A guide to content analytics: Why content professionals should care about their metrics

A core tenet of The Content Technologist newsletter is that nothing about internet content is particularly sophisticated, and even the most advanced researchers and practitioners are still galaxy-braining what it all means. This newness goes triple for data science, a comparatively recently invented discipline rooted in monolithic 20th century assumptions of behavior across cultures.

I advocate for content professionals to understand and engage with measurement because most of the statistical models and measurement methods out there are either extremely basic or highly over-engineered, with not much middle ground. The tech industry continually undervalues practices related to "meaning" and "words" and overvalues advertising and market manipulation as a means to business growth. Like it or not, it's up to us, the people who enjoy making things, to advocate for what we value and to value what we create. We must, on a base level, understand our numbers. Otherwise, an adversarial "they" will short us because "they" can.

Senior editors in legacy publishing are responsible for understanding their performance analytics. Digital content strategy is an editorial discipline that distributes the same types of information on giant calculators. Therefore, it's only natural that we content people should have the same ownership of our inputs. Understanding analytics gives content professionals a seat at their table, a way to converse with the math machines, and argument fodder to make better choices about what works and why.

The content analytics I advocate don't require a higher level than eighth grade math skills. The real key is knowing where the numbers come from and knowing how to read a basic graph. (Frankly, people in all information production professions need to be better at reading and producing graphs.)

As a rule of thumb for all digital measurement: if you can't correlate the metric with a human action, it's probably not worth your time to track.

Without further ado, here are far too many newsletters about content metrics and where they come from:

The basics: Learning to measure like a professional

Google Analytics (GA/GA4) and Google Search Console (GSC) are essential tools for all digital publishers and will be the standards for the forseeable future. Yes, there are other analytics tools, but GA is by far the most accurate in zooming in on actual human behavior.

Benchmarking against your own performance is an essential skill that will help you monitor performance improvements and changes.

If you read only one GA4 post, read this one.

If you've never explored Google Search Console, be prepared to be amazed by the level of insight you can find there.

Emily's post on social metrics remains a banger.

Intermediate content analysis: When you're ready to notch up that performance

Got a handle on your basic analytics? Awesome. Stretch your muscles with these exercises.

A data collection strategy is necessary before analysis.

If you publish content, make this change in your GA4 admin to get a more accurate read of who is actually paying attention.

You can measure literally any marketing effort, online or off, with Search Console data.

Your lurkers are your most valuable customers. Learn to read them without surveillance. Make yours like mine.

I don't advocate for competitive analysis often, but it's helpful to know where the other teams in your league are hiding out.

Traffic sucks: If you measure pageviews you're doing it wrong

I've written at length at why I hate pageviews and the entire idea of measuring traffic without context. Pageviews do not indicate anything meaningful about audience behavior and encourage lowest common denominator pandering. Meaningless traffic also has nearly zero correlation to successful business performance—quality lead gen, subscriber acquisition, etc.—no matter how many marketing bros tell you otherwise.

If you don't believe me or the below posts, read Traffic by Ben Smith, which I believe is about how traffic is a bad way to measure media performance (I think... I couldn't get through more than the intro because Dottie, I lived it).

From just a few months ago: please let's just let the impressions go!

You could make a custom metric like the one described in this post. Or you can just used Engaged Sessions in GA4, which is pretty much the same thing. It's almost like Google was reading The Content Technologist to get ideas for their GA4 metrics (they weren't).

The theory behind the analytics practice: Deep thoughts on measurement and analysis

I enjoy waxing poetic about the origins of measurement models and whether they relate to actual human behavior. The essays below are this newsletter's most popular traffic-wise (it does very little for business performance!), followed by two of my all-time favorites.

It's still The Content Technologist's all-time most popular post... and needs a third update because Netflix keeps moving the target again.

When two completely different metrics have the same name, I start quoting Gertrude Stein.

A good part of my first digital strategy job involved watching Buzzfeed from afar — mostly with admiration, always with lots of questions about how exactly they were making money. Turns out they weren't!

Content measurement remains an incredibly necessary but widely misunderstood discipline, and I've clearly no shortage of commentary on the practice. There will be more! But in the meantime, if you're looking to gnaw on the numbers, the above should suffice.

A guide to content analytics: Why content professionals should care about their metrics

The basics: Learning to measure like a professional

Intermediate content analysis: When you're ready to notch up that performance

Traffic sucks: If you measure pageviews you're doing it wrong

The theory behind the analytics practice: Deep thoughts on measurement and analysis

A guide to content business models: Choose your platform like a professional