The original poster wants to A/B test thumbnail image styles (studio vs. lifestyle) and create a report tracking click-through rates (CTR) and conversion rates for products across collections to identify which items need better primary images.
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The discussion remains open with no definitive answer to the original question about creating CTR/conversion reports. Two follow-up comments indicate others are seeking the same solution, and one asks about the methodology (software vs. manual analysis) used for the testing shared.
I would like to test which style of thumbnail image works better for conversions (Between studio images, or a mix of studio/lifestyle imagery).
But I would also like to create a report, so like out of all collections what is the click through rate for each product and conversion rate. So I can know which products needs the first image changed to perform better.
If anyone had any handy tips for this?
I can weigh in on this. Not sure what niche you’re in, but:
For product photos, we tested product-only vs product with a human model listings across 110 listings. Models were generated using picjam.ai
T-shirt category: +26.7% difference on average with a human model, vs without a model
Jeans/pants category: +16.4% difference on average with human model, vs without a model
I do remember seeing studies on how we will look to human faces first when scrolling social media or browsing online, which is something instinctive.
Suspect this might have something to with it? Besides explaining the positive results in t-shirts, this might also explain the difference between between t-shirts and pants (confirming that the results with pants did not have faces, and had arms and shoes only).
Did you find an answer to this? I am searching for exactly this
Hi, how was this analyzed? Through software or manually?
