ClearBrain Blog

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Modern Growth Teams have one primary goal - scale the usage of their product. In order to do so, growth teams have to analyze the impact of every part of their product, so that the product can be optimized to increase the relevant KPIs. The traditional way to measure the impact of a specific part of a product would be to run an A/B test - analyzing how two different versions of the product affect a particular KPI. However, not everything can be A/B tested - whether because of feasibility, ethical concerns, or practical constraints. So instead one usually turns to analytics tools like Google Analytics or Mixpanel, which approximate impact without running an A/B test by looking at the correlation between an action and a KPI. This can take many forms - calculating the Pearson correlation coefficient, measuring the conversion rate before and after users do an event, or the feature importances of a machine-learned model. While sometimes these correlated variables are correct to focus on, j…