How to analyze and interpret A/B testing results

Analyzing A/B testing results is one of the most important stages of an experiment. And while most experimentation platforms have built-in analytics to track all relevant metrics and KPIs, it's important that marketers – prior to analyzing an A/B test report – understand the following two important metrics: uplift and probability to be best. 

In this post, learn more about test analysis, specifically:

• Basic experimentation analysis
• Secondary metrics analysis
• Audience breakdown analysis
• Why losing A/B tests are actually winning