My main recommendation – include only users impacted by the change in your analysis; exclude users who are not.
- Let’s say you have an e-commerce site. You want to test whether certain changes to your checkout page would increase conversion (% of users purchasing).
- You want to run a 2 x 2 Multi-Variable experiment with 1 control and 3 treatment groups.
- Your current conversion is 5%; you want to detect conversion changes as small as 10% (with the conventional 80% probability of detection and confidence level at 95%).
- According to this table in my blog post, you would need 30,400 users in each group, or 30400 x 4 = 121,600 users in total visiting your site. (That’s a lot!)