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by wodenokoto 622 days ago
> 2. Making sure your experiment runs in 7-day increments. Averaging out weekly seasonality can be important in reducing variance but also ensures your results accurately predict the effect of a full rollout.

There are of course many seasonalities: day/nigh, weekly, monthly, yearly seasonality, so it can be difficult to decide how broad you want to collect data. But I remember interviewing at a very large online retailer and they did their a/b tests in an hour because they "would collect enough data points to be statistical significant" and that never sat right with me.