Measured study
The in-store conversion study: a census beats a sample
This is the measured result behind Cognifyze: what happened when a physical-retail network stopped sampling a few mystery-shopping visits and started measuring 100% of its sales interactions. The headline numbers are below, followed by how the study was run.
How the study was run
The design is same-store: the same locations were compared before and after the program, which controls for differences between stores. Rather than sampling a handful of visits, Cognifyze measured 100% of sales interactions with AI, captured with consent and without identifying any shopper. The change in conversion was tested for statistical significance.
What changed
Conversion rose from 51.5% to 79.5% after the program, a lift of 28 percentage points, statistically significant at p<0.001. Measured ROI reached 383%, with payback in 1.4 months. Because the comparison is same-store, the gain reflects the program rather than differences between locations.
Why measuring everything mattered
A sample of a few visits per store shows whether service is broadly good or bad; it cannot show which specific behavior, in which store, moved the number. Measuring every interaction makes the result coachable: managers see what actually happened and adjust daily. That is what compounds into a 28-point lift.
Privacy
Interactions were captured with consent and without identifying any individual shopper. The approach is privacy-first, aligned with LGPD and GDPR.
Run the same measurement on your network
The study is one network’s result; the method is repeatable. A pilot starts with a 30-minute executive diagnostic and an auditable ROI baseline, so you measure the impact against your own numbers.
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About the study
What did the study measure?
The change in in-store sales conversion after replacing sampled mystery-shopping visits with an AI census of 100% of sales interactions, on a same-store basis.
What is a same-store study?
It compares the same locations before and after a change, which controls for differences between stores and isolates the effect of the program.
Is the result statistically significant?
Yes. The lift from 51.5% to 79.5% conversion was significant at p<0.001.
How was privacy handled?
Interactions were captured with consent, no individual shopper was identified, aligned with LGPD and GDPR.