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Show HN: Birdy – Twitter Profile A/B Testing

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Re: Show HN: Birdy – Twitter Profile A/B Testing

#31
post #24

Earlier quoted context omitted.

What's a good entry to the indie maker community on Twitter?

Start building a strong Twitter presence! Also engage with the IndieHacker forum.

I have a years old Twitter account with like 300 followers (many mutuals) but very low engagement on anything that isn't a reply to a higher-profile account.

Should I create a fresh account to reset how the algorithm sees me, or should I double down on this one that already has /some/ (not much) visibility?

Re: Show HN: Birdy – Twitter Profile A/B Testing

#32

Earlier quoted context omitted.

Definitely agree that this is a good solution given the limitations, 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 said I think the chances of that are super low and A/B testing is only so accurate anyway. Great idea and nice website!

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…

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...

Re: Show HN: Birdy – Twitter Profile A/B Testing

#33

Earlier quoted context omitted.

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…

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...

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

Re: Show HN: Birdy – Twitter Profile A/B Testing

#34

Earlier quoted context omitted.

Start building a strong Twitter presence! Also engage with the IndieHacker forum.

I have a years old Twitter account with like 300 followers (many mutuals) but very low engagement on anything that isn't a reply to a higher-profile account. Should I create a fresh account to reset how the algorithm sees me, or should I double down on this one that already has /some/ (not much) visibility?

Definitely double down on the one you already have. Starting from 0 is way more difficult than starting out with 300 followers.

Transform your profile and make it super interesting (work on your banner and bio, then have a good pinned tweet once you get a somewhat viral tweet). Then engages daily with other accounts - that's where new people will discover you.

Re: Show HN: Birdy – Twitter Profile A/B Testing

#35

Earlier quoted context omitted.

Start building a strong Twitter presence! Also engage with the IndieHacker forum.

I have a years old Twitter account with like 300 followers (many mutuals) but very low engagement on anything that isn't a reply to a higher-profile account. Should I create a fresh account to reset how the algorithm sees me, or should I double down on this one that already has /some/ (not much) visibility?

> Should I create a fresh account to reset how the algorithm sees me

Don't overthink it, just think about why someone would follow you. If it's just a bunch of retweets about a large range of topics it's usually not very interesting to people. Unlike TikTok there's no algorithm that suddenly puts you in some recommendation box where you then get millions of views over night.

- Make sure you have a profile picture, a good description

- Clean out the people you follow to be relevant to what you care about these days

- Follow interesting people in your niche

- Reply to tweets if you have some interesting to say, engage with content you like.

After a while you'll see people over and over and if you like what they put out, you follow them.

Re: Show HN: Birdy – Twitter Profile A/B Testing

#38

Earlier quoted context omitted.

Definitely agree that this is a good solution given the limitations, 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 said I think the chances of that are super low and A/B testing is only so accurate anyway. Great idea and nice website!

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…

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

Re: Show HN: Birdy – Twitter Profile A/B Testing

#40
post #38

Earlier quoted context omitted.

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…

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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