Use Data Or Be Used By Data!

The Jun 2 issue of Seotistics is here for you!

When I switched to Analytics I wasn't prepared to the amount of brutal change brought by LLMs.

And now I love it even more!

Unfortunately, many professionals are still tied to their old ways because "it's always been like that".

I am here to show you how to upskill to survive in the future (and make some money while at it).

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To come next:

"Analytics for SEO" ebook v9 (I swear, this one soon 👀)
More additions to "Analytics for SEO" course
More content for "Think Like a Web Analyst"
Freebies (one already out)
Articles

I am taking my sweet time as I was busy playing with LLMs and revamping my content calendar 🔥

The Industry Before

When I started studying data, the buzzword "Data Science" was everpresent.

Countless universities rushed to create useless curricula teaching you Machine Learning, Data Science and related topics.

This legacy is still alive in the form of those fast-food courses you see teaching you:

Machine Learning methods
Pandas + some Python
Statistics and Calculus you don't need

which completely miss the mark of our daily jobs.

Web Analytics has always been its own thing, you can say the "black sheep" of the family.

Extreme isolation and living in the Google bubble is quite similar to the SEO/PPC worlds.

This means the vast majority prepared on topics like tagging and preparing reports in GA4 but ignored all the rest.

What Didn't Work

Many companies hired technical people with basic knowledge of Python/R/SQL, convinced that Data Science was a cool thing to do.

What they didn't know is that most of their budget would never come back 💀

People with no clue about the business and 0 software engineering knowledge can't add value to a business.

Companies realized it and started laying off.

Imagine spending millions in data work and then you can't even make money out of it. Do you see why companies got more picky now?

This wave didn't really hit Web Analytics, since many companies are more concerned about tracking and setup.

And what about the actual analysis?

It actually happens, but specialists carry it out, like SEOs, PPC, Growth and Product specialists:

I personally put analysts and marketers in the same bucket as Analytics for me is more of a complementary skill.

Engineers are a different breed for sure but if you are on the analyst side, then why don't you also study business and marketing?

You'd be surprised by how many agencies I've talked to that aced GA4/GTM but failed to create meaningful dashboards or even metrics!

Winds Of Change

Since the introduction of ChatGPT, things have started to change.

What at first was a cool toy became a mainstream phenomenon (allegedly) threatening Google.

Sure, a search engine doesn't get replaced by an LLM, they are quite different.

Still, with the advent of more competitors (like Anthropic and Perplexity), people have started to rely on LLMs even more.

I am one of those people.

The thing I've always hated about coding in some languages was the amount of boilerplate and manual work.

This is now gone today.

Cursor can quickly generate whatever you want and do it much better than any human.

As pointed out in my previous newsletters, LLMs are capable of wonderful things.

AI/LLM Proficiency

This is a topic where companies are ruthlessly wasting their budget.

I’ve been talking about AI/LLMs in the last Seotistics issues (check reads at the bottom) and the answer is always the same.

What you need is balance, having a good enough understanding of which tools to use.

Understanding how LLMs work will NOT affect your Analytics skills in the slightest.

Still, you need to be comfortable with Claude and Cursor as they are too good.

A web app like this in minutes and with the super cool retro style I like 😎 But you folks keep spending hours on prototyping 👀

Remember, no one cares about how you do the job.

You don’t ask your plumber how they fixed your pipes.

LLMs unlocked a completely new level of speed that wasn’t possible yesterday.

The Resistance

Change is never approved without casualties.

There are some people, the "veterans", who claim things have always been in a way and will never change.

This is true to a certain extent.

LLMs are objectively superior to most analysts writing code and they are faster.

Sure, having a strong background in SWE makes a big difference, it's not like machines get it all.

When in doubt invest in the "gold" of data, SQL!

What You Can Do Now

There is plenty of time to adapt, luckily.

Every week there are new changes but the underlying idea is still the same: solve problems, make other people money.

Nothing exotic here.

You can choose 3 paths:

The 3rd path would be being a hybrid of some sort between the 2 extremes.

I'd go for the left option and double down on "humanities" as this is what machines can't really do.

For us in Marketing and Business, this is super easy.

People working in super academic industries (e.g. Pharma) have a harder time getting it.

For my favorite audience, SEOs, I've updated my SEO Analytics roadmap:

As you see, the only real difference is that SQL comes after Python since a lot of data they work with is NOT in databases.

But if you often work with large websites, you should do SQL first and master the BigQuery integrations ASAP.

The Seotistics Vision

As said many times, Seotistics stands closer to the business and empowers people.

Technical skills are mere tools to achieve this.

Rather than using the improper term "soft skills" we should say "human skills".

If you want to be just another Analyst, the market is crowded.

This is different if you treat Analytics as a discipline, like I do.

You combine it to your existing role rather than dedicating your entire career to it.

In this way, it's much easier to adapt and be flexible.

"With AI specialists will die"

Some people who believe in this crap

The notion of AI being able to answer specific questions is rooted in nothing and you can test it yourself.

The argument of generalism vs specialism is still valid.

The important is understanding your market and how well either can help you develop YOUR value proposition as a professional.

The Birth of the Data Web Analyst

As I often sign myself as Data/Web Analyst, I think others should too.

In my very humble opinion, the following skills are key:

Domain knowledge
Statistics
Some coding
SQL
Data warehouses

Don’t fret, most of these you need at a basic/decent level.

It’s not like you should invest thousands into them.

I’ve taught countless professionals and the answer is always the same: learn only what you need.

One of my most recent students for my newest course. It's clear that traditional roles are slowly shifting into business-led ones.

I don’t recommend SEOs to work with more than they need. What’s the point of learning X and Y if then you can’t rank pages?

I don’t recommend Analysts to become the next Philip Kotler unless required.

After all, an analyst isn’t tasked with marketing but needs to know what's going on.

How can you analyze web data if you don't even know marketing? 🧐

You need to find that balance and stick to it.

Given what I just said, I've created this course as a way to upgrade beyond the typical "Web Analyst":

Become A Top Data Analyst Now!

Redeeming "Human" Skills

We unjustly dub skills as soft as opposed to hard skills, the cool ones, like coding.

I say this is nonsense and doesn't reflect reality.

Abilities like:

Embracing chaos and making order out of it
Abstracting problems
Building systems

are extremely profitable and don't involve any technical skill.

This is why in my recommended reads I sometimes put books that are unrelated to Analytics or unconventional.

True human skills will always matter and be relevant.

👥 Join Our Community

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🔎 Analytics For SEO Ebook - Course / Ebook

You will:

✅ Use GSC and GA4 Data to their fullest potential

✅ Learn Python/SQL for your needs

✅ Get a complete blueprint for auditing websites

✅ Learn how to 10x your productivity

✅ Learn BigQuery to work on large websites

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!

Learn Analytics for SEO Now!

Also in ebook:

Unlock Powerful Insights Now!

📚 Recommended Reads - Peak Content 🗻

Read these peaks:

My LinkedIn Content:

❗️ 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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