I’m active on Quora and got a request to answer a question that made me think. How would I, or anyone, figure out the average lifespan of an article with Google Analytics?
Simple enough, right?
Hold on. Let me explain:
When you look at this article from Parse.ly about the methodology behind analyzing the lifespan of an article, you’re reminded that the question isn’t as simple as looking at one report and just saying, this or that. The type of content you use is also important.
But this isn’t a scientific case study as much as wanting to understand just how valuable your content is to your reader. Fair enough. Here’s how I look at this.
Breakdown Lifespan Using Custom Reports
Before anything, I’ll start by saying that I’m not a fan of looking at just one metric in Google Analytics. You need two or more to even get a good handle on the answer you’re asking of your data. Just looking at bounce rate, for example doesn’t tell you much. You need another parameter to add context and meaning.
With that in mind, I thought about how I would describe the lifespan of an article in the most basic terms: How long after initial publishing of an article will it be attractive. When you look at it that way, your first thought would be traffic, users, visitors. But what about Average session duration?
When you look at traffic numbers alone, you don’t really understand much other than getting hits or views. Again, not helpful.
Take a look at the Date dimension along with a few metrics like Average Session Duration, Users and Bounce Rate and remember to filter using the URI of the page.
You’ll want to also look at which channels (direct, social, referral, paid, organic) may work within that as well. Say you’re running a PPC advertising campaign. A report like this could show you whether these PPC visits find your post attractive enough to hang around or not. That, in combination with you ad relevancy and landing page experience could lead you to make some adjustments if you find your content isn’t as attractive as it could be to your audience.
Analyzing Your Data
Once you run the report and see the table of data, it’s a good idea to export it to Excel. It’s far more robust than Google Sheets and if you ever have connectivity issues, Excel is local.
Now, I’ve shared that I like DataStudio. It’s terribly convenient when you want to just pull your live data and see how things are going. I’ve used it for former clients and it’s great.
However, the drawback with DataStudio is that it uses highly structured data. I can compare certain metrics if the system doesn’t deem it appropriate. I’ve run into that wall many times and it’s annoying.
If you want to be free to ask whatever question you want of your data, then using Excel is a must.
Again, bare in mind, content type matters. The Parse.ly test specified evergreen content, which is content that has a longer shelf-life and is great SEO for your site. If you’re testing any of the other three content types, seasonal, trending and general, is significant on your results.
One More Thing
While checking out the lifespan of the article, you’ll also want to keep in mind that your finding isn’t written in stone. You can, and it’s recommended that you do, update you content every once in a while. That freshness helps when your content is re-indexed.
Could that help with shelf-life? Sure. But again, the other factors mentioned may come into play.