A/B Test Analysis

Know if your test actually won. Get statistical confidence, segment breakdowns, and clear recommendations.

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About this tool

The A/B Test Analysis tool evaluates experiment results with proper

statistical methods. Stop guessing whether your test won — get

confidence intervals, p-values, and segment-level insights.

Know when results are real

See the range of likely outcomes

Check if results differ by segment

Know if you have enough data

Most A/B tests are called before reaching statistical significance.

PreHog runs proper analysis so you know whether your results are real

or just noise.

Data collection — Pulls experiment data from PostHog or GA4
Sample size check — Verifies you have enough data for reliable results
Statistical test — Runs appropriate test (chi-squared for conversion, t-test for continuous)
Confidence intervals — Shows the range of likely true effect sizes
Segment breakdown — Checks if results hold across mobile/desktop, new/returning

Proper statistics prevent costly decisions based on noise
Segment analysis catches cases where a test wins overall but hurts a key segment
Sample size warnings prevent premature test calls

Never call a test with less than 95% confidence unless you understand the risks.

By PreHog · March 2026

Video coming soon

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