Challenge
With hundreds of styles across the range, shoppers found the one item they came for and left. The generic 'related products' plugin pushed irrelevant items and rarely earned a second click.
28%
All case studies
A recommendation engine that lifted average order value 28%
With a deep catalog, shoppers found one item and left. A recommendation engine trained on the brand's own sales and browsing data now surfaces the right products across site, app, and email — lifting basket size and repeat purchases.
+28%
Average order value
+22%
Repeat purchases
35%
Revenue from recommendations
5 wks
Time to launch
Approach
We trained a recommender on the brand's own data — what gets viewed together, what sells together, and what each customer keeps coming back for — instead of relying on off-the-shelf rules.
Implementation
'Recommended for you' on the homepage, 'frequently bought together' at checkout, and personalized product emails — all powered by one engine that updates as customers click and buy, measured against a holdout group so every gain is real.
Results
Average order value rose 28%, repeat purchases climbed 22%, and recommendations now drive over a third of revenue — proven against a control group, not guessed.
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