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Thank you!

> I think the only downside to this approach is that there might be some effect based on time of day or the interval affecting your results.

That is definitely true. I'm about to start alternating the versions every 5m to mitigate this. The closer I can get to 0m, the more accurate the results are. This way even if you get a followers spike (let's say you get a viral tweet), the followers will be properly distributed between each version.

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I think what you really want to do is randomize A or B within each 30m (or 5m) interval. This is basically switchback testing. Door dash has a nice write-up here: https://doordash.engineering/2018/02/13/switchback-tests-and...

Yep - we've run many switchback tests so I'm happy to chat more about it. It's a lot more akin to what you're building here, from a stats point of view.

Oh right, that's actually a better technique! Thanks for the idea.

Then you get the opposite problem: users are more likely to see multiple versions of the same profile.

I feel like that's less of a problem because the user is more likely to convert on the version that he likes more, which would still provide accurate data.

But yes, there is no perfect solution with the limitations of the API :D

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