Retail has spent the past decade investing heavily in data, adding platforms, expanding digital touchpoints, and implementing systems to capture nearly every customer interaction. Yet as 2026 begins, many retailers are facing a sobering reality: a significant portion of valuable information remains unseen, unused, or disconnected from day-to-day decision-making.
This challenge is described as “dark data”—customer, operational, and behavioral information that exists within an organization but cannot be easily accessed or applied. Research from SAP Emarsys highlights how widespread this issue has become, showing that while brands collect large volumes of transactional and behavioral data, more than half struggle to use it effectively because it is spread across marketing, service, commerce, and revenue systems. According to industry analysts including Gartner and IDC, 70-80% of a CIO’s budget is spent maintaining and integrating siloed legacy systems rather than unlocking the insight those systems were meant to provide. From an operational standpoint, this fragmentation and budget constraint limits agility at a time when speed and precision matter more than ever.
As a COO, I see dark data not as a technical inconvenience but as an execution risk. When insight is delayed or incomplete, decisions slow down. Teams work with partial context. Problems are addressed only after they surface in lagging indicators such as declining revenue or customer churn. By then, the cost of inaction is already embedded in the business.
Retailers don’t suffer from a lack of data; they suffer from a lack of connected insight, leaving early warning signals buried across systems until churn, lost revenue, and operational inefficiencies surface too late.
Customer loyalty is where this risk is most visible. SAP Emarsys’ latest Customer Loyalty Index shows that trust alone does not secure long-term commitment. While 67 percent of consumers say they trust a favorite brand, 61 percent will switch for a better price, and nearly half will leave after a single poor experience. What makes this difficult is that dissatisfaction is rarely explicit. Customers do not usually announce their intent to leave. Instead, they disengage gradually—opening fewer emails, visiting less often, or reducing spend incrementally. This quiet erosion often goes unnoticed until the relationship is already lost.
Retail teams frequently acknowledge that the problem is not customer volatility, but visibility. The early indicators of disengagement exist, yet they are scattered across systems that they have been unable to connect. Commerce platforms may show declining order values, marketing tools reflect reduced engagement, and service systems hold unresolved issues. Without a unified view, no one sees the full progression of the customer relationship, and opportunities to intervene early are missed.
Looking ahead to 2026, broader industry trends are intensifying this challenge. AI tools became widespread across retail operations in 2025 and will continue to scale. While these technologies deliver efficiency and personalization, they also introduce new complexity with the volumes of data they generate. At the same time, consumers are demanding greater transparency around automated decisions, placing pressure on retailers to understand not just outcomes, but the data foundations behind them.
Customer journeys themselves are also at risk of becoming more fragmented. Shoppers expect consistent experiences across channels, whether browsing online, purchasing in-store, or engaging with customer support. Each interaction generates additional data, yet many retailers still struggle to structure and integrate this information in ways that enable timely action. Collecting more data without improving its organization only deepens operational friction.
There are, however, clear examples of progress. Molton Brown’s consolidation of systems through SAP Commerce Cloud and SAP Emarsys allowed the company to connect engagement across channels more effectively. The result was a 20 percent increase in repeat purchases, a fivefold increase in email-driven revenue, and stronger omnichannel performance overall. Notably, these gains did not come from acquiring new datasets, but from making existing information accessible and usable across teams. This is a powerful reminder: operational leverage often lies in simplification rather than expansion.
Technology providers like SAP CX increasingly emphasize the importance of an intelligence layer that connects insights across marketing, service, commerce, and revenue functions. From an operational perspective, this approach reflects how decisions are actually made. Advanced analytics and automation only deliver value when built on consistent, high-quality data. Without that foundation, even sophisticated tools risk amplifying noise rather than clarity.
Emerging trends such as smart consumer agents further raise the stakes. As automated systems assist with purchasing and reordering, the accuracy and structure of product and customer data become critical. These tools depend on clean information to function effectively. Once again, success hinges on data readiness rather than volume.
In discussions with retail leaders across the U.S., several priorities are consistently emerging for the year ahead. Many organizations are reducing the number of disconnected systems that house critical customer and product data. Others are narrowing their focus to the metrics that most reliably indicate intent or disengagement, while deprioritizing those that add little operational value. There is also a growing effort to ensure service insights are visible to marketing and commerce teams, breaking down silos that delay action. Finally, explainability has become essential, as customers increasingly expect clarity around automated decisions.
The opportunity for 2026 is not to gather more information, but to make better use of what retailers already have. Many of the signals that predict customer behavior and operational risk already exist within their systems. What is missing is alignment—shared visibility, common definitions, and integrated pathways that allow insight to move quickly across the organization.
Dark data is not an abstract concept. It is the gap between information and action. Retailers that succeed in closing that gap will be better positioned to strengthen customer relationships, manage demand, and navigate an increasingly complex environment with confidence in the year ahead.
