Avoiding common mistakes can make a huge difference in the quality of your A/B test results. Here are some common pitfalls and how to avoid them.

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Changing Multiple Elements at Once

When you change multiple elements at the same time, it becomes difficult to isolate which change caused the performance difference. Stick to testing one element per experiment, whether it’s a CTA button, a headline, or a product description.

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Running Tests Without Sufficient Traffic

Ensure you have enough visitors to detect significant differences. Without enough traffic, your test may never reach statistical significance.
For a 1% difference, you’ll need around 7,000 visitors per variation.
Learn more about traffic requirements here.

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Stopping Tests Too Early

Prematurely ending a test can lead to inaccurate conclusions. Always let the test run for the full duration needed to gather enough data, even if early results look promising.
We recommend running tests for at least 1-2 weeks or until you reach statistical significance.