In the past two issues, I’ve covered the why and how of first-party data collection and understanding your audience. Now it’s time for some practical details: common content engagement data patterns for both web and email.

A few notes on method and my web analytics stack

I am a Google Analytics (GA) power user, and in my opinion it’s absolutely necessary for a content business to use GA as a baseline analytics tool. It’s free to use and learn. Adobe Analytics works as well, although it’s a far bigger investment (but if you work for an Adobe shop you often have no choice).

Some privacy-focused web analytics alternatives are on the market, but they don’t provide the robust and multilayered data of Google Analytics, which content analysis requires. If you’re a direct-to-consumer company with no content marketing arm just looking to move e-commerce products, one of those web analytics alternatives might be fine. If you are running a content business, you need more robust reporting capabilities to understand how people engage with content and not just purchase subscriptions.

If you are concerned about privacy, you can run Google Analytics on your site and not turn on the ad or data sharing features. You do not have to share your website analytics data with Google.

(If you are one of those people who starts with the assumption “Google is lying about its data sharing with Google Analytics,” I don’t know what to tell you. Maybe let’s talk? But in good faith and deep experience, you can use GA and still be privacy-minded. If they're lying, it's on them.)

If you’re interested in content analysis and don’t understand a word of the below tips, I’d recommend that you invest some time in an advanced certification in Google Analytics. It’s free! (Yes, that’s where they get you. Yes, it’s big tech. I still recommend it.)

Technical considerations for content analysis

This overview concerns Universal Analytics (UA), the classic GA setup that you’re likely still using. Google Analytics 4 (GA4) was released last year, but most companies haven’t switched or are still running UA concurrent with GA4.*

Setup for all scenarios: Set your dates in Google Analytics to look back at a year’s worth of data. If you don’t have a year, do a quarter or six months. You need at least a quarter’s worth of data for this analysis to be useful.

For the intent of understanding lurker engagement, we’re going to use above-average pages per session (PPS) as our barometer. It’s a default metric in GA, so even if you don’t have event and conversion tracking set up, you can still follow along. Typically greater than 3 PPS is considered highly engaged for most content businesses.

As with many enterprise software programs, GA offers several methods to filter data that ultimately achieve the same result. I typically use segments and predefined tracking where I can, but for the purposes of this piece, I’m adding screenshots of GA’s training wheels, the advanced filter report. That way, you can make yours like mine.

Two groups of the same wooden blocks are across from each other, anchored by one red block. They are not at all similar. From The Royal Tenenbaums.
"All right, Dudley. Make yours like mine."

If your business hasn’t, take time set up conversion and event tracking to make your data even more closely tied to business results. Some guidelines are at the bottom of this email. PPS is a great starter metric for measuring engagement, but subscriptions and conversions actually drive revenue.

*All of these reports are available in GA4 but with a completely different setup (that I haven’t entirely figured out yet). I’ll publish recommended content flows once GA4 becomes more common, and I've used the tool enough to gain confidence.

1. Opportunity to increase reader interest: Look for low traffic, highly engaged pages

Just like every woman has a freakum dress, every content-focused website has these sexy little gems hidden deep in their analytics, waiting for their big night on the town.

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