Analyzing my Twitter analytics

More than a decade ago, I made a huge mistake that has a huge mistake on my career as a tech blogger. While reading my analytics, I got curious about Twitter and why people would want to link to my blog. I decided to check out what the fuzz was all about and signed up for an account. That was a huge mistake.

I quickly discovered how easy it was to throw things online on Twitter and was immediately hooked. As a result I started to tweet more and write less. Nowadays, if I average a blog post (or a video) across all my platform every few months, that’s “a lot”. One blog post across four or five blogs and a few channels is far from enough to drive traffic to any of them. I might as well not write / create the content at that pace.

On the other hand, I manage to write about 500 tweets a month. Last month, I blew that number out of the water by writing over a thousand tweets. With an average engagement rate of 1% except when going into “hilarious reply-guy mode” that’s practically like yelling into the void and hoping it yells back.

Seeing that 4-digit number made me want to calculate what that number of tweets would translate into if those words were “better” used in the form of a blog post or a script for a video. Let’s do the math together, shall we? Yeah, you weren’t expecting math today. I’m sorry.

I started by rounding the number of tweets down to a nice, smooth 1000. Given that I hit the limit for a tweet quite often let’s assume I always max out at 280 characters per tweet. That means that 280,000 characters are written that month.

A number of characters is all fine and good, but I usually count my writing on words. An online source suggested that 280 characters equals more or less 40 words, so let’s go with that number for our math. If we divide 280 characters by 40 we get a factor of 0,14 which we can use to convert characters to words.

To get the number of words written, we need to do the following:

280000 * (0,14) = 39200 words

That leaves us with 39200 words written per 1000 tweets. That’s a lot of words dedicated to tweets, but how does that translate to blog posts and video scripts?

Let’s be generous and assume that my blog posts hit the recommended 1000 words (which they often don’t) and that my video scripts are about ten minutes long and include 1500 words (which are a lot of words, especially if I have to speak them). That means we can convert those 1000 tweets into:

  • 39 blog posts of a thousand words
  • 26 video scripts of one thousand-five hundred words.

That’s a lot of content that wasn’t written in a month! You could run quite a few blogs with that kind of content, if you manage to actually produce it. And that’s the problem. Because writing your average tweet is a lot simpler than a blog post or a video script. Not every tweet has to be incredibly deep or original. You can respond to what other people say, observe something or write absolute nonsense. Most of my tweets are created in between my work anyway, during dead moments, or – and this is the worst case scenario – when I’m bored and could indeed be creating content.

But even then, writing a tweet doesn’t take that long. It takes about 45 seconds at best assuming the website is open (and I always have a tab open). Now let’s compare that to the time it takes to create a blog post or a video script.

Writing a blog post takes me about 45 minutes, and that’s just the process of writing it. I often do this by hand and then have to enter it on the website, which adds even more time. But let’s pretend that doesn’t matter for this exercise.

To create a video, I need about an hour to create a 1500 word (or ten minute) script, give or take. But a video script is worth even less than a blog post if the video isn’t created, so let’s murk the water a bit and add the time needed to record the video (at least 30 minutes) and the time needed to edit the video (at least an hour to the equation.

Content typetime in secondstime in hours
A 1000 tweets1000 * 45 = 45,000 seconds12.5 hours
39 blog posts39 * (45 * 60) = 105000 seconds29,25 hours (X)
26 videos26 * (3600 + 1800 + 3600) = 234000 seconds65 hours

Halfway through preparing this blog post I realized that it’s impossible to compare the time spent tweeting with time spent creating “actual content”. As you can see in the table about, it’s about 2.5x times more time effective to tweet than to create a blog post and 5x as effective as creating a video.

On the one hand, you have to take in consideration that tweets are fleeting. Videos or blog post have a longetivity that tweets simply don’t have. Try finding a tweet that’s a week, a month or a year old. It’ll be near impossible. But then again, it’s a lot easier to write a tweet than to create a blog post or a video. In the above scenario, not only do you have to have an idea ready but you also need to find 45 minutes to two and a half hours to create a video or blog case – and those don’t always end up being really good.

So what should the conclusion of this blog post be?

Conclusion

I think it’s fair to say that I tweet a lot – well, a lot more in March than in other months – and that in theory, those words could be used for more “lasting” content like blog posts and videos – both of which I haven’t made enough of in the last few years. However, it might not be correct to conclude that creating content instead of tweeting would achieve the desired results. I definitely don’t see how I’d be setting aside fifteen hours to create videos. Or where I’d find the inspiration and time to write 39 different blog posts a month.

Converting my tweets to “something useful” sounded great in theory, but it’s not supported by my own math.

(X) As I’m wrapping up this blog post, I’ve spent an additional 45 minutes editing the blog post and typing it into my website – I prefer to write my first draft manually for some reason. So now part of the math is debunked before the article is even complete. I’d spent closer to 60 hours writing these blog posts than the projected 30. And that’s without images, editing for SEO and other shenanigans.

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