How to measure SEO content success in the age of AI? Stick to business fundamentals.

How to measure SEO content success in the age of AI?

Nothing like a simple question, right?

A while back, I made some alterations to my website and consulting business, focusing less on “SEO” and broadening instead to a “holistic marketer” focused on brand storytelling.

The reason was simple: I felt the age of search was giving way to new habits in the age of generative AI.

This wasn’t only informed by my own searching habits, either. I also came across articles like this one, where a user says the same thing — they’re swapping out one for the other.

All of this creates havoc for SEOs trying to measure content performance.

There’s some talk of metrics like “share of model.” There are also studies like this one from Apple showing how variable LLM responses can be.

And as I showed in an article about Perplexity, that traffic isn’t counted as organic in GA4.

I’ve been doing SEO for nearly a decade, having spent 8+ years in digital agencies.

Here’s how I typically saw content measured:

• Clicks, Average Position, Impressions, CTR at the query or page level from Google Search Console.

But how useful are these metrics in the age of AI? I say not very.

Aren’t there third-party tools available to measure AI Overviews and even AI model mentions, though?

Well, I recently did an exhaustive content audit for a medium-sized business with a healthy blogging habit.

My initial takeaways using third-party SEO tools went completely out the window as soon as I got my hands on their first-party data.

That’s not to say third-party tools aren’t reliable. It is to say, I wouldn’t stake my final performance notes on them.

Here are a few things I did learn about measuring SEO content in the age of AI …

Stick to the fundamentals at a business level. 🤗

• Active users, average engagement time, and conversions at a page and device level.

It’s tricky when we’re preconditioned to see the world in terms of keyword rankings, but these are obsolete in the age of AI.

It’s also tricky when we’re preconditioned to see the world in terms of organic traffic, but that’s not the only referral source SEOs should care about now.

Nor is traffic itself that important.

I often use Perplexity for content topic research, and in auditing those results manually, I saw a lot of visibility for my client … but not a lot of traffic potential.

However, by analyzing the top-performing pages from a business case, I was able to reverse engineer where users are engaging the most with the site topically, and how that should inform a future content calendar and strategy.

I wouldn’t ignore the traditional metrics around organic traffic, as they do hold value. They’re just only helpful in a limited sense.

Focus more instead on active users, average engagement times, and conversions at page levels, especially.

These can better inform the value of your SEO content in the age of AI.

Until next time, enjoy the vibes:

Thanks for reading. Happy marketing! 🤗