Age-matched people in store images: +6.47% revenue per visitor
Test run byDave DiederenSyntra Labs
Commentary byLiftArchiveOur analysis, not theirsReplacing images across the store with people closer in age to the older target customer lifted revenue per visitor by 6.47% in Dave Diederen's test. Conversion rate rose 4.75% and profit per visitor rose 6.67%. Average order value also ticked up 1.64%.
- Revenue per visitor: +6.47% (£1.52 to £1.62). The range shown stayed above zero (+1% to +28%).
- Conversion rate: +4.75% (1.37% to 1.44%). Slightly more visitors bought, though this range crossed zero.
- Profit per visitor: +6.67% (£0.88 to £0.93). This was the main metric and it moved in step with revenue.
- Average order value: +1.64% (£110.60 to £112.42). A small gain on top of the extra orders.
The change
Images across the store were swapped to show people matching the older audience's age.
Simplified mockup drawn by LiftArchive from the shared screenshots.
Control
The store's existing images, where the people shown looked decades younger than the brand's typical customer.
Variant
The same store with images updated site-wide so the people pictured reflected the age of the audience actually buying. The post does not show the new images.
Why it likely won
Our reading of the result, not the practitioner's claim.
- shoppers judge "is this for someone like me?" from images before reading any copy, so visuals that match their age remove a quiet mismatch.
- copy and offer were already written for older buyers, and the images were the one piece out of step with that message.
- an older buyer seeing people their age using the product makes the outcome easier to picture for themselves.
Caveats: Sample size and test length were not shared, and the conversion rate range crossed zero. It ran on one store targeting an older audience.
Who ran it
Dave Diederen (@DaveDiederen) shared this test on X. The numbers and screenshots are theirs.
View the original post on X
How to run this test on your store
- Hypothesis
- If we update the people in our store images to match the age of our real customers, then more visitors will buy because they will see the product as made for someone like them.
- Primary metric
- Profit per visitor or revenue per visitor
- Guardrails
- Average order value
- Conversion rate among younger segments
- Return rate
- Who should test it
- Brands whose buyers skew clearly older, roughly 50 and up, while their imagery shows much younger models. If your customer data shows a young or mixed audience, this change has little to correct.
Questions
Does model age in product images affect conversion?
In this test it did. Showing people closer to the older customer's age lifted revenue per visitor by 6.47% and profit per visitor by 6.67%.
Should I change images on every page or just the product page?
Dave Diederen updated images across the whole store, so the result reflects a site-wide change. It did not isolate which page mattered most.
Who should test age-matched imagery?
Brands selling to older customers whose site imagery shows much younger people. That mismatch is what this test corrected.
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