You Ask, I Answer: Measuring Lifetime Value of Content?

In today's episode, Will asks, I'm currently thinking a lot about measuring the lifetime value of blog content. Curious how much you've looked into that and what your thoughts are on the value of that exercise. So lifetime value um is really uh it is a good exercise, it's a valuable exercise. You can look at um built-in measures like page value. In Google Analytics, you can see what the value of any given page is uh based on how many conversions it participates in and what the value of those conversions are.

Where a lot of people run into trouble is because they don't have conversions and conversion values set up, that data's not in the application, and then you don't know how much it's worth. But if you know, for example, that even in a B2B setting, if you know what the value of a marketing-qualified lead is or even a prospect is, then when you generate prospects on your digital property, you know what that's worth, and then you put that in the system, and the system goes through and it creates those values for you, those valuations for you. Um, I think that's a very valuable exercise to see what content participates the most in conversions, which is really what that tells you. How we uh this content participates the most in conversions, and therefore um you should focus on it. And I think that's the part that lifetime value exercises miss, is once the software or your computation method is done, you then have to figure out well, what do we do?

Like what does this information tell us? What should we do next? And the the two things there that computation should do is one guide you to as to improving the value of that page by optimizing it some more, right? Um revamping it, adding more content if it's appropriate, doing a lot of A B testing or multi uh multi-objective optimization testing on the page with tools like Google Optimize or Optimizally or you know any of the A-B testing tools that are out there. And two, changing up your promotion strategy, right?

If you have a page, say on your blog that has an extremely high page value, much higher than all the rest of the pages on your blog, that should be at the front of the line for the recommendation engine. When somebody's on your blog and they're reading, you know, you might also enjoy that most valuable page should be at the top of the you might also enjoy list, right? That page or collection of pages should be featured in your emails. Every single uh issue of your email newsletter, say, hey, some additional content you you might like to read. And you send more traffic to those valuable pages.

Um in social media posts, those are the posts that those are the pages that you should you know share more often in case you missed it, right? In case you missed it, here's this page that we know converts at a much higher uh value rate. Uh running ads. You should be running ads to those pages and see if the traffic numbers hold. That's one of the things that we do.

Um I have a piece of software that I wrote that looks at a page's conversion efficiency. How many visits does it take to that page before somebody converts? And when I find pages that seem very efficient, then we run some marketing campaigns to those pages, get some extra traffic to them, and see if that conversion number holds, see if it continues to convert very efficiently, or if it loses that because you know uh the analysis just showed what it was doing in the background, not when it was put in the spotlight. But that those exercises are what the real value of these lifetime value exercises are. The content itself and the exercise itself doesn't do anything, it doesn't help you if you don't do something with the information afterwards.

I would start with the built-in page value exercises. I think those are uh perfectly fine calculations as a starting point, and you don't need to install any additional software. You just need to use Google Analytics for that. Um, then consider up leveling to the more sophisticated stuff, like um uh we use machine learning to do the computations for the pages that uh most frequently assist conversions and then the that conversion efficiency analysis. Uh and those are more sophisticated analytics techniques, but they're better for helping us understand, like, yeah, this page is just not converting.

Right. And if it's a pillar content, you know, like uh a page about data analytics on my company's website and is just not converting. That's conversion efficiency is very low, uh, it's its rank in the most valuable pages report is very low, then we know we got a lot of work to do to fix up that page to get it to meet the expectations of both the search engine, because a lot of the times it's uh searches are a strong driver of content to those pages, of traffic to those pages, and the user does it satisfy the user's intent. And it has been my experience that pages that have very low conversion efficiency, it's because they don't satisfy user intent. A user gets to that page expecting one thing, it's something else totally different, and they're like, Well, this is not what I wanted, and away they go.

So make sure that you are clear as you do the exercises, what actions you will take and what decisions you will make based on the information you find. If you don't have that written down, if you don't, if you are not clear about those actions and those decisions, don't bother with the analysis. Uh because it's just going to waste your time. Uh I am a big fan of a quote by Seth Godin uh who says, you know, when it comes to analytics, if you're not going to change what you eat or how often you exercise, don't get on the scale, right? Because you're all that number's going to do is make you feel bad, and you're not going to change your behaviors.

So you can't, you're not going to make that number better. Right. So if your in-house marketing strategies and tactics and things like that are not going to adapt based on data that you gather, don't gather the data because it's not going to change anything. Right. Instead, update your LinkedIn profile because that organization's doomed.

Right. Um, if you have people who are so data resistant and so analysis resistant that they will not make decisions when confronted with data that is unfavorable or whatever, that organization's going nowhere, right? And any success it has is purely luck. So uh that's what to do with that. It's a really good question.

Really good question. Thanks for asking it.