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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Stereotypes In Analytics & Where To Find Them
Published about 21 hours agoΒ β’Β 6 min read
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Use Data Or Be Used By Data!
The March 9 issue of Seotistics is here for you!
Today we talk about some of the most common stereotypes in (Web) Analytics.
And no, I am not just talking about the tools... we go deeper!
I will give you my 2 cents about some related topics too.
This is a great time to work but you need to stay sharp and upskill yourself!
P.S. Will send a special offer to my loyal readers soon + announcing news soon π
Please move this email to your Primary inbox or reply to it. This is to prevent Seotistics goes into spam by accident. Gmail users can read this tutorial to do it.
My new course about Analytics will be available this week for a preorder.
Those who voted will receive special benefits.
This will be for Analysts or everyone wanting to explore Web Data in general, not only SEO.
The topics I am planning to cover are:
Coding in general (Python, SQL, R - all aided by LLMs)
LLMs and how to use them properly
Auditing websites and deeper business considerations (so not only SEO)
The topics covered in this newsletter
If you forgot to vote and want to be included in future communications, please contact me.
I will speak at MeasureCamp Milan on March 21, let me know if you are going too!
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P.S. I may consider presenting twice!
βοΈ Some articles releasing soon on my website π
Now let's start the issue!
"You must be good at Math"
Some people told me "I am a creative person and bad at Math".
OK that has zero truth and is unrelated to Analytics too.
It's amazing how much brainwashing the education system can do.
A creative person isn't automatically bad at everything that involves numbers.
Analytics isn't even about Mathematics, no one will ever ask you to solve integrals.
A common reaction to most of the stereotypes you will read in this newsletter.
You can think of it as the art of dissecting things and making the right decisions.
I've taught pretty much anyone and it still applies.
You don't need to limit yourself mentally.
"You Must Use Python and Love GA4/GTM"
Most of you have been brainwashed into thinking that you are not a true analyst without Python.
Most of us have never touched Python lol (well I did but I am an exception)
The lingua franca of data is SQL, which allows you to interact with databases.
As predicted 2 years ago, the modern needs now have evolved and companies actually ask for more.
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While it's true that not every company uses GA4... in most cases they will and it's the dominant player.
GTM I don't use at all as I've always delegated it to someone else...
but it's true that a generalist should know it, no excuses (I am a specialist though).
If you are in PPC/SEO/Growth/Product, then you have much more fun with data.
In fact, it's common to work with other data sources, such as:
Google Search Console
Crawl data
Log files
Shopify/Woocommerce
CRM (Salesforce/Hubspot)
CMS
This is a paradox, specialists playing with more data sources than many generalists!?
There is much more than GA4 in life!
Don't miss out on opportunities just because you were taught one tool.
This leads to the next point...
Web Analytics Does NOT Solve Issues
This is my main issue with generalist Web Analytics, it hardly solves any issues.
You see dashboards, cool apps, 10Ks of trainings paid for GA4 (companies pay for that in 2026) and more questions than answers. π
This is because there are many paths you could take:
GA4 + GTM robot (purely technical and limited by tools, slowly fading)
Domain specialist (you know your stuff)
Mixing Analytics with Engineering
Needless to say, the best option is to always be closer to the business (Domain Specialist).
Who do you think will be preferred for a complex Ecommerce project: a guy with Google tools knowledge or someone who spent 15 years playing with Ecomm data?
You don't know how many agencies completely lack this awareness.
They do the perfect setup that no one will ever use.
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The reason is that most lack the business context and are unaware of what companies need.
So they stick to "safe topics", i.e. technical stuff, to bring home some money.
This mindset isn't good long-term because you need to make yourself indispensable!
"You Must Code & Clean Data All Day"
In most cases an analyst talks to people, frames problems and is full of meetings.
Yes, you can't be a good analyst as a shy person, forget about it.
You'll have to repeat yourself many times and work on your communication.
"Most of the data work is cleaning!"
This is also false crap from cheap textbooks or online courses.
It's completely misleading and outdated.
Data modeling in general is needed. You can easily tell which company is outdated based on how they keep their data.
This was a popular take years ago when the data field just started and we didn't have data engineers.
If you spend too much time cleaning your data, it means you have severe issues in your organization.
This is why one of the first things I do with new businesses is to setup the stack correctly.
"LLMs will eliminate Analysts"
Anthropic released a picture showing the impact of AI in specific industries.
Cool picture, in reality, it doesn't mean anything (yet)
As usual, people on LinkedIn started panicking (nothing new) for absolutely no reason.
LLMs as of now help a lot with the most annoying parts of the job like:
writing code
building MVPs
But they completely fail at 2 key things:
being independent (you should know that machines are by definition unable to start by themselves, right?)
abstract and "original" thinking
LLMs are part of the current meta so you MUST learn them or be familiar with some use cases.
I've talked a lot of times about the wonders of Claude and Gemini.
The issue is when you start obsessing over the details and spend more time on LLMs than Analytics.
That's a bad thing to do!
"My company already has a good setup "
You may think that most companies are informed and already have the basics done...
well, you would be severely wrong.
In most cases, you will have to repeat yourself many times, like in most jobs.
This is also good because it means problems exist and you can solve them.
What is NOT true is that every business model is the same.
There are discrepancies between a B2B Saas and an Ecommerce, and what about publishers?
My advice is always the same: get familiar with business models and growth.
This won't affect your GTM skills but will really impact how you look at data.
The Most Valuable Lessons
So the idea is simple, you must master the foundations and go beyond.
As usual:
Google Stack
Coding
Databases
Business/Marketing
This is what is super important and allows you how to differentiate yourself.
That's also why I am launching a new course, to bridge the missing technical skills that many skipped in favor of GA4 and GTM.
And if you want to upskill in terms of thinking, organization and management, I have the solution for you:
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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