A/B Split Test Calculator

A/B Split Test Calculator

Calculate statistical significance between two variants. Make data-driven decisions with confidence using robust statistical analysis.

Test Results

Frequently Asked Questions about A/B Split Test Calculations

What Data Do You Need for A/B Testing Calculation?

You need to enter four main values:
- Control Visitors (A): Total number of users who saw version A
- Control Conversions (A): Number of users who converted in version A
- Variation Visitors (B): Total number of users who saw version B
- Variation Conversions (B): Number of users who converted in version B

How to Set Up Your A/B Test Parameters

The calculator offers two key settings:
Test Type:
One-sided: Tests if variant B is better than variant A
Two-sided: Tests if variant B is different from variant A (either better or worse)
Confidence Level: Choose between 90%, 95% (standard), or 99%

Understanding A/B Test Calculator Results

The calculator shows:
- A clear success/failure message
- Conversion rates for both variants
- Relative difference between variants
- Statistical power percentagep-value of the test

How is the conversion rate calculated?

Conversion rate is calculated as:
Control rate = Control Conversions / Control Visitors
Variation rate = Variation Conversions / Variation Visitors
All rates are displayed as percentages in the results.

What is P-Value in A/B Testing?

The p-value shows the probability of seeing these results by chance if there was no real difference between variants. Lower p-values indicate stronger evidence of a real difference:
- Below 0.05 for 95% confidence
- Below 0.01 for 99% confidence
- Below 0.10 for 90% confidence

How to Know if Your A/B Test is Statistically Significant

Your test is significant if the p-value is less than (1 - your confidence level).

Ready to get more customers for your SaaS?

Book in a call and I’ll show you how I’d scale your acquisition with Google Ads for your product.