Classic two-variant tests, full-factorial designs, interaction effects, traffic allocation, power & sample-size calculators.
4 resources on this topic
A guide to using four causal analysis techniques to measure the contribution of product features and marketing initiatives to key business metrics and KPIs. Covers experimental design, quasi-experimental methods, propensity scoring, and causal graphs to establish causality and quantify feature impact.
Build your experimentation system to get new insights at a fast pace. Kickstart the compounding effect that will generate long term business outcomes and customer value.
This article provides an in-depth look at how WeTransfer leveraged a custom growth model to predict marketing ROI and identify their biggest revenue opportunities. It covers the process of building the growth model, how it was used by the product and marketing teams, and the key insights and results that were uncovered.
A comprehensive guide on designing and implementing an in-house feature flagging and A/B testing platform for managing product rollouts, experiments, and user segmentation at scale.