Engagement Begets Engagement
I swear I wasn’t engagement farming.
If it looks like engagement farming, sounds like engagement farming, and smells like engagement farming, it’s probably engagement farming. Usually.
In this case, I was testing a theory.
Engagement begets engagement.
Twitter’s algorithm is quite confounding these days. Elon’s magic touch seems to have that effect on our favorite social media platform. This time though, the effects have been very much felt by a lot of us. Friends we used to see all but disappeared off our timelines. Engagement TANKED worse than the Solana crash (ok ok, that was a low blow — sorry). Twitter feels different, and not in a good way.
I wanted to test a theory to see if there was a way to revive the stagnant engagement rates that 2023 ushered in. Mytheory was simple:
If one tweet gets a significant amount of engagement, what happens to tweets that follow that day?
The findings aren’t as staggering as I’d hoped, but I stumbled on some interesting data. And because it’s worth saying, it’s really damn hard to do a true experiment around engagement on Twitter. You can’t control 99% of factors that impact engagement, so by definition this is less experiment and more of an exercise of trial and error (kind of).
The Tweet Itself:
As expected, asking for likes yielded more likes.
Despite a healthy amount of skepticism that “James is just engagement farming here”, 67 folks liked the gm tweet, outperforming previous “gm” tweets quite a bit:
All of the above feels a bit obvious. But what came next was most intriguing.
What Happened Next:
A little over an hour later, I tweeted the following:
The second gm tweet had over 2x views compared to the first tweet, and almost as many likes. Are these two things correlated? Maybe. Maybe not. It could have just been the right tweet at the right time that struck a chord with my NFT loving audience.
What follows throughout the day however makes me wonder if my hypothesis was turning out to be true: that engagement really does beget engagement.
Saturday, which is typically a lower engagement day for most, was the highest engagement day for the week, even beating out my birthday, when my 353 piece birthday NFT collection sold out.
That day, engagement was clearly 🆙 with 59 replies (9 of which came from the original tweet) and 207 likes (67 of which came from the original tweet).
Conclusion?:
So what does this all mean?
Well, my hypothesis was simple. Engagement begets engagement. If one tweet sees an uptick in engagement, this will play in favor of engagement for following tweets that day.
Can we conclusively take this tiny segment of data & say that our “findings” are definitive? Certainly not. Like I said before, the scientific method is almost impossible to implement here. There are just too many factors outside of our control to do a true experiment.
However, as a marketer, the data here certainly piques my interest, and will influence how I continue to use Twitter.
Which leads me to this final takeaway for you:
Engage with your community. At the very least, you’ll show them your love and support. And who knows — maybe you’ll be helping them reach others by sparking growth in their engagement.