Store inefficiencies are getting worse, not better, meaning retailers must be more careful than ever with deploying store intelligence technology.

• Retailers now lose an average of 6.4% of gross sales to in-store operational failures, up from 5.5% in 2025 and 4.5% in 2024, according to Coresight Research's annual State of In-Store Retailing study.
• In 2026, the revenues across these sectors is estimated to increase by 3% year over year (from $2.96 trillion in 2025 to $3.07 trillion in 2026), but sales lost to inefficiencies are estimated to increase by a massive 21% during the same period (from $162.7 billion in 2025 to $196.4 billion in 2026).

The gap is widening, and the technology most retailers are buying isn't closing it.

The problem is getting worse

Nine out of 10 retailers report being at least "slightly" challenged managing store operations, per Coresight's survey of 200 US retail decision-makers.

What has changed is severity: 18% now describe themselves as "extremely" challenged, and out-of-stocks saw the sharpest jump, with 52% of retailers calling them "very" or "extremely" challenging. The average mispricing rate hit 13% in 2026, up from 10% in 2025. For a sector running on thin margins, that's not a rounding error.

What makes this data uncomfortable is that 60% of retailers say they are either scaling store intelligence technologies or have them fully deployed, up 18 percentage points from last year, according to the report. Adoption has never been higher. The operational results haven't followed. Losses are rising faster than revenues. Pricing errors are getting worse. The technology is being deployed; it is just not being deployed in the right sequence.

Retailers are building the stack in the wrong order

Coresight's sequencing framework starts with shelf digitization, meaning real-time, shelf-level visibility powered by computer vision and AI, as the foundational layer, with data analytics, inventory management, assortment planning, pricing software, and supplier collaboration building on top in sequence. The actual investment priorities of retailers are almost exactly reversed. Pricing software ranks first, cited by 43% of retailers. Supplier collaboration platforms rank second at 36%. Shelf digitization ranks third at 33%, the lowest investment share of any technology in the study, and lower than downstream tools like inventory management software (41%) and data analytics (34%).

Retailers are buying the roof before they've poured the foundation. Pricing software without real-time inventory visibility cannot eliminate pricing errors. Supplier collaboration platforms without sell-through data are running on forecasts, not facts.

“Shelf intelligence and the data foundation that it creates must come first, or every downstream system will fall short of expectations," said Kim Anderson, vice president of store operations support at Schnucks Markets. "If you don't have a reliable view of what's actually in your stores, nothing else works."

The size gap makes this more urgent. Among retailers with more than $5 billion in annual revenue, 73% are scaling or fully deployed. Among retailers under $1 billion, only 42% have reached that stage. Larger retailers are building infrastructure that becomes structurally harder to match over time, and mid-size players scaling without sequencing are capturing some efficiency without capturing the ceiling.

When the sequencing is right, the results follow

Retailers that do get the order right are seeing measurable returns. Surveyed retailers report an average 11% increase in customer lifetime value since implementing store intelligence technologies, according to the report, with 86% of store associates reporting at least some reduction in time spent on manual tasks, including shelf auditing, inventory counting, and pricing verification.

BJ's Wholesale Club deployed shelf intelligence to improve inventory and price accuracy, then used that data foundation to build a digital twin of each club location, applying those insights to optimize pick paths for curbside and same-day orders and improving picking efficiency roughly 40% YoY, according to the report. Lowe's Perpetual Productivity Improvement program expanded operating margin by 240 basis points between launch and 2022 and is now saving 80 non-productive labor hours per store per week. Both cases share the same logic: a reliable data foundation built first, with higher-order tools layered on top.

The question in 2026 is whether an investment in store intelligence is being built in an order that will actually work.

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