What is statistical significance?

Statistical significance is the likelihood that the difference in conversion rates between your Control and Variation is not due to random chance.

A/B Test Significance Calculator

Q: How long should I run an A/B test?

Run tests for at least one or two full business cycles (1-2 weeks) to account for daily variances, regardless of how quickly significance is reached.

Q: What does p-value mean?

The p-value represents the probability that the difference in your test occurred by random chance. A lower p-value means higher confidence.

Determine if your split test winner is real or just luck

🅰️ Control Group

Visitors

Conversions

🅱️ Variation Group

Visitors

Conversions

Test Result

Not Significant

Enter your data above to see if the difference is statistically significant.

0% Control Rate

0% Variation Rate

0% Relative Lift

Why You Can’t Trust Your Eyes

In digital marketing, human intuition is often wrong. You might see that Variation B has 50 conversions while Control A has only 40, and assume B is the winner. But is it? Or was it just a lucky day?

This A/B Test Significance Calculator uses statistical math (specifically a two-tailed Z-test) to tell you the probability that your results are due to actual user behavior changes rather than random chance.

🎯 The Goal: You want a “Confidence Level” of at least 95%. This means there is only a 5% chance the result is a fluke.

How Statistical Significance Works (The Math)

Behind the scenes, we are calculating a “Z-Score” to find the standard deviation between the two conversion rates. Here is the formula breakdown:

Z-Score Formula:

Z = (P_var – P_con) / Standard Error

Where Standard Error is derived from the pooled conversion rate and sample sizes.

If the Z-Score is high enough (typically above 1.96), it corresponds to a 95% confidence level.

How to Interpret Your Results

1. Significant (95% or higher)

Green light! 🟢 The variation is statistically proven to be different from the control. If the lift is positive, you should implement the change immediately.

2. Not Significant (Below 90%)

Red light. 🔴 There is not enough data to prove a difference. If you implement the change now, you are gambling. You need to run the test longer to get more visitors.

3. Negative Lift

If your result is significant but the lift is negative, your change actually hurt performance. Revert to the Control version immediately.

Frequently Asked Questions (FAQs)

How long should I run an A/B test?

You should run a test for at least one full business cycle (usually 1 or 2 weeks) to account for weekend vs. weekday behavior, regardless of how quickly you reach significance.

What does “p-value” mean?

The p-value is the inverse of confidence. If your Confidence Level is 95%, your p-value is 0.05. It represents the probability that the difference occurred by random chance.

Can I stop a test as soon as it hits 95%?

It is best practice to wait for the pre-calculated sample size to be reached. “Peeking” too early can lead to false positives, as data can fluctuate wildly at the start of a test.