Conducting Additional Analysis for Deeper User Insights
Performing additional analysis for an A/B test is common, especially when introducing bigger changes to a product. The results of an A/B test tell you what happened, but they don’t typically tell you why it happened. To understand why, you may need to do subsequent analysis.
In Chapter 4, Interface with Data and Visualizing Results , we’ll detail best practices for interfacing with data so that it’s easy to conduct additional data analysis; until then, let’s explore how analyzing subgroups within the test variants enabled us to understand why the initial For You test results were so low.
Assessing the For You Homepage on High Consumption Users
The For You homepage is a significant change ...
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