AI Measurement: The Final Issue


Use Data Or Be Used By Data!

The July 6 issue of Seotistics is here for you!

This is the last issue talking about LLM measurement.

I will cover some of the last details because this topic has been covered a LOT.

Then, I will start drafting one of the many articles I promised you πŸ‘€

If you are still postponing studying LLMs... I have bad news: they are everywhere.

It's also true that AI Search as of now looks like Sci-Fi in terms of measurement (it doesn't exist yet).

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πŸ“£πŸ“£ Important Announcements πŸ“£πŸ“£

My new course is out in case you missed it:

The course is split in 4 amazing modules:

βœ… GA4, GSC and other data sources: how to use them
βœ… LLM Workflows, BigQuery, SQL & Python
βœ… Dataform & Pipelines
βœ… Real Use Cases at work

I will speak at Belgrade SEO in September:

Use the code "MARCO" to get 25% on the ticket at checkout, see you there!

The Limitations of Citations & Mentions

The last time I mentioned citations... which are useful overall but could be misleading.

In fact, you can be mentioned without being cited... that is still a win in my book!

This is why I recommend looking at both. Results from 3rd parties will naturally include mentions of different brands with the citation (the source) of one website.

Use them as an indication of whether you are picked by LLMs.

Remember, you want to be visible for some core topics you define or people won't choose you.

The Different Models

As mentioned last time, models greatly differ to each other.

AI Mode for example cites a lot because it acts more like a research assistant and a Google extension.

If you've ever used Claude, you'd know it tends to be more conservative with web searches.

You'd tend to use the metrics from the past issue for both, though.

Regardless, the 2 have very different use cases.

My advice is to avoid obsessing over details and overoptimization because you will commit a lot of mistakes.

Treat LLMs as "similar" just to avoid overcomplicating your thought process.

P.S. If you remember the Claude Code leaks, the of a page is ignored which means no schema.

This was already obvious sooooo, nothing new.

Attributing Results To AI

You may have heard (or not) about incrementality as a way to measure the real impact of a given channel/source on revenue.

This is NOT easy at all because it requires companies to have a proper setup and system to track it all.

In the proper conditions, you could:

  • apply very specific changes to a page and measure what happens compared to a page without them
  • compare between specific regions/areas
  • compare with user groups

This is close to impossible in reality and most tests we read are Sci-Fi.

The big limit of Organic is that you can't switch it off (unlike Paid).

Well, technically you (partially) could by noindexing your website πŸ’€

In reality this is super hard to replicate and you can't even have holdouts with "GEO".

You can't instruct an LLM to ignore a brand as a test...

Where you can focus today (not many did so far) is your CRM.

It's super beneficial to understand the basics of tools like Salesforce and HubSpot.

Say you work for a B2B company... you use AI and SEO to bring you leads.

Then, you ideally move from leads to actual business opportunities.

Even though a CRM doesn't solve the issue of measuring AI Search, you can measure variations.
​
By analyzing your sales pipeline you learn more than what GA4 tells you.

According to the latest research by Similarweb that we analyzed in the 2 previous entries, people run branded searches after AI exposure.

That's a good piece of info that doesn't help us with measuring though.

Measuring direct traffic is also a dumb idea for the reasons I listed in the past.

Content Logic: Explained

The biggest issue with content is that it's still considered homework by companies.

You need to content to rank on search engines and be visible.

Which is correct but it's a horrible mindset to craft art.

This is also why I dislike working with publishers compared to years ago... because now with AI the entire business model is collapsing.

Drawing the direct connection between content and results is impossible.

Think of content as the mirror of your value proposition.

You do content to articulate your value to people and help them solve issues.

To be perceived as an authority in a field, you need to make sure people remember and cite you.

This is why I write content rather than just sending spammy emails or attending conferences.

What Fails Today

I see 3 main problems behind why companies can't produce good measurement (and therefore decisions).

  • data storage
  • processes
  • people

Data storage is one of my most common topics as this is super needed and easy to do today.

Without data retention, it's impossible to analyze data and make meaningful analysis (check my resources).

The 2nd issue lies in the processes.

Companies barely think about optimizing how they work and often rely on legacy tools.

This is how corporations work, Enterprise Analytics is on a whole different level of complexity.

Still, LLMs now cost peanuts if you don't use Anthropic or OpenAI models.

I am surprised many of our colleagues don't lock themselves in their room to play with AI.

The opportunities are endless and a lot of legacy processes can be radically changed.

Speaking of which, I recently discussed how Fable 5 (Anthropic's model) is overhyped.

The model has been severely nerfed and costs a LOT.

The final issue is... people!

If SEOs refuse to upskill and analysts refuse to learn marketing/business, organizations will never move forward.

Beyond The Data

So as you have noticed, I myself don't believe much in all these new frameworks and methods used by people.

That's because in industries like SEO but even Web Analytics, you can count on your fingers people with a strong marketing background.

Brand didn't suddenly became important and "content for the users" is not a new thing.

The truth is years ago you could get away with it easily because Google wasn't punishing you.

Why even expand your knowledge or test if you can make money with the bare minimum, after all?

I've recently had very positive results in terms of actions/recommendations with tools like Waikay (topic reports).

I confess I didn't try all of the others apart from Semrush AIO (Enterprise).

Even without a tool, LLMs with proper tuning are super good at giving you advice and analyzing content networks.

The next issue will cover a topic you are familiar with from a new lens.
​
Can you guess which one?

πŸ‘₯ Join Our Community

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I will start posting more there as we have a forum channel now.

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πŸ“š Recommended Reads - Peak Content πŸ—»

Read these peaks (again):

As usual, my most recent LinkedIn content is here.

❗️ Feedback and Recommendations

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Marco Giordano
​
Data/Web Analyst

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Seotistics - Web Analytics + Business + Strategy

The Seotistics newsletter is written by Marco Giordano, a Data/Web Analyst with the goal of combining business and web data. Tired of the usual boring Analytics content without any business impact? Seotistics teaches you how to use Analytics, web data and even content in your workflow while helping you with Strategy.

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