exercise taught me something that is still relevant today.

Service as a revenue driver is not a new idea. And it does not start with technology. It starts with a business model.

What do we mean by service-led revenue?

“Service as a revenue driver” is often used as if it means one thing. In reality, service can contribute to revenue in several different ways.

First, it can protect revenue. A customer whose issue is resolved quickly and professionally is more likely to renew, continue buying, and remain loyal.

Second, it can influence revenue. Service professionals often understand a customer’s operational reality better than anyone else. They may identify a need for additional services, training, upgrades, or new solutions, creating opportunities for commercial teams.

Third, it can generate revenue directly through premium support, professional services, subscriptions, remote monitoring, advisory services, or outcome-based offerings.

These ambitions are related, but they are not the same. Each requires different processes, skills, measures, and sometimes different operating models.

Not every service interaction should become a sales conversation. But every service organization should understand whether it is expected to protect, influence, or directly generate revenue.

Technology creates possibilities, not the business model

Technology has always played an important role in service innovation.

Remote monitoring reduced the need for on-site visits. Connected solutions made global support models possible. Customer and service platforms improved access to account, contract, equipment, and interaction data.

Today, Autonomous CX capabilities can expand these possibilities even further. Joule, embedded AI agents in Â鶹ԭ´´ Service Cloud, and AI-assisted opportunity detection in Â鶹ԭ´´ Sales Cloud can classify and route cases, summarize interactions, surface relevant knowledge, identify patterns, detect revenue opportunities, and increasingly automate routine requests. All within the context of a connected service and sales operating model.

Yet adoption does not equal usage, and usage does not equal value. Technology does not answer the most important questions:

• What value are customers willing to pay for?
• Which customers should we serve?
• How will the service be sold, delivered, and measured?
• Can it be delivered consistently, profitably, and adopted by employees and customers?

Customers are already drawing their own conclusions. In 2026, believe AI in service is deployed primarily to save money, not to improve service. Seventy-nine percent still strongly prefer human support. These perceptions are not only a trust problem, they point to a business model problem. When the technology decision precedes the value decision, customers notice.

From ambition to execution

This is where many service-led growth initiatives struggle.

Ambition may be clear in the boardroom, while the organization underneath continues to operate as before. Service is still measured primarily on cost and case closure. Sales and service pursue different objectives. Customer information remains fragmented. Opportunities identified by service disappear during handovers. Employees are expected to adopt new behaviors without understanding why.

Turning service into a measurable revenue driver therefore requires more than enabling a new feature or deploying a new technology. It requires alignment between business objectives, processes, people, data, and technology.

The Advanced Success Plan version for Â鶹ԭ´´ Customer Experience solutions is an expert-led engagement model that helps translate Autonomous CX into an executable plan. It does not replace business strategy or determine which services should be brought to market. Instead, it helps connect a chosen ambition to the processes, capabilities, and governance needed to make service-led growth measurable and repeatable.

1. Clarify the value intent

The first step is to define what service-led growth actually means for the organization.

Is the priority to improve retention? Increase renewals? Create opportunities through service interactions? Launch paid services? Improve profitability?

Through the value management expert session within the Advanced Success Plan for Â鶹ԭ´´ Customer Experience solutions, stakeholders can align on business priorities, value drivers, and success measures.

The objective is not to create a long list of KPIs, but a shared understanding of the outcomes that matter most.

2. Connect the end-to-end process

Once the ambition is clear, the next question is how value will actually be created.

If a service professional identifies an opportunity, what happens next? Who owns the follow-up? Is the customer experience consistent from the initial interaction through fulfilment and invoicing?

Business process best practices and expert guidance can help identify gaps in ownership, handovers, and process alignment across service, sales, commerce, and supporting operations.

This matters beyond operational efficiency. shows that 45% of revenue leaders cite improving collaboration and handoffs across marketing, sales, and service as a current priority, and 39% are actively pursuing expansion, cross-selling, and upselling within existing accounts. Service teams often have valuable customer context, but the real question is whether the process exists to act on it.

3. Close capability and adoption gaps

Organizations can then assess which capabilities are needed to support the process. This could involve better access to customer information, improved knowledge management, analytics, automation, AI-supported recommendations, or opportunity management capabilities. Targeted expert services within the Advanced Success Plan for Â鶹ԭ´´ Customer Experience solutions help connect Â鶹ԭ´´ CX capabilities to desired business outcomes.

At the same time, employees need the right enablement, incentives, and confidence to adopt new ways of working. Without that, even the best-designed process remains a PowerPoint slide.

The cost of getting this wrong is real. Employees asked to adopt new behaviors without understanding why, or without the tools to support them, do not persist. When experienced people leave, they take institutional knowledge and customer relationships with them. Enablement is not a training exercise; it is a retention and continuity investment.

4. Measure, learn, and improve

Service-led growth is not delivered through a single project.

highlights several recurring priorities for service leaders: efficiency and time to resolution (48%), collaboration and handoffs across marketing, sales, and service (46%), first-contact resolution (40%), and AI-driven predictive insights (33%). These figures provide useful context, but the measures that matter for service-led growth depend on the value intent defined at the start. Progress should therefore be tracked against the agreed outcomes, whether these involve retention, renewals, service-generated opportunities, paid-service revenue, or profitability.

Ongoing governance and engagement planning helps organizations review progress, address gaps, and scale successful approaches over time.

Service-led growth is a business-model choice

Moving from cost recovery to service-led growth is not simply a matter of asking service employees to sell more. It is a business-model choice with implications for the value proposition, customer experience, processes, organization, skills, technology, and measures of success.

Twenty years ago, remote monitoring changed what service organizations could deliver. Today, AI is expanding those possibilities again. But the underlying challenge has not changed. Technology changes possibilities. Business models determine how that value is captured.

First, decide where service should create value. Then, build the operating model required to deliver that value consistently and profitably.

The Advanced Success Plan for Â鶹ԭ´´ Customer Experience solutions can support that journey by helping organizations connect business outcomes with the processes, capabilities, adoption, and governance needed to turn ambition into measurable results.

Raf Dille is product manager for the Advanced Success Plan for Â鶹ԭ´´ Customer Experience.
Tara Tracey is global product owner for the Advanced Success Plan for Â鶹ԭ´´ Customer Experience.

To meet these expectations, organizations must move beyond siloed commerce channels toward a connected autonomous CX model that integrates commerce, order sourcing, fulfilment, and customer support across the full customer journey.

The Advanced Success Plan for Â鶹ԭ´´ Customer Experience supports this shift by accelerating omnichannel capability build-out through outcome-based governance. It helps organizations move from fragmented execution to coordinated operations—enabling consistent cross-channel experiences, aligning commerce with sales and service execution, and improving conversion and repeat purchase through end-to-end alignment.

Reality of B2B buying

B2B buying is rarely linear anymore. Buyers often switch between digital channels, sales teams, and service touchpoints before deciding. Research from McKinsey’s B2B Pulse highlights that buyers typically engage across multiple interaction channels before making a decision.**

This reflects how digital commerce has become a core part of the buying process, with 58% of global B2B retailers selling on at least three e-commerce platforms.†

At the same time, expectations have shifted. Consistency across channels is assumed, digital self-service is often the starting point, and speed and transparency are baseline requirements.

That creates a dual challenge for organizations: improving customer experience while also managing increasing operational complexity behind the scenes.

Convergence of commerce, sales, and service

B2B environments combine complex operations with tightly connected customer journeys. Organizations must manage customer-specific pricing and contracts, large and dynamic product catalogs, multi-step approvals, distributed fulfilment models, and integrations across commerce, ERP, sales, and service systems. Customers, however, do not see this complexity. They experience a single journey, from discovery to purchase, fulfilment, and support, and expect it to feel seamless.

A typical journey may include discovering products online, aligning pricing with sales, placing orders through self-service channels, and resolving issues via service interactions. Expectations for real-time visibility, fast issue resolution, and consistent engagement continue to rise, as highlighted in research such as DHL’s B2B E-Commerce Trends. The same DHL report also shows that 78% of B2B retailers expect website sales to grow over the next three to five years, which reinforces how central digital channels have become.†

Yet many organizations still operate in silos. The result is often inconsistent data, limited visibility across interactions, slower issue resolution, and disconnected customer experiences. This is why omnichannel transformation is not about adding channels, but about connecting commerce, sales, and service into a unified operating flow.

Process excellence as a foundation

As complexity increases, end-to-end process alignment becomes critical. Customers experience outcomes, not systems, and those outcomes depend on how well processes are connected across commerce, sales, service, and fulfilment.

Breakdowns typically occur when sales agreements are not reflected in commerce systems, fulfilment is not aligned with order promises, service teams lack customer context, or data differs across channels. These are not isolated system issues, but symptoms of disconnected processes.

In practice, that can mean a customer sees one price in the portal, a different one in the quote, and another one in the order confirmation. It can also mean service teams have to ask customers to repeat information that already exists elsewhere in the organization. Even when the underlying technology is in place, the experience still feels broken if the process is not connected.

Organizations that invest in process excellence are better positioned to deliver consistent experiences, reduce friction, improve operational efficiency, and scale complex B2B models. Process alignment also makes it easier to respond to change, because teams can adapt faster when the underlying journey is not held together by disconnected handoffs.

Why omnichannel matters

Omnichannel in B2B is not just about offering more ways to buy. It is about making those ways work together. When the customer starts on one channel and finishes on another, the handoff needs to feel natural. If not, the customer experience becomes fragmented very quickly.

That matters because B2B buyers are increasingly comparing their business purchasing experience to the consumer experiences they already know. They expect simple navigation, transparent pricing, reliable order updates, and a service team that understands the full context of the account. In other words, they want the convenience of digital commerce without losing the support and complexity that B2B purchasing often requires.

This is also where many companies struggle. They may have a strong storefront, but weak back-end coordination. Or they may have good sales support, but poor visibility once the order has been placed. Omnichannel transformation closes that gap by connecting the customer-facing experience with the operational processes behind it.

Accelerating outcomes with the Advanced Success Plan for Â鶹ԭ´´ Customer Experience

The Advanced Success Plan for Â鶹ԭ´´ Customer Experience helps organizations accelerate omnichannel capability build-out through outcome-based governance and alignment between strategy and execution.

Rather than focusing only on implementation, the emphasis is on measurable outcomes across the full customer journey. This includes enabling consistent omnichannel experiences, aligning Â鶹ԭ´´ Commerce Cloud, Â鶹ԭ´´ Sales and Service Cloud, and fulfilment processes, managing catalog and contract complexity at scale, improving order sourcing and fulfilment coordination, and strengthening end-to-end process alignment.

The goal is to ensure all capabilities operate as one connected system rather than separate functions.

That becomes especially important in B2B environments where a single transaction can involve multiple stakeholders, custom pricing rules, approval steps, and several systems working together at once. Without clear governance and alignment, even well-designed digital tools can create confusion instead of clarity.

With the right operating model, however, organizations can turn complexity into a strength. They can reduce friction for customers, improve efficiency internally, and create a more reliable buying experience across every channel.

The Advanced Success Plan for Â鶹ԭ´´ Customer Experience includes access to Business Process Best Practices which helps customers understand the end-to-end process flow and best practices for executing business processes across Â鶹ԭ´´ Sales and Service. This service showcases reference processes and bridges the gaps that can occur during rapid implementations of solutions in complex landscapes or when implementation of multiple solutions creates fragmented processes without taking into consideration unique end-to-end view.

Conclusion

Omnichannel commerce and B2B digital transformation are reshaping how organizations engage customers and deliver value. Success depends on connecting commerce, sales, service, and fulfilment into a unified operating model supported by strong end-to-end processes.

Organizations that focus on process excellence and outcome-based governance are better positioned to scale effectively and meet rising customer expectations. The Advanced Success Plan for Â鶹ԭ´´ Customer Experience enables this by connecting strategy to execution and supporting consistent outcomes across the customer journey.

For B2B companies, the real shift is not just digital adoption. It is building a model where channels, processes, and teams work together in a way that feels simple to the customer, even when the operation behind it is complex.

Nikola Stojanovski is a product manager for the Advanced Success Plan for Â鶹ԭ´´ Customer Experience.
Tara Tracey is global product owner for the Advanced Success Plan for Â鶹ԭ´´ Customer Experience.

*Digital Commerce 360, 2025
**McKinsey, 2021
†DHL, 2025

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 Â鶹ԭ´´ 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 Â鶹ԭ´´ Customer Experience covers available out-of-the-box integrations, common usage scenarios, and pitfalls and how to avoid them—all delivered in a live remote session by an Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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—they have better judgment about how to use it.

The Advanced Success Plan for Â鶹ԭ´´ 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 Â鶹ԭ´´ Customer Experience.
Ella De Torres, product manager for the Advanced Success Plan for Â鶹ԭ´´ Customer Experience.

The Advanced Success Plan version for Â鶹ԭ´´ Customer Experience solutions is designed precisely for this moment. It offers utilities customers a structured, continuously guided approach to maximizing value from Â鶹ԭ´´ Customer Experience (Â鶹ԭ´´ 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 Â鶹ԭ´´ CX portfolio can support compliance when features are correctly activated and configured.

Â鶹ԭ´´ in utilities: a significant and growing market

Utilities are not a niche segment for Â鶹ԭ´´. Understanding the scale of the Â鶹ԭ´´ utilities community frames why the Advanced Success Plan for Â鶹ԭ´´ Customer Experience solutions matters for this industry in particular. Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ CX portfolio can address these challenges across the full customer lifecycle. Â鶹ԭ´´ Engagement Cloud enables targeted, segmented communications. Â鶹ԭ´´ Service Cloud can centralize complaint management and agent interactions. Â鶹ԭ´´ Sales Cloud helps manage accounts, contacts, leads, and opportunities. Â鶹ԭ´´ Commerce Cloud is the 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ Sales Cloud, Â鶹ԭ´´ Service Cloud, Â鶹ԭ´´ Marketing Cloud, and Â鶹ԭ´´ 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—and how each one helps

The Advanced Success Plan for Â鶹ԭ´´ 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 Â鶹ԭ´´ Service Cloud to segmented communications in Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ Service Cloud. Many autonomous agents or assistants announced at Â鶹ԭ´´ 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 Â鶹ԭ´´ Customer Experience solutions can drive meaningful business value, especially for organizations without deep technical or functional Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ CX adoption looks like in practice

When utilities customers engage with the full Advanced Success Plan for Â鶹ԭ´´ Customer experience solutions at the right moments, the outcomes can be concrete and measurable:

• Adoption confidence: Teams understand the Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ Service Cloud and Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ investment in the utilities sector is substantial and well-established. Utilities organizations around the world have already deployed the Â鶹ԭ´´ 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 Â鶹ԭ´´ CX investment.

The Advanced Success Plan for Â鶹ԭ´´ 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 Â鶹ԭ´´ Customer Experience.
Tara Tracey is global product owner for the Advanced Success Plan for Â鶹ԭ´´ Customer Experience.

For many Â鶹ԭ´´ Commerce Cloud and Â鶹ԭ´´ 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 is where AI translates those signals into action—the 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 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ Commerce Cloud

Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ Engagement Cloud

Â鶹ԭ´´ Engagement Cloud, powered by Â鶹ԭ´´ Emarsys, can extend personalization beyond the storefront and into the full lifecycle of the customer relationship. This is where Â鶹ԭ´´ 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—independently of time zone, language, or region—and 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 Â鶹ԭ´´ Emarsys, AI-assisted campaign translator capability and omnichannel orchestration, Â鶹ԭ´´ 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 Â鶹ԭ´´ Commerce Cloud and Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ Customer Experience.
Tara Tracey is global product owner for the Advanced Success Plan for Â鶹ԭ´´ 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’t 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.

Â鶹ԭ´´ delivers an ecosystem that can provide the tools needed to meet these expectations. Using Â鶹ԭ´´ 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 Â鶹ԭ´´ Commerce Cloud

Intelligent selling services for Â鶹ԭ´´ 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 Â鶹ԭ´´ Commerce solution is an industry-specific solution designed to enable travel companies to deliver omnichannel digital traveler engagement through Â鶹ԭ´´ Commerce Cloud. For customers that already have an existing Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ Sales Cloud, Â鶹ԭ´´ Service Cloud, and Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´.
Geoffrey Arado is product manager for Â鶹ԭ´´ Customer Experience.

The version for , part of the Â鶹ԭ´´ Services and Support portfolio, is the helping organizations adopt, activate, and scale the Â鶹ԭ´´ Customer Experience and AI innovations announced at Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ 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 Â鶹ԭ´´ Customer Experience helps operationalize seven macro trends shaping modern customer experience.

1. AI‑powered 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‑impact starting points, a plan to scale with guardrails, accelerating time from pilot to production and grounding every decision in Â鶹ԭ´´â€™s CX AI capabilities and product road map.

2. Hyper‑personalization at scale

Personalization demands more than algorithms; it requires clean, consent‑aware 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‑of‑truth 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‑out by uniting commerce, order sourcing, pricing, and fulfilment patterns, supported by outcome‑based 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‑to‑revenue contribution, and ensure the data foundation supports them.

6. Service as a revenue driver

Service is no longer a cost center; it’s a growth channel. We guide users to productize services, monetize value‑added offerings, and embed outcome‑based contracts. The plan includes:

• Playbooks for cross‑sell/upsell from service interactions
• Knowledge and field service patterns to improve first‑time fix and attach rates, KPI frameworks for service‑led growth

The result: With prescriptive governance and AI‑driven intelligence, service organizations move from reactive cost management to consistent, measurable contribution to top‑line 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‑based 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 Â鶹ԭ´´ 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. 
• 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 Â鶹ԭ´´ Customer Experience translates CX strategy into repeatable execution and measurable business outcomes.

Tara Tracey is a global product owner at Â鶹ԭ´´.