Free A/B Test Significance Calculator

Check if your A/B test results are statistically significant before making decisions.

Your test may not have enough data — you could be making decisions on noise.

Running A/B tests means you're actively optimizing. You need easy-to-test elements to run more experiments faster.

Widgets That Solve This

Based on the problem this tool reveals, these widgets directly address the root cause.

Popups are the most common and fastest element to A/B test — headline, timing, and offer copy.

Top bars are lightweight test subjects — test different CTAs or offers without touching page code.

Enter your actual numbers for the most accurate diagnosis. Estimates work but real data gives better recommendations.

Check how your numbers stack up against industry averages. This context helps prioritize what to fix first.

Use the recommended widgets below to address the specific problems this tool reveals. Start with the easiest wins.

Ready-to-use templates you can customize and embed on your website.

Embed this tool on your website, or explore widgets that solve the specific problems it uncovered.