Customer analytics is a priority. So why is execution still inconsistent?

Across financial institutions, restaurants and retailers, customer analytics is a top focus — 94% to 97% say it matters, and 70% are actively improving it. Yet translating investment into consistent, high-impact decision-making remains a critical sticking point.

That takeaway comes through clearly in Mastercard’s The state of business experimentation 2026, a white paper drawing from more than 100 industry leaders who use Mastercard Test & Learn®. The research reveals a complex picture: Many brands still conduct fewer than half of analyses at the customer level, and only about one in five always use segmentation or testing to guide rollout decisions. 

At first glance, it looks like a failure to execute. But it may be more useful — and more revealing — to also see it as a signal of maturity. Organizations are not short on ambition. They are ready for the next leap in customer analytics maturity, and the execution gap may be what stands between them and the other side.

Based on what we’re seeing in the market, underperformance is likely just part of the puzzle.

For one, today’s customer environment is infinitely more complicated. Meaningful outcomes hinge on delivering the right message, at the right time, through different channels and contexts. Now that signals span more touchpoints than ever before — and privacy expectations are on the rise — distilling that complexity into informed decision-making is all the more challenging. 

That is exactly why execution is harder. As signal volume grows, so do the operational requirements around identity resolution, software integration, governance, shared metrics and decision workflows. In other words, the issue is no longer whether organizations are prioritizing customer analytics. It’s whether they can build an operating model that connects every data insight to a larger vision that extends across systems, teams and policies.

Financial institutions, restaurants and retailers are not at the starting line. They are deep in the work. They are unearthing richer customer signals, combining first-party data with third-party sources to understand patterns across more fragmented journeys — a fact borne out by our own research. And across all three sectors, brands are leveraging customer-level analysis, segmentation and testing at least some of the time.

These are signs of organizations building a more holistic understanding of their customers in ways that were once thought impossible. But more data insights don’t automatically lead to better decision-making.  

Businesses are ready for the next step; they just need help removing operational bottlenecks hindering consistency, efficiency and scale. To close that gap, teams should focus on four operational enablers: 

• Automation: Less than half of businesses use AI-driven personalization to improve relevance, and just two-thirds use predictive analytics to inform decisions. These capabilities help brands understand what drives results in real time, empowering them to respond and adapt swiftly.  
• Customer segmentation: For scale, segmentation depends on a repeatable process for building, refreshing and activating audiences. That means moving from one-off analyses to always-on audiences. 
• Data integration: Brands must identify siloed sources of data insights and unify them under a single customer view.  
• Efficiency: Winners should be running tests with less manual effort, so business experimentation can more easily become the default workflow.

Closing the execution gap requires brands to unblock these enablers — and doubling down on business experimentation is the best way to accomplish that.

If this pattern feels familiar, the next move is removing the friction that keeps their customer analytics strategy from informing better decision-making under pressure. 

Whether it's creating a more usable customer view, embedding insights into workflows so teams can act on them in time, enhancing segmentation or making test-and-learn approaches easier to execute, the solutions are already within reach — businesses just have to take the leap.

Leaders: The execution gap is a sign, not a setback. When ambition is already in place, the real opportunity is to remove the bottlenecks that keep insight from becoming action at scale.

For deeper benchmarks across financial institutions, restaurants and retailers — and guidance on operationalizing experimentation and decision-making at scale — download The state of business experimentation 2026 report.