- A/B testing is the process of testing two versions of a page to see which one performs better in reaching your business objectives. -
-1. Define what to test
- The main goal is increasing your ROI. Figure out the best page(s) to
- test. Here are a few examples of good testing variables:
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2. Create the page variation
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3. Configure a Google Analytics account
- This is necessary in order to record the statistics of your test.
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4. Create your campaign in Google Analytics
- Simply follow the wizard by creating a new experiment in the Behavior >
- Experiments menu of Google Analytics.
- To learn more, take a look at their online help.
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Good practices |
- Bad practices |
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| Know how long to run a test before giving up - Don't give up too early! Wait for your test results to be significant. Take a look at the statistical - confidence in Google Analytics; It should be at least 95%. - Don't give up too late neither because poorly performing variations could cost you revenues. |
- Don't test versions at different time periods If you - test one version one week and the second the next one, your results won't be - accurate, or worse, wrong! |
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| Do many A/B tests - Don't despair if your first A/B test turns out to be a lemon. The key in optimizing conversion rates is to do a ton of A/B in order to put together all the most effective configurations. |
- Don’t surprise regular visitors - If you are testing a core part of your website, include only new visitors in - the test. You want to avoid shocking regular visitors, especially because the - variations may not ultimately be implemented. |
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| Test only one variable Try only one variable at a time, otherwise you won't be able to clearly interpret the results of your modifications. |
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