A/B Testing Visuals the Right Way
Form one sharp hypothesis per test: for example, “Outcome-first screenshot increases tap-through.” Change a single variable at a time, and run long enough to reach confidence. Predefine success metrics and stop-loss limits to prevent chasing noise.
A/B Testing Visuals the Right Way
Look past conversion rate. Track click-through from search, install rate from page views, and retention to catch misleading wins. A flashy visual that draws installs but inflates churn isn’t success—align tests with lifetime value and cohort quality.