A bit of controversial statement: every store is the same!
We still get regularly the question about having in-store analytics deployed in a few stores to then derive conclusions at scale. How can it be when every store is different?
After 10 years of measuring shopper behavior in-store, we’ve discovered that many of the metrics we measure (for a certain category) are actually quite similar from one store to another : dwell time, stopping rate, conversion. They’re all pretty stable for a given category between different stores and that’s why in-store analytics is so powerful. You can learn a lot from just a few stores and then derive general merchandising rules to be deployed across your store estate.
In this whitepaper, we’re sharing multiple examples of similarties between stores.