Product image A/B tests: hypotheses, sample size, and metrics
xcropimage.io Team
Run clean experiments on PDP images with one variable at a time and enough traffic for significance.
Introduction
A/B tests measure how image variants affect conversion, but you need one clear variable and enough traffic.
Earlier in this series: UGC moderation · Watermarks · Before/after series.
Hypothesis example
“White-background hero increases add-to-cart vs lifestyle hero.” Tools evolve—check current experimentation platforms’ docs.
Metrics
Track CTR, add-to-cart, and revenue; segments differ. Optimizely’s glossary explains testing basics.
Conclusion
Tag winning assets in DAM as approved variants.