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AOV lift is the percentage increase in average order value (AOV) produced by an A/B test variant compared to the control. While conversion rate lift measures how many more visitors complete a purchase, AOV lift measures how much more each buyer spends per order. Together, these two metrics — and the combined revenue lift — provide a complete picture of how a change affects your store's top-line revenue.
AOV Lift (%) = ((Variant AOV − Control AOV) / Control AOV) × 100
Example:
Note: AOV lift should always be reported alongside statistical significance — a 15% AOV lift that is only 70% confident is not a reliable result.
For D2C brands, increasing AOV is often more capital-efficient than increasing conversion rate, because it improves revenue without requiring more visitors or ad spend. A product bundle that lifts AOV by 12% on a store doing ₹1 crore per month adds ₹12 lakh in monthly revenue — while acquisition cost stays flat. AOV lift experiments — testing bundle displays, free shipping thresholds, quantity selectors, add-on product carousels — are therefore some of the highest-leverage tests a Shopify store can run.
The Man Company tested a "Build Your Kit" bundle selector on their face care category page. The control showed individual products; the variant grouped three complementary items with a 10% bundle discount and a single "Add Kit to Cart" button. The control AOV was ₹890. The variant AOV was ₹1,310 — a 47% AOV lift. Even accounting for the 10% discount, the net revenue per order improved significantly, and the test reached 97% confidence after 18 days. The bundle module was rolled out across all care categories.
AOV is a continuous metric with high variance (orders range from ₹200 to ₹5,000+ on many stores), which means AOV lift experiments typically require larger sample sizes than conversion rate tests to reach statistical significance. Use a t-test or Mann-Whitney U test when analyzing AOV results, and ensure your testing platform can handle revenue as a metric, not just binary conversion events.
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