What High-Maturity Brands Do Differently: 5 Lessons in Customer Engagement

The other day, I got an ad from a brand in a genuinely seamless and relevant way. My first thought was, “How did they know exactly what I needed?”

And as a marketer myself, I know those experiences don’t happen by accident. Behind every memorable customer engagement touchpoint is an organization that has made a deliberate, sustained commitment to building what the most forward-thinking CX teams are now calling Autonomous: where data, AI, and connected systems work together continuously across marketing, sales, service, and commerce.

What the data tells us

In an autonomous CX model, the right action happens at the right moment without friction or delay. Brands that operate this way have a fundamentally different approach, where people set the direction, and AI executes.

An SAP global study of 4,800 senior decision-makers reveals that a select group of brands are already living this vision, and their results prove it’s worth studying. Below, I’ll share the concept behind the SAP Engagement Maturity Index and include lessons that the most mature brands do differently to stand out and amplify their impact.

What do high-maturity brands do differently in customer engagement?

High-maturity brands differentiate themselves by unifying customer data, embedding artificial intelligence into their daily workflows, and aligning teams across marketing, sales, service, and technology. They move quickly from strategy to full execution and consistently outperform their peers in customer retention, revenue growth, and overall engagement outcomes, even though only about 21% of brands have reached this level of maturity.

How are leading brands using AI in customer engagement?

Leading brands embed AI into their operations rather than treating it as a set of isolated tools. These brands are integrating AI into workflows such as real-time decisioning, content generation, customer journey analytics, and churn prediction. About 81% of high-maturity brands have operationalized AI in this way, ensuring it is connected to real business data and governed by clear guardrails to drive measurable impact.

What is an autonomous CX strategy, and why does it matter?

An autonomous customer experience strategy refers to an operating model where unified data, embedded artificial intelligence, and cross-functional alignment work together to deliver the right action at the right moment without friction or delay. This approach matters because it enables brands to scale personalized, real-time engagement across the entire customer journey and represents the future state that high-maturity organizations are building toward.

Why are most companies stuck in the middle of customer engagement maturity?

Most companies remain in the developing stage of customer engagement maturity because their data is siloed, their technology is only partially integrated, and their execution is fragmented across teams. While many organizations understand what effective engagement looks like, they struggle to operationalize it at scale, which leaves approximately 63% of brands stuck between strategy and consistent delivery.

What business results do high-maturity customer engagement strategies deliver?

High-maturity customer engagement strategies deliver measurable business results, including increased customer lifetime value, stronger retention, greater customer advocacy, and improved return on investment. For example, 86% of mature brands report growth in customer lifetime value. These results demonstrate how sustained investments in data, AI, and organizational alignment translate into long-term competitive advantage.

Before diving into what the best brands do differently, it’s worth understanding how maturity is measured and where most organizations actually sit today.

The SAP Engagement Maturity Index evaluates how well brands align people, processes, and technology to deliver cohesive, intelligent customer experiences. This index scores organizations across six key dimensions:

• AI and marketing automation
• connected data strategy
• omnichannel engagement
• real-time personalization
• customer loyalty
• email marketing

The result is a Customer Engagement Maturity (CEM) score that places brands into one of three tiers:

Low CEM Score: Emerging (16% of brands)

Organizations at this stage have minimal adoption of enterprise-wide customer engagement technologies and strategies. Data remains siloed across business functions, making it difficult for teams across marketing, sales, service, and operations to access shared insights or respond in real time. Limited integration and low AI readiness hinder consistent experiences and long-term loyalty. For these brands, engagement is largely reactive, and the gap to the top is significant.

Moderate CEM Score: Developing (63% of brands)

The largest group by far, these brands have moderate adoption of customer engagement technologies and cross-functional strategies. Teams can access portions of shared data and deliver basic personalization, but coordination across marketing, sales, service, commerce, and product teams remains uneven. Experiences often feel disconnected, forcing brands to rely on short-term tactics rather than building deeper relationships. This is where most organizations are stuck. But that also means this is where the greatest opportunity for transformation exists.

High CEM Score: Established (21% of brands)

The top tier is where established brands have advanced adoption of integrated engagement technologies and enterprise-wide strategies. They connect data and intelligence across all functions—marketing, service, sales, commerce, and operations—to adapt quickly and anticipate customer needs. They use AI and automation to deliver personalized, omnichannel engagement in real time, at a global scale. Critically, maturity has improved year on year, but this group remains rare! This group sends a clear signal that achieving true high-maturity engagement requires something most organizations haven’t yet built: better-connected systems, real-time data, and AI-driven orchestration across the entire business.

63% of brands are stuck in the middle tier

This means most brands know what good looks like but are not yet connected enough to deliver it consistently. The shift from Developing to Established requires brands to build (or rebuild) the foundation that makes their customer data even more powerful. The sections below explore exactly how the brands that have made that leap are doing it.

Data is the foundation for becoming truly autonomous, and high-maturity brands have built that foundation intentionally. 86% of Established brands say they can connect and combine data across every channel and customer touchpoint, and 84% can connect and use data from other teams and systems spanning sales, service, commerce, and ERP.

High-mature brands can also move more quickly, with 50% of mature brands able to access and use data in real time. They’ve also moved decisively away from third-party data dependency: only 60% of Established brands say their marketing still relies on third-party data, and 83% have a clearly defined first-party data strategy in place.

What this means for you:

The vision of an autonomous enterprise starts and ends with data. AI agents can’t make smart decisions, campaign assistants can’t personalize at scale, and cross-functional teams can’t coordinate effectively without a single, unified view of the customer grounded in real business truth. Too many organizations still treat data as a departmental asset rather than a company-wide resource. Until that approach changes and data flows freely across CRM, ERP, marketing, and service in real time, the promise of an autonomous future will remain out of reach. The brands that crack this first are excelling in marketing because they’ve built the infrastructure that makes everything else possible.

High-maturity brands have access to better AI tools, but their real winning strategy is weaving AI into the fabric of how their organizations actually run. Their adoption is both broad and intentional:

AI use cases in practice

These brands are applying AI across a wide and sophisticated range of use cases, including:

• real-time decisioning (38%)
• automated content generation (39%)
• predictive churn modeling (34%)
• customer journey analytics (35%)

Critically, their AI isn’t operating in isolation. Instead, they ensure that AI is grounded in full business truth: connected to ERP data, CRM records, service history, and commerce behavior and governed by clear human oversight. In this scenario, AI assistants and agents that can run entire workflows across the customer journey, from campaign creation to deal qualification to case resolution, all without losing the human direction that keeps it purposeful.

What this means for you:

The disconnect between the brands generating real returns from AI and those still running disconnected pilots comes down to one thing: a strong data foundation. Established brands have built the connected data infrastructure and organizational workflows that make AI genuinely effective. They understand that an assistant grounded in real customer data delivers something fundamentally different from a standalone AI tool generating generic content. You’ll win your brand’s race to an autonomous enterprise by building the right foundation first.

Most brands build their strategies to deliver connected, personalized, omnichannel experiences. The real measure of success comes down to execution and output. Established brands have decisively figured out how to ensure their engagement strategies come to life in an impactful way.

Across every major engagement area, mature brands have moved from intent to full implementation:

These brands have focused on optimization rather than just implementation. 79% of Established brands also acknowledge they will need to significantly transform their engagement approach in 2026; not because they’re behind, but because they’re already thinking about what comes next.

What this means for you:

This is possibly one of the most interesting findings in the entire study. The conversation in most boardrooms is still about what to implement. And the real competitive question is: how fast? The path to building an autonomous enterprise is a comprehensive transformation project that is an accumulation of implemented capabilities, each one building on the last. Mature brands committed early, iterated often, and built organizational momentum around execution. For brands still in the planning phase, the message is urgent: every quarter spent in strategy is a quarter your competitors spend in market embedding agents, activating AI, and compounding their advantage.

High-maturity brands have built the internal scaffolding that makes autonomous sustainable. Coordination is the backbone of their success: 89-90% of Established brands report coordinated engagement efforts across every function, including Marketing, Sales, Service, and Technology.

That coordination is the result of deliberate infrastructure investment across every cross-functional pairing:

From alignment to measurable impact

And 46% of Established brands have already implemented shared enterprise engagement KPIs across functions, with 44% having fully integrated their marketing, CX, and ERP approach. When full engagement is achieved across the organization, mature brands are most likely to report improvements in operational efficiency (32%), customer trust (32%), customer retention (31%), and revenue growth (32%).

What this means for you:

An autonomous enterprise can’t run on siloed teams any more than it can run on siloed data. The brands furthest ahead have made a critical realization: when your CRM, ERP, marketing, and service platforms share data and speak the same language, AI-driven agents and real-time personalization become possible at enterprise scale. When they don’t, even the best technology hits a ceiling. This emphasizes the importance of marketers leading the charge to bring people together and break down organizational silos, connecting CX workflows across the entire enterprise. Engagement maturity is an organizational achievement first, and a technology achievement second.

All of the above compounds into something that matters most: results. Established brands are outperforming on every engagement outcome measured, and the margins are significant:

The CLV finding is particularly striking: 86% of Established brands say their customer lifetime value has increased. That level of impact is the commercial dividend of years of sustained, compounding investments in doing the fundamentals right.

What this means for you:

The autonomous enterprise vision ultimately creates businesses that are measurably stronger, more resilient, and more deeply connected to their customers. CLV, retention, advocacy, ROI: these are the metrics that board-level decisions are made on, and mature brands are winning on all of them. Organizations that embody customer engagement excellence ground every customer interaction in full business truth, run their CX stack with AI-powered intelligence, and break down the silos that slow everything down. They’re building a fundamentally different kind of business, and the advantage they’re creating compounds with every passing quarter.

Customer engagement in 2026 is unfolding like a high-stakes race, and the leaders have already pulled ahead.

High-maturity brands are moving with speed and precision because they’ve built the systems, alignment, and intelligence to sustain momentum. Their investments in connected data, embedded AI, disciplined execution, and organizational alignment are now fueling continuous acceleration.

Across the rest of the field, many organizations are still progressing, but without the same consistency or coordination. Movement is happening slowly and without the compounding effect that defines the leaders.

Only 21% of brands have reached true engagement maturity, and their lead continues to grow as every interaction, insight, and automated decision builds on the last.

This is how advantage scales. Each improvement strengthens the next. Each capability unlocks more value. Over time, the distance becomes harder to close.

The race is active, and every organization is already on the track. What matters now is how effectively you build speed, remove friction, and sustain forward motion.

The path is visible. The front-runners have set the pace. Now the outcome depends on how quickly and intentionally you can match the pace. And perhaps, how far you’re willing to push beyond it.

These five themes tell a portion of the story. Download the full SAP Global Engagement Index to explore the complete findings, including where brands are investing in 2026, the biggest barriers holding organizations back, and what it truly takes to build the connected, AI-powered engagement engine across the enterprise.