How do I avoid common A/B testing mistakes on Shopify?

A few missteps can ruin an otherwise well-planned A/B test. The most common include testing too many elements at once, ending the test too early, or declaring a winner before reaching statistical significance. Another issue is testing changes with little traffic; this often leads to inconclusive results. Make sure you're testing one variable at a time unless you're using multivariate testing. Let your test run for at least 2 full buying cycles to account for variations in behavior. Also, make sure that the testing tool you’re using doesn’t create SEO issues by duplicating URLs without proper handling. Fibr.ai helps erase these risks with guardrails for test setup, auto-calculated sample sizes, and clear metrics to track.