Use Data Or Be Used By Data!

The May 11 issue of Seotistics is here for you!

So, you have some web data but have no idea where to start or what to do with it.

Don't worry, the majority of companies out there are in the same spot.

Rather than understanding why this happens, I will simply tell you what you should do now.

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📣📣 Important Announcements 📣📣

You can now preorder my new course at 30% off until June 15, the official launch date.

This will be for Analysts or everyone wanting to explore Web Data in general, not only SEO.

The course is split in 4 amazing modules:

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

Aaaand... I will speak at MeasureSummit on May 13, you can get your tickets here.

There is also a free tier 👀

And yes, I will talk about data modeling and complex stuff, new topic!

Using Your Web Data Today

Most of the businesses I talk to struggle with basics.

Another portion has the basics in place but can't action their data.

Finally, a very small segment has heavily uses data, that's usually the field of aggregators or businesses who live with web data.

In all the other cases web data is an afterthought.

So now I've prepared this simple tier list to show which actions (based on your web data) have the most impact.

Most companies today sit between D and E.

The good news is that today it's relatively easy to jump straight to A with the right information.

The F + E Tiers

I mean this is a meme tier but jokes aside, Bounce Rate and similar engagement metrics in GA4 do more harm than good.

That's because many have never read the Google documentation or think this data is even accurate.

Among the least useful activities we have analyzing data with AI.

It looks so convincing and correct until you actually validate the results.

There are also cases where AI does give you solid analyses but they usually require a skilled Analyst to begin with.

The D Tier

This is where most companies sit actually.

Spending hours of the week on manual exports and using outdated tools!

If you still export your GA4 data to Excel, I have good and bad news for you.

Good news: there are better and easier solutions.

Bad news: you need to learn quickly because it's 2026.

All this effort just to report on some traffic metrics that often barely affect the bottom line.

The C Tier

This tier is also quite common and where companies that are a little bit more experienced sit.

A shiny tool or being very good at GA4 don't solve much.

Even an agency doing the perfect technical work (apparently) doesn't help much.

OK, you have server-side tagging and you track events... now what?

In fact, this is the illusion of being good at Analytics without doing the extra work.

A complex dashboard or investing in tools won't increase your profits or boost efficiency.

Also because dashboards are often free technical debt at this stage.

But compared to other actions we saw, this is something that can be fixed.

It's more about redirecting these efforts to more lucrative activities!

The B + A Tiers

Some years ago I remember spending hours and hours with the Google APIs and the output was terribad.

I had to setup some Python script to extract the data, then compare it with the UI and finally stitch it.

But then the data was stored nowhere so I just lost time lol

A good first step in the right direction is indeed using the APIs (better than the UIs).

As you see, technologies like Python sit at the top but are by no means foundational.

And after using them, you'll immediately realize they are limited and clunky.

This is the point where you realize that you need actual engineering and modern practices for a reason.

You can check my blog and all the past Seotistics issues to find infinite examples of BigQuery with GA4 and GSC data.

That's important because you don't need to use weird APIs and you own your data.

The S Tier

At this point, you've made it, or you are just aware of the right actions.

Some will be shocked to see that the best actions you can take for Analytics are simple and kinda obvious.

TAKING ACTION is where many fail!

Because it's boring, unglamorous and let's be real, not what companies love doing.

One of the favorite pictures in data books and for a reason. This is a mythological concept as not many actually reach the top of the pyramid.

Among these topics, you clearly see metric trees, which I covered extensively in the past.

This is where you domain knowledge makes a BIG difference.

Which is also why most job offers today are more tailored and less "generic". Generalists have no clue about what we do.

The reason why I started writing is that most of the Web Analytics content back then was shallow or too technical.

Now the situation is different and there are great colleagues talking about the business/marketing side of it.

Different Business Models

As I always say, the use of data DOES depend on the business model.

I don't expect complex data work with a publisher or a small B2B business.

Now take a medium-sized Ecommerce or a competitive B2B SaaS... the situation is different!

The tools and the data is largely the same but with some key distinctions:

For Product Analytics (aka software businesses), you may work with Amplitude or Mixepanel
Ecommerce/Aggregators have much more data points and that's a constraint

In my enterprise experience, the challenges are visible, like spending a lot of money for queries or waiting for minutes.

So it's also about size and maturity of the company you work for.

In all of this, I just want to end this issue by saying LLMs are actually nice and not bad if you are competent.

But again, they don't solve the core issues we just described, they simply make you better (if you are good at your job).