A Twitter Experiment
An experiment in growing a highly-engaged audience with a new account.
I’m going to try to get to 1,000 followers on Twitter within the next 100 days.
That’s a ~3x increase from my current follower count (9/8/2020) of 306 followers.
If you’d like to check out what I’m doing (and follow along), here’s my profile.
I’ll be writing up all of the results (and what I’ve learned) at the end. You can sign up for the Growth Library newsletter to get an email when it’s ready.
Based on my initial research, most creators who are “big on twitter” either brought the audience from another channel or can’t seem to bring that audience to another channel.
I’m not sure it has to be that way. I don’t see any good reason that you can’t establish reach and create a discovery channel for your external projects.
In true fashion, I thought it would be interesting to lay out my hypothesis and my process.
A lot of my readers (and potential audience) are on Twitter. It seems like it would be good to be there, too.
Impact vs. Increment
The ideal outcome is that I earn engaged followers. There are many folks on twitter that have hundreds of thousands of followers, but abysmal engagement. That seems nearly worthless. Note that many of them seem to follow a massive amount of other accounts (say, 200k followers and 150k followed). I’m not going to play any follow games.
I want real followers interested in the things I write and tweet about — a community of thoughtful marketers.
The reason that I haven’t attempted twitter in the past is that I believe that you should commit to creating high quality, native content for each channel that you engage with. I wasn’t ready to do that yet.
Alluring as it may seem, it’s not enough to schedule out posts months in advance that gets syndicated to Instagram, Facebook, Twitter, Pinterest, etc.
I’m going to test out a handful of content types. I pulled down a big collection of marketing-related accounts (and their tweets) and used the engagement data to get a feel for what works. I made a very simple attempt at optimizing the data by looking at engagement (retweets, comments, likes) as a ratio relative to follower count.
This should at least put me in the ballpark and serve as a baseline for optimization as we go.
One additional thing that I did was map out how often these profiles reply, like, and retweet other accounts. At first glance, Twitter can seem like a broadcast-only channel, but I think it would be a mistake to adopt that posture. Most of the accounts with high engagement are highly engaged with others.
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