# AI product recommendations rollout: +21% homepage conversion

- Outcome: Won
- Page type: Site-wide (Ecommerce)
- Elements: Upsells & cross-sells
- Test run by: [AB Tasty](https://liftarchive.com/practitioners/ab-tasty/)
- Commentary by: LiftArchive (our analysis, not theirs)
- Original source: https://wingify.com/success-stories/case-study-groupe-equipementde-la-maison/
- Page: https://liftarchive.com/test/bricomarche-ai-recommendations-rollout/

Replacing manually managed product recommendations with AI-driven ones was followed by a 21% rise in homepage conversion rate and a 21% rise in average basket value. AB Tasty rolled this out for Groupe Équipement de la Maison, the parent of Bricomarché, and it was published as a VWO case study. This was a product rollout compared before and after, not a split test.

## Result

**+21% homepage conversion**

- Homepage conversion rate: +21%.
- Average basket on product pages: +21%.
- Engagement with recommendations: 10% of shoppers interacted with them. No baseline was given, so this is a usage figure, not a lift.
- The team also reported time saved on manual merchandising; no figure was shared.

## Control

Product recommendations were picked and managed by hand across a catalog of more than 250,000 products.

## Variant

AI-driven, personalized recommendations appeared on the homepage, product pages and even 404 error pages. The source describes the setup as cookie-free.

## Why it likely won (our reading)

- With a very large catalog, hand-picked recommendations can't stay relevant for every shopper.
- Showing related items on product pages gives shoppers easy ways to add to the basket.
- Recommendations on 404 pages give lost visitors somewhere to go instead of leaving.

## Caveats

This was a vendor product rollout measured before and after, not an A/B test, so seasonality or other changes could explain part of the lift. No sample size, duration or test setup was shared, and the figures are vendor-reported.

## How to run this test

- Hypothesis: If we replace hand-picked recommendations with personalized ones on the homepage and product pages, then conversion and basket value will rise because shoppers see items more relevant to them.
- Primary metric: Revenue per visitor
- Guardrail: Homepage conversion rate
- Guardrail: Page load time
- Guardrail: Average order value
- Who should test it: Retailers with large catalogs where manual merchandising can't keep up. Small stores with a few dozen products will see less benefit. Run it as a split test rather than a full rollout so you can measure the real effect.

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Credit: AB Tasty ran this test and owns the result. Summary and commentary by LiftArchive (https://liftarchive.com/test/bricomarche-ai-recommendations-rollout/).
Usage: Free to use, quote and build on, with credit and a link: name the practitioner or organization that ran the test and link to its LiftArchive page. The results belong to the practitioners who ran and shared them; the summaries and commentary are LiftArchive's.