Achieving Perfect Store with AI Image Recognition​

Measuring actual in-store execution using Snap2Insight ‘Perfect Store’ solution, allowed Primo to fix execution gaps that mattered the most, and drive growth rate by 15% points.

Biz question

Primo ® Brands, a bulk water and water dispenser provider, found themselves drowning in a sea of data and analytics concerning their Walmart retail environment across the United States. With three business units spanning thousands of retail locations, all with varying footprints, merchandising and product/promo offerings, they needed to understand what the consumer was seeing and how to interpret its impact on the business.

Solution

Primo used Snap2Insight’s Perfect Shelf solution to measure and analyze Primo’s execution across all three business units in 4,000 Walmart locations. A Perfect score scoring customized for Primo was set up in order to make the process totally objective—something that makes AI more valuable than human assessment. The Primo team decided how many “points” would be deducted from each display’s score (out of 100) based on the severity of a violation. For example, one improper placement of a promotion could set them back a few points, but as the violations became more severe, like the complete absence of a promotion, the deductions cut deeper. It was simple: the more violations that occurred, the lower the display’s score as a whole. Similarly, multiple aspects from product availability, share of space, POS presence, Planogram compliance was measured and weighted appropriately to form a total ‘score’ for every store. Pairing store scores with sales and identifying key elements in the score that drove sales allowed Primo to prioritize fixes at a per-store level.

Impact

The growth rate for the brand went from 15% to 30% attributable to actions from the Perfect Shelf solution.