A Leading European Retailer Reduces Out-of-Stocks and Improves Pricing Accuracy with Shelf Intelligence

AT A GLANCE

• Retailer: Leading European food retailer
• Segment: Grocery & Hypermarket
• Stores Deployed: Proof of technology across multiple large-format stores
• Focus Areas: On-shelf availability, pricing accuracy, labor efficiency
• Key Wins:
  • 25% reduction in out-of-stocks within the first 60 days
  • 30%+ reduction in controllable out-of-stocks
  • 60%+ of detected outs restocked each week; ~30% resolved within 12 hours
  • 70%+ improvement in pricing accuracy in a paper-tag environment
  • 45% reduction in unlinked electronic shelf labels (ESLs)

A leading European food retailer, operates some of the largest store formats in its market, managing tens of thousands of SKUs across complex assortments. While execution standards were strong, leadership recognized a persistent challenge: the shelf itself remained difficult to monitor with consistency and speed.

Store teams relied on manual shelf checks, exception reports, and periodic audits to identify out-of-stocks and pricing issues. These processes were labor-intensive and inconsistent, particularly during seasonal resets and promotional changes. At the same time, labor capacity was tightening. Teams did not have the bandwidth to audit shelves frequently enough to keep pace with assortment complexity and store scale, while continuing to provide top-notch customer service.

The innovation-led organization set out to evaluate whether autonomous shelf intelligence could close this visibility gap without disrupting daily store operations.

The retailer launched a proof-of-technology phase deploying Simbe’s Store Intelligence platform, powered by Tally the autonomous shelf-scanning robot, to evaluate real-time shelf intelligence in live grocery environments. Success criteria were clearly defined and tied to improved on-shelf availability, pricing accuracy, and speed of issue resolution. Leadership treated the initiative as operational learning focused on understanding how autonomous shelf-scanning technology would function inside their large-format stores.

Shelf data was integrated directly into existing store routines. Reporting formats, scan timing, and assortment coverage were refined throughout the program based on store feedback, seasonal demands, and local operating constraints.

The initiative spanned highly complex environments, including large-format stores where manual auditing is difficult to sustain, as well as mixed pricing setups using both ESLs and paper tags. This allowed the retailer to evaluate pricing execution across operating models and confirm that autonomous shelf scanning surfaces issues ESL systems alone do not detect.

Simbe maintained regular feedback loops with store leadership throughout the pilot and delivered training & materials in the local language to ensure operational clarity. This standardized deployment approach helped teams translate data into action quickly and consistently within established workflows.

Store teams acting on shelf intelligence data delivered meaningful improvements across availability, pricing, and execution speed.

Overall out-of-stock rates declined by 20–25% across proof of technology stores. Controllable out-of-stocks—items that were available in the store but missing from the shelf—improved by 25–35%, highlighting how often availability issues were execution-related rather than supply-driven.

Execution speed improved as well. Approximately 30% of detected shelf gaps were resolved within 12 hours, with the majority addressed within a day, significantly tightening the loop between detection and action.

Pricing accuracy also improved. In paper-tag environments, the retailer saw a 70%+ improvement in price error rates, while ESL-related issues declined, including a 45% reduction in unlinked ESLs. These results reinforced that even stores planning for broader ESL adoption benefit from frequent, independent shelf validation.

Store team and shopper sentiment also exceeded expectations. As one of the first retailers in its market to introduce autonomous robotics in-store, leadership closely monitored reception. Both associates and shoppers responded positively, with no disruption to daily operations.

Senior leadership noted that automated inventory control and integrated reporting provided stronger oversight of shelf availability while giving employees more time to focus on customer service creating measurable benefits for both operations and shoppers.

Real-time shelf intelligence delivers measurable value even in well-run, large-format European stores. These outcomes are consistent with Simbe’s scaled deployments across multiple continents. The biggest gains came from giving store teams clearer, more frequent signals on what needed attention first. Close collaboration with store managers, local-language enablement, and an iterative rollout also helped build trust and adoption early, ensuring shelf data translated into action.

For the retailer, shelf intelligence was ultimately about establishing a dependable source of truth inside the store. Based on the pilot’s strong results, leadership approved expansion to additional stores.