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A/B Test Statistical Significance Calculator

Determine if your A/B test results are statistically significant or just random noise. Essential for Conversion Rate Optimization (CRO).

Control (Version A)

Original

Conversion Rate

3.00%

Variant (Version B)

Challenger

Conversion Rate

3.70%

Test Result: Not Significant

The difference in conversion rates is not large enough to be statistically certain. You may just be seeing random noise.

Certainty

94.8%

Confidence that controls are different

Observed Lift

+23.33%

Relative increase in conversion rate

Test Status

Keep Testing

Based on 95% threshold

Key Benefits

  • Avoid implementing changes based on 'luck'
  • Calculate statistical significance (p-value) instantly
  • Compare Conversion Rates of Control vs Variant
  • Make data-driven decisions with 90%, 95%, or 99% confidence
  • Stop wasting traffic on inconclusive tests

Target Audience

  • CRO Specialists & Growth Marketers
  • Product Managers running improvements
  • UX Designers validating new designs
  • Digital Marketers testing ad creatives

How It Helps

  • Prevents false positives in your experimentation program
  • Gives you a mathematically backed 'Winner' declaration
  • Helps you understand when to stop a test
  • Standardizes how your team measures success

Stop Guessing. Start Testing.

Running an A/B test is the easy part. Knowing if the result is real is the hard part.

Human brains are wired to find patterns where none exist. If Version B gets 5 more sales than Version A, you might pop the champagne. But often, that is just random statistical noise.

This calculator uses Frequentist Statistics (Z-Test) to tell you mathematically if you should deploy the winner or keep the test running.

Interpreting the Results

Significant

The calculator is 95% (or more) confident that the difference is real. Action: It is safe to declare a winner and roll out the changes.

Not Significant (Yet)

There is not enough data to be sure. The difference could be due to luck. Action: Keep the test running to collect more sample size.

Frequently Asked Questions

Common questions about using this tool