Hey guys!
It all started just because Iβm curious how to grow my twitter account better. I decided to make a mini-research & pull the public data of almost 60k IndieHackers followers from Twitter and see what I can learn & share it.
The goal of posting it here is:
π‘ Done so far:
Iβve got names, created_date, followers/followings, # of tweets, bios of all the users
Breaking them down into cohorts + a basic analysis of the bios.
π‘ General overview:
46% of users have <100 followers
(cohorts = days from-till):

52% of users follow <499 accounts
(cohorts = followings, from-till):

55% of users have <499 tweets
(cohorts = number of tweets, from-till):

66% of accounts are older than ~5 years
(cohorts = days of account existing, from-till):

π‘ TOPs:
Top 10 accounts by followers:

Top 10 accounts by followings:

Top 10 accounts by tweets number:

Top 10 accounts by age:

π‘ Early growers:
Those who just started (<50 days) & grew past 300 followers seem to be following aggressively:

Accounts who grew to 500+ followers in the last 100 days look like this:

(looks like they either start with following others, or are really active (# of tweets), or maybe have other source of audience - eg, other social media)
But accounts who grew to 10k+ followers in the past 365 days donβt have a high following/followers ratio:

π‘ Bios content:
I checked the # of bios containing some words assuming this may correlate with the audience interests/niche they are working at, etc. Here is the result:

IH users seem to be founders with mostly technical background + there are more niches/interests that are interesting to check.
What I was even more excited to see is the ability to find the intersections of interests in particular bios. This may be a good way for lead generation/targeting particular people in a niche you are working in. For example, 'founder' + 'nocode':

π‘ Further plans & questions I have so far:
π‘ Just so you know:
If you have any questions/ideas what youβd like to see from this data -> please, let me know! I'll be happy to check them & share for you. If we have enough question here, I'll be happy to make a Part2 of it.
Also if you would like to work with a tool having all this data yourself - please, leave your email in a Typeform here - so I'll know you are curious about it: https://maxreva.com/twitter.
Also don't hesitat to ping me on twitter, ofc π !
Thanks for reading this & hope it brings value to you guys! β₯
Jeez, this is massive!!! Thank you for taking your time.
I did something similar, I analysed the tweets of IndieHackers to understand which converts better. I shared this on a thread: https://twitter.com/ToheebDotCom/status/1371481721766559744?s=20
It may give an insight into one of the other questions you have (on posts and engagements).
Nice job! Like you, I was curious too. Can't wait for the next part.
Thank you! Glad to check your thread πβΊοΈ
This info is very interesting! Congrats for the initiative! Can you share what stack did you use to "mine" for data?
thank you!
sure, it's simple: python (tweepy) + twitter api + vultr server
Thank you so much for sharing this! According to the tables in the post, it looks like constant activity (tweet/d avg ) pays off - this is a nice point. I'll wait for the next part)
thank you!
exactly, people with bigger audience seem to post more actively.
I'm thinking about categorization of the content -> to be able to say, which type of content works better π
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thanks for your thoughts!
I'm definitely glad to hear about Connect & looking to research more about it. Right now I'm just curious to find what works for growing my account + have like 3 different product directions to think about - trying to understand what's more valuable.
Also good point about the community/course/books: I didn't see them in top, so didn't check their numbers. They aren't too big, but still they are here:
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thank you!
well, agree with you on the 'outside' building of the audience.
as for the 'inside' one -> I'm still experimenting with it.
it's also not necessarily connected to the engagement/growth itself -> I'm also thinking about mining the content, for example -> it's just really wide area and I think there is still some space for a useful tool here. the real question is how to frame it to bring most of the value, though.