You Ask, I Answer: Measuring Content Engagement KPIs?

In today's episode, Erica asks, what KPIs do you use to measure your content and engagement and where do you source the data to track them? It depends on how we define engagement. So engagement is one of those really tricky terms because it means many different things to many different people. There are a whole basket of different metrics that generally fall into the engagement bucket. On websites, it's like time on page, uh, average session duration, uh, number of page views all indicate that you're spending a lot of time on the site, right?

You're engaging with the content. And then there are other things you can do on a website like uh share a link uh through a social widget, for example, uh email an article to a friend. All those would be uh engaging content as well. In the social media realm, uh you have all the traditional measures, the three major buckets, right? Like content, uh, like, comment, share, would be the three major behavioral types that you perform in social media for engaging content.

And the trick is this for those two domains, there's not a load of a lot of overlap. So let's let's take a look here. This is uh a scatter plot of 7,700 pages, and this is the number of uh page views, traffic to a set of top performing articles, um, versus the number of total social media shares. What we see here is a statistical non-relationship. What this means is that just because something is shared on social media does not mean that it has any mathematical uh relationship with uh the number of views that that content gets.

People share stuff all the time and don't read it. People read stuff all the time that they don't share. So be very, very careful about mixing these two measures together because you can see there is no relationship. There is nothing that connects these two together. So the question then is okay, KPIs.

How do we measure content engagement then? You have a basket full of metrics, right? All these different uh metrics, things like social shares and stuff like that. You also have or should have a measure of uh what content performs the best in terms of uh outcomes you care about, like conversions, right? Whatever your goal completions are, conversions are every piece of content should have uh a number that it has an outcome, right?

Is an outcome of some kind, even if it's you know a zero to one hundred scale, even if it's you know just raw number of uh clicks out to buttons that you care about on your website, something. The way you make a determination about KPIs is you do a regression analysis, you do a regression analysis on that outcome that you care about and all of the engagement metrics you have. And yes, absolutely for a given piece of content. If you can get likes, comments, and shares, get that data, get time on page, time in session, um uh number of clicks uh away to a page on the same site, uh, number of clicks off-site if that that's relevant, whatever information you can get. And what you are looking for is which of the metrics that you have, either alone or in combination, uh, have a mathematical relationship to the outcome that you care about, right?

So maybe time on page is a good predictor of whether that content helps nudge somebody towards a conversion. Maybe uh number of times shared or emailed to a friend. If you've got a plug-in on your website that can measure that, um, is a good predictor of the likelihood of a conversion down the road. That's how you do the KPI identification. And here's the catch with Erica's question.

Not everyone's KPIs are going to be the same. Right? Your content, my content, they're different, right? I guarantee they are different because we write differently, we may cover different topics, we for sure uh probably use different formats and different techniques, and as a result, the way that my audience behaves is the way that differently than the way your audience behaves. Your audience behaves very differently, probably, than my audience does.

And so when you run this analysis, you will probably come up with different KPIs than I would. For my site, it might be um time on page, because I write long dense articles and have videos embedded in these pages, right? You might have a very different type of content. There might not be a video on your page. So time on page might not be relevant as relevant to what moves the needle forward, moves the ball forward for your conversions.

So that's why you have to do this analysis. Um where does this data come from? As you've heard, it comes from Google Analytics or your web analytics package of choice, um, your social media data, uh, possibly your email data. If you're if you're emailing out your content, you may need to pull email uh click data in from your email marketing system. But whatever the case may be, um, you're gonna want to bring all this data together and do that regression analysis to figure out what has a relationship.

And then comes the hard part. Once you establish a correlation, you must have to establish causation. Just because time on page uh seems to be say uh predictive of conversion, you then have to test, okay. Well, what if you you're cranking out 1500 word posts, go and make some 3,000 word posts, double the amount of time on page, double the amount of page, you can double put the amount of time on page. And once you see time on page go up, do you then see a time-based change?

Meaning that once you start increasing the size of articles, uh page size, uh time of page increase, you then see a corresponding increase in the outcome you care about. If you double time on page and you believe that time on page predicts conversions, by doubling the page, do you then double the conversions? If you don't, if the conversions actually go down, then you have a correlation, but you do not have causation. That means that something else has happened. Uh there's a third variable, there's another source of data, there's another metric that may determine uh what really gets people to engage, but by in that doing that process, you may find that nope, there wasn't a relationship.

You may also find, again, when you do that first regression analysis, if there is no either Pearson or Spearman uh correlation coefficient above point say three, like point two five, point three. If everything's below that, you may have no correlation at all. Right? Which means then that you're missing data. You're missing information, you're missing a metric that could be a KPI, and you have to go and hunt it down, find it, figure out what it is.

You might have to do some engineering on your data to extract out things like time of day or day of week. You know, those could be hidden factors that you might not initially uh initially think, oh, I should put that input into my content engagement analysis. Figuring this out is tricky. Figuring this out requires a lot of detective work. But once you figure it out, you then know exactly which levers to pull to make your content more engaging for the purposes of conversion.

It's not just engagement for engagement's sake, it is engagement to nudge people further down your marketing operations funnel and get them to essentially do the thing that you want them to do. You want them to convert. Whatever conversion means in your world, you want people to convert, and this is how you measure it. So there's a lot of pieces you have to assemble. There's a lot of data you have to assemble together in order to get the answer that you're looking for about what KPIs should you measure.

But once you figure it out, then you're in really good condition to start testing and proving what what meaningful engagement is for your site. So, really good question. You got a follow-up question, leave it in the comments box below. Subscribe to the YouTube channel on the newsletter. I'll talk to you soon.

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