It's officially the busiest month I've ever had since going freelance five years ago, and I am annoyingly joyful about it. I'm deep into audience research, user interviews, audits, reports, competitive analysis, all the activities, and it feels glorious.

A full slate of client work means that original content will likely be limited for the remainder of the year, but I'm aiming to update the newsletter all-timers, collect past content in guides like the one below, and add one new review per month. I'm also allowing myself unplanned off weeks, so if you're wondering where the newsletter is, I'm resting, dammit.

I doubt you've been paying close attention to The Content Technologist's editorial calendar, but I share where I'm at, like a girl apologizing to her diary, on the off chance a reader is following along like a disgruntled Yelper.

If you want an update: before the end of the year, I aim to finish what I've started as far as video courses, which includes returning to a reconfigured Let's Build a Website and revising Understanding GA4. More than (key)Words and Your Content Is Your Marketing are now available, but the measurement and content strategy chapters are no longer in the production schedule. As I noodle on meaty client challenges, I don't have the brain space to cook up much of anything new. Also, I admit that I went a little overboard in my embrace of video. (One reason I am joyful: I'm not actively in sales or promotional mode, and neither am I constantly editing videos of myself. I can just kinda be.)

So! Let's start the show: A guide to everything The Content Technologist has ever written about content analytics, a subject near and dear to my heart that I encourage you to explore, even if you think you hate "metrics."


A guide to content analytics: Measurement for people who deliberately chose careers that weren't supposed to involve math

One of the core tenets of this 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.

Content performance and email benchmarks | The Content Technologist
Digital user data availability will change. Here’s how to take a benchmark, using Apple Mail’s recent privacy changes as an example.

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

Google Analytics 4 content engagement metrics | The Content Technologist
Google Analytics 4 measures engagement differently than Universal Analytics (the previous version of GA). Here’s what content professionals need to know.

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

How to read Google Search Console Insights | The Content Technologist
GSC Insights is an automated dashboard with content-focused data from both Search Console and Google Analytics, along with some brand new data that Google has never before offered as a default calculation.

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

The best metrics to track for Instagram, Facebook and TikTok
Social media stats can indicate problems ahead. Can’t remember when you last looked at the numbers? Today’s the day for your social media health check-up.

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.

Gathering audience data from your content | The Content Technologist
Data management is a part of your life as a content professional. Learn why content marketing and digital publishers should have a content-based data strategy.

A data collection strategy is necessary before analysis.

GA4 Adjust Engaged Session Timer | The Content Technologist
If your website focuses on content for readers or viewers, change this back-end setting in Google Analytics 4 to better understand your most valuable audience.

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

Measuring brand lift with organic GSC data | The Content Technologist
Measure PR and ad effectiveness without pricey brand lift studies. This brand media measurement approach uses free data your organization likely already has.

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

4 content engagement analytics patterns | The Content Technologist
Want to learn more about how your audience engages with your content? Here are 3 Google Analytics setups and one email metric to watch.

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

What’s a good web content engagement benchmark? Adding sophistication to your analytics approach
In digital content, measurement remains a massive boondoggle for most organizations. Here’s our reliable, replicable method for measuring high-quality content.
Competitve content analytics scorecard | The Content Technologist
To evaluate competitors’ content strategies and success, I’ve developed a four-point competitive scorecard that provides clients with just enough data to understand how owned organic content performance compares to similar sites.

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).

Making impressions a thing of the past: Grounding your content performance data in reality
Everyone else’s numbers are inflated, but your own data is your gold. Learn to trust your owned data and make decisions with verifiable performance metrics.

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

What to measure instead of pageviews | The Content Technologist
Pageviews suck. Sessions aren’t much better. How will you measure content better in the 2020s?

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.

The Netflix content engagement KPI | The Content Technologist
Measuring for eyeballs is for chumps. Especially if you care about content.

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

What is bounce rate? | The Content Technologist
In 2020 western digital culture has clearly established that words do not mean what you think they mean. The disinformation phenomenon doesn’t just apply to politics; it applies to any digital news or marketing or even entertainment content in spades.

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

From engineered content to informed editorial: Blazing new trails in digital publishing
With data science and algorithms being panned into binary, good-versus-bad narratives, where can we find clarity and room to experiment?

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.


  • Academic researchers found that one of the best ways to combat misinformation is to educate people about how algorithms work, in NiemanLab. Yes! Media literacy! Combat folklore!
  • Speaking of folklore, intelligence researchers are advising tech marketers and the industry in general to critically examine metaphors used to describe AI, per Tech Policy Press. Loud applause from my corner, especially around what the article names as the Productivity Myth.
  • Content Technologist alum Sam Thielman reminisces about the millennial glory that is/was Homestar Runner, over on the very cool Flaming Hydra.
  • "Journalist is bewildered and cynically enthralled at a tech conference" is a trope that gets old fast, especially if you've attended more than a few tech conferences or watched Silicon Valley, but Laura Dattner navigates the convention hilariously for n+1 at what sounds like a batshit AI tradeshow featuring an abundance of specious behavioral science and applied statistics.
  • Zuck had all the advantages of going to Harvard but never took a class from Homi Bhabha, and as a result his company failed to meet basic thresholds of cultural understanding required to "connect the world." Of course it has consequences for the product and the people who study the product. Here's a study from the Center for Democracy & Technology (via Everything in Moderation) on Colonialism in Content Moderation Research.
  • "Choosing a brand to buy is a deeply social process, regardless of whether you are buying sauces or SAASes" is the most delightful B2B sentence I've read all week, in this excellent explanation of why brand stories matter, in Attention Matters, a newsletter from the fine folks at Storythings.

The Content Technologist is a newsletter and consultancy based in Minneapolis, working with clients and collaborators around the world. The entire newsletter is written and edited by Deborah Carver, independent content strategy consultant, speaker, and educator.

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Cultural recommendations / personal social: Spotify | Instagram | Letterboxd | PI.FYI


Did you read? is the assorted content at the very bottom of the email. Cultural recommendations, off-kilter thoughts, and quotes from foundational works of media theory we first read in college—all fair game for this section.

Threads is extremely strange and confusing, but internet journalism legend Katie Notopolous has been trolling the algorithms to brilliant effect.