How do I use Google Analytics for AB test?

How do I use Google Analytics for AB test?

Create an A/B test

1. Go to your Optimize Account (Main menu > Accounts).
2. Click on your Container name to get to the Experiments page.
3. Click Create experiment.
4. Enter an Experiment name (up to 255 characters).
5. Enter an Editor page URL (the web page you’d like to test).
6. Click A/B test.
7. Click Create.

How do I report an AB test?

10 Tips for Your Next A/B Test Report

1. Test Period. It might sound like a no-brainer to you, but make sure to always include the test period and exact dates of when the test did run.
2. A/B Test Variations.
3. Hypothesis.
4. Most Important Results.
5. Relevant Side Analysis.
6. Predicted Uplift in Revenue or Margin.
7. Conclusion.
8. Learnings.

What do you need to know about AB testing?

AB testing (AKA “split testing”) is the process of directing your traffic to two or more variations of a web page. AB testing is pretty simple to understand: A typical AB test uses AB testing software to divide traffic. Our testing software is the “Moses” that splits our traffic for us.

What’s the difference between AB and split testing?

While AB testing and split testing are the exact same thing, multivariate testing is slightly different. AB and Split tests refer to tests that measure larger changes on a given page. For example, a company with a long-form landing page might AB test the page against a new short version to see how visitors respond.

How often is a winning variation on an AB test?

Marketers and CRO experts wait for a pre-determined level of Confidence before declaring a winning variation. Most of the time, this is set at 95%. If your AB test results are statistically significant at a level of 95% they could still be due to random variation once in every 20 times.

How to analyze and interpret a / B testing results?

For example, if one variation has a revenue per user of $5, and the control has a revenue per user of $4, the uplift is 25%. Probability to Be Best: The chance of a variation to have the best performance in the long term. This is the most actionable metric in the report, used to define the winner of A/B tests.