Hey guys!
It all started just because I’m 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:
🟡 Done so far:
I’ve got names, created_date, followers/followings, # of tweets, bios of all the users
Breaking them down into cohorts + a basic analysis of the bios.
🟡 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):
🟡 TOPs:
Top 10 accounts by followers:
Top 10 accounts by followings:
Top 10 accounts by tweets number:
Top 10 accounts by age:
🟡 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 don’t have a high following/followers ratio:
🟡 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':
🟡 Further plans & questions I have so far:
🟡 Just so you know:
If you have any questions/ideas what you’d 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 😅!
Thanks for reading this & hope it brings value to you guys! ♥
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 👍☺️
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 😍
This comment was deleted 3 years ago.
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:
This comment was deleted 3 years ago.
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.