AI-Personalised Offers and Loyalty Analytics for a Regional Grocery Chain
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Problem
One-size-fits-all loyalty offers
A 38-store regional grocery chain in the US Midwest ran a plastic-card loyalty programme that did little more than accumulate points. Weekly coupon mailers went to every member identically, redemption sat below 2%, and category managers planned promotions from month-old spreadsheet exports. Younger shoppers were drifting to national competitors whose apps surfaced offers that actually matched what they bought.
Solution
Personalised coupons, data-driven merchandising
We built a recommendation engine trained on two years of anonymised basket history that scores every loyalty member against the week's offer inventory, delivering personalised digital coupons and product suggestions through a rebuilt loyalty app. A merchandising analytics dashboard gives category managers store-level views of redemption, basket affinity, and promotion lift, so weekly offer planning runs on current data instead of habit.
Measurable Impact
What changed after launch
Digital coupon redemption rate rose from under 2% to 11% within the first 5 months
Members receiving personalised offers grew average basket size by 8.5% versus the untargeted control group
Active loyalty app usage reached 46% of enrolled members, up from 17% on the legacy points portal
Weekly promotion planning time for category managers dropped from two days to under three hours
Tech & Tools Used
What powered the build
Ready to Build your Grocery Retail Business with Recommendation Engines
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