A Guide on Estimating Long-Term Effects in A/B Tests

Addressing the complexity of identifying and measuring long-term effects in online experiments

Imagine you’re an analyst at an online store. You and your team aim to understand how offering free delivery will affect the number of orders on the platform, so you decide to run an A/B test. The test group enjoys free delivery, while the control group sticks to the regular delivery fare. In the initial days of the experiment, you’ll observe more …

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