Use Data Or Be Used By Data!

The December 1 issue of Seotistics is here for you!

The end of the year is getting close but companies are still failing in their Web Analytics initiatives.

That is, barring a few exceptions that do it correctly.

I show you which problems to avoid 👀

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📣📣 Important Announcements 📣📣

My product updates will be live by tomorrow at most, thanks for your patience.

You can even expect more in January 2026.

For those who are late, my special sales are still live with code "BF2025".

The deadline is December 3 👀

I am already working on my next content for 2026 and have some crazy ideas to share with the world.

What Can Go Wrong

This is what usually causes pitfalls in Web Analytics:

Most of these issues can be prevented and as you may have noticed, they are about people.

You don't have to fix everything quickly, the important is that you prepare the company for optimal conditions to produce value.

Data As Homework

The sneakiest of them all is when companies treat data as a separate entity from the business.

When there is this discrepancy, you can expect your data initiatives to miserably fail.

Oh yes, do that thing in GA4 and then we forget about it lol

Data is seen as something you must have because the others are doing it.

No strategic depth or willingness to improve, zero!

Solution: tie data to use cases and show what would happen without data availability.

Outdated Stack

I always mention it because you see outdated tools promoted even by other professionals for commercial interests.

A stack like this one below is simple and it just works:

I have talked about it many times, it doesn't have to be complex.

I've observed this problem with organizations infested by "veterans" and where the status quo is strong.

The incentive to modernize is low due to the people 👀

Solution: know what is "modern" and why it makes sense. Make it so convenient that they would be stupid to refuse your proposal.

Siloed Data

This is another plagues of Web Analytics because you get a lot of data saying different things.

I am not into Performance Marketing but that's quite common with paid data.

And also in all the other cases because not everyone even connects their source systems to web data.

Ecommerce: how to tie actual transaction to web data? GA4 revenue data is unreliable!

B2B: how can I tie my CRM to GA4? I don't only want traffic!

Solution: bridge data by asking the right questions first.

It's not like you need to actually combine every source, ask the right questions first:

It will be clear what to combine, where to find it and why.

For example, if you want to have a reliable measure of revenue per product, you can't rely on GA4 alone.

So you would start by figuring out:

where are the actual transactions sitting
can I ingest that data somewhere
how does it even connect to GA4

This is much better than realizing after years that you actually need more data.

This problem is also technical but trust me, in most cases it's because people let it get bigger.

Vanity Metrics

This one is a little bit better now, thanks to LLMs making people discover incredible topics like branding and common sense.

For years, inbound performance has been measured on views and traffic.

Needless to say, this is bad.

Solution: define what matters for your business (not so easy).

What many get wrong here is that they overdo it in the other direction: they only check l agging metrics.

For example:

full focus on revenue/net profit
only measuring facts

The problem is that telling you how much you made isn't actionable and measures the past.

So you need to consider other leading indicators like:

Traffic (without overdoing it)
Specificic events (e.g. PDF downloads, etc.)

Those are NOT your end goal but they affect your lagging indicators.

Without visibility or traffic, people don't buy from you.

Outdated Practices

And why do you think vanity metrics exist?

They are a legacy of the past, of professionals who don't want to let go.

Times change and so how we work.

It's super hard to convince "veterans" that we are in 2026.

Most don't get it, really!

This is why some companies do marketing like 2005 or have ineffective practices.

Another example is the anti LLM waave, which is absolutely stupid.

For sure, don't use LLMs for creative tasks or for writing B2B content...

but if you don't use it for coding, brainstorming and documentation, you are missing out.

This is the present now:

Asking to write code by hand during interviews or other bizarre stuff will make you hire the worst candidates.

LLMs are not the future, they are already used today and we use them!

I don't see why we should stigmatize what works wonders.

Solution: make crystal clear the gains of the "new" ways and use data to showcase differences.

Tools Over Strategy

Another classic is managers thinking a bunch of tools can replace a strategy.

For those who don't know what strategy is, I have a dedicated article on it.

The entire point here is that switching stack per se doesn't make you profitable.

Solution: hard to say, this requires finding the right companies and people. Can't be fixed in a month.

Broken Tagging

You know GTM is not my forte but I always check if we have a somewhat decent tagging in place.

Too many times I've seen companies redesigning websites and breaking a LOT of the tagging.

Solution: luckily this is mostly technical lol

My advice is to monitor your events over time (like from Looker Studio) and even go further and:

create tests in Dataform
you build your dedicated GTM monitoring solution / pay for a tool

This is something that requires consistent monitoring!

Poor Data Quality

Similar to the previous point but with some key differences.

In Web you can control how you track events... and you have 0 power over sources like GSC and BWT.

So, apart from GA4, where you can have quality issues?

When using 3rd-party tools or when stitching different data together.

I am talking about abominations like:

Combining Universal Analytics data with GA4 data
Combining GSC API with GSC BigQuery data
Combining (incorrectly) GSC with Bing Webmaster Tools (BWT) data

It makes sense engineering-wise but not really in terms of actual logic.

Solution: get to know what makes sense in terms of business and marketing. Develop domain knowledge... but it takes months/years.

Or involve domain experts.

Is It That Bad?

Over 2025 I'd say many virtuous companies have realized they needed to change their ways.

I've personally worked on a big data modernization project that took up a lot of time and resources.

And you know what? Better late than never.

Now I can proudly say that it works and many people will use what I worked on 😎

My based advice is the following:

not every company is ready to embrace good practices...
but you must know which are these good practices

So make it easy and always focus on what you actually deliver.

If the company you work with is unsavageable, walk away. Really, there is no reason to spend your time on what can't be fixed.

And if you want to learn even more about these topics, this is for you 😎:

Become a Top Data Analyst Now!

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Our Discord community offers a small place where we can talk business and web data.

If you hate all the noise of social media, then this place is for you.

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

This is the best way to stay updated in real time on Seotistics:

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🔎 Analytics For SEO Ebook - Course / Ebook

Remember about the offer 👀

You will:

✅ Use GSC and GA4 Data to their fullest potential

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✅ Get a complete blueprint for auditing websites

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I teach you what's needed to go from 0 to a professional Data Analyst.

Even if you leave SEO, the foundations are the same for other jobs!

P.S. Update coming tomorrow (at most).

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Also in ebook with the new update releasing tomorrow (at most):

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📚 Recommended Reads - Peak Content 🗻

Read no more than:

As usual, my most recent LinkedIn content is here.

❗️ Feedback and Recommendations

If you have ideas/recommendations for the next issues of Seotistics, you can simply reply to this email.

Marco Giordano
Data/Web Analyst

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Bernerstrasse Süd 169, Zurich, Switzerland
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How (Not) To Fail At Web Analytics