PPC A/B Test Significance Calculator

Find out if your ad creative test has a real winner - or if you need more data. Built for PPC managers who test creatives, landing pages, and audiences.

Variant A (Control)

Impressions / Visitors

Conversions / Clicks

Variant B (Test)

Impressions / Visitors

Conversions / Clicks

How This Calculator Works

This tool uses a two-proportion z-test to determine whether the difference in conversion rates between your two ad variants is statistically significant or just random noise.

95%+ confidence - You can confidently declare a winner and scale the better variant
90–95% confidence - Leaning towards significance but consider running longer
Below 90% - Not enough evidence yet. The calculator tells you roughly how many more impressions you need

Tips for Better PPC A/B Tests

Test one variable at a time - headline, image, or CTA, not all three
Run tests for at least 7 days to account for day-of-week effects
Ensure both variants get equal traffic (50/50 split)
Don't peek too early - commit to a sample size before checking results
Use the copy button to save your results for team discussions or client reports

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