If I’m understanding correctly, this switches your profile on some interval between A and B, whereas a proper A/B test will randomly bucket a user to experiment A or B.<p>Not that it matters - this solution is probably the right way to go without building something into Twitter itself - but the more data/stats oriented folks may be confused or irked by calling this “A/B testing”
Don't want to rain on your parade but this is in no way a scientific A/B test. If I understand this correctly, Birdy periodically switches profile information b/n A and B.<p>* How do you make sure the same user who was on A variant yesterday doesn't get the B variant today?<p>If the same user gets both variants over different periods of time, how can you say treatment group engaged more with your content. People shuffle in and out of the treatment group periodically. Thoughts?
I built Birdy to help you optimize your Twitter profile with continual automated A/B testing!<p>Why? More Twitter followers. More website clicks.<p>I'm a huge fan of Twitter since I discovered the indie makers community. I wanted to create a product around this passion of mine, so I started experimenting with the Twitter API and I eventually landed on profile A/B testing as a cool problem to solve :).
Do this with the Apple App Store! “App Store Optimization” is a huge business, and something simple like this (with suggestions on what you should try - perhaps a premium feature?)<p>I’d sign up instantly
This is a brilliant idea. Feel like it should work since this is already done for YouTube. The same mechanism is used to A/B test thumbnails and automatically choose one to be the winning candidate.<p>Congrats on making this.
What a great, simple idea. Way to follow through and actually make it happen!<p>Random ideas:<p>* Pricing: you could tie pricing with the performance (pay $1 per extra followers that your best version is getting - cap at $X0).<p>* Marketing: use the twitter api to find accounts that need you the most. Probably businesses who tweet a lot with little engagement. You could target newly funded startups, maybe look at who's posting on product hunt etc.
Cool idea, looks very polished. I guess for this to work best, you need to be very consistent with putting out content to get a good baseline?<p>The Twitter maker community is exciting to be in right now. Lots of fun tools popping up (Saying this as a fellow bird-named tool creator: <a href="https://getbirdfeeder.com" rel="nofollow">https://getbirdfeeder.com</a>).
I like the website!<p>There is no “testing” going on here, unfortunately. You’re just taking turns placing users in the treatment or control group, arbitrarily, depending on when they visit the page. How can you measure any treatment effect when everyone is part of either group?<p>I guess you could try something like switchback testing, but I’m not convinced visits to the average Twitter profile will yield enough samples.<p>I think it’s a well-executed idea, but I don’t think it’s fair to sell results under the guise of statistical validity when they don’t appear to have that. (although it’s just Twitter profiles, not eg medical treatment, so no real harm done)