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.
Share
π Upskilling In Web Analytics [2025 Guide]
Published 10 days agoΒ β’Β 7 min read
Use Data Or Be Used By Data!
β
The December 16 issue of Seotistics is here for you!
The new year is close and many of you want to upskill.
Whether you are a marketer or a data professional, it's always good to have more skills, especially during a recession.
I'll show you what you can learn and how to avoid spending time on topics you will never touch.
P.S. I prepared a small survey to gather some information on what I should work on next :3
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.
Really, having all the web data in one place makes a BIG difference.
Absolutely prioritize this!
DBT/Dataform
While Engineering is a separate discipline, this is a nice one to have.
I use both occasionally if there are specific tasks that require processing.
To keep it simple, these tools process your data in BigQuery and make them more usable.
Pick either and find some practical use cases, like:
transforming GSC data
unnesting GA4 data/breaking it down into multiple tables
Remember, you can simply use packages or solutions built by other people.
Now, SQLMesh is getting more spotlight but it doesn't really matter!
Learn what you need to carry out the job and you are done.
Coding (To A Certain Extent)
A lot of people ask me about coding in general...
because it's considered the hardest part.
Short answer: yes but not too much.
Analytics is NOT coding. β Analytics is NOT coding. β Analytics is NOT coding.
SQL is the 1st natural choice due to BigQuery (and because data is often stored in databases).
Then, you can choose one between Python and Javascript.
I went for the 1st due to my background, but if you are obsessed with GTM and Dataform, I recommend the latter.
AI made it easier, you aren't even required to be as proficient as before.
Back then, you had to be more involved with coding and I was every day on Stack Overflow.
Now? I hardly check it, Claude Sonnet is the best π―
Our job is about analyzing data and communication, simple syntax can get you quite far.
SQL and Python are well-documented... AI can write entire scripts without many issues.
Some "veterans" consider this taboo because they are afraid of change.
It literally made me save hours per month and immensely boosted my productivity!
What You Don't Need
It's easier to tell you what NOT to study because I was in this position years ago.
The shiny topics are the worst ones:
AI (complex models)
the Machine Learning you study in universities
I was lucky because I spent my college years reading good advice on LinkedIn.
Deep Learning and the "complex" models are topics I completely skipped because many companies don't need them.
At least, in the Web industry!
As my friend Ergest Xheblati (20+ years of exp. in the data industry) says, you need basic stuff everywhere:
The Web industry is a little bit quirkier but it's still boring and repetitive (great for making money).
Most of my work consists of:
framing business problems
deciding which data to use
running SQL to get insights (occasionally Python/R)
communicate them
prepare actions
See? No mention of strange models whatsoever.
You don't even need fancy degrees because it's all practice (and industry expertise).
Some of my connections went back to college to study topics that are outdated by now...
and no one really cares about the Web world in the academic world.
P.S. A good degree makes the difference (Engineering) but not the "cool ones" about Data Science lol
Lucky you, the basics will get you far, I saved you 1000s of $.
My Personal Experience
I started with a background in Business Administration and Marketing and then moved to Data/Computer Science.
So I'd say this is a great example of upskilling.
Back then, there was no reliable resource to learn from, it was pretty much all generic stuff and hyped content.
The most impactful skill is without a doubt understanding problems and marketing.
You can save so much money with the right mindset.
Don't start that project if the motivations aren't clear.
Avoid pruning half of your website because the "data suggests so".
This is what makes the difference with a mediocre data professional.
If you feel in doubt, remember this picture here:
You convert data (raw material) by giving it a meaning put into the right context that eventually leads to action.
It all depends on your understanding!
A Ready Roadmap
Like in RPGs, you can choose different paths.
While reality is more complex than binary choices, this is often true:
Seotistics is clearly on the left end of the spectrum as most of my content is about business.
You can follow the mainstream and become another half-engineer...
so the market will be saturated again and you will make even less.
Business acumen and having a clear mindset are underrated... β because many people won't even grasp them. β Yet, this is how you can make a concrete difference.
For SEOs, this is what's been working great:
Don't venture too much into Engineering topics unless you want to be overworked.
Most of those tasks will be handled by proper engineers (if not, there is a severe organizational issue).
I prepared the right path for you, don't worry:
[Analytics For SEO Course - v3]
If you want to be guided and start from scratch, this is the course for you!
This is ideal if you want to start the year with a competitive advantage.
You will:
β Use GSC and GA4 Data to their fullest potential
β Learn Python/SQL for your needs
β Get a complete blueprint for auditing websites
β Learn how to 10x your productivity
β 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!
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.
Read more from Seotistics - Web Analytics + Business + Strategy
Use Data Or Be Used By Data! The December 23 issue of Seotistics is here for you! Data is cool but what about decisions? In the end, we use data to make decisions and it's all about what we do later. I will show you some practical concepts of Decision Science to improve your daily tasks and limit uncertainty. P.S. I am still running the poll to decide which course to release next, go vote please! Please move this email to your Primary inbox or reply to it. This is to prevent Seotistics goes...
Use Data Or Be Used By Data! The December 9 issue of Seotistics is here for you! One of the most frequent questions they ask me is "how do we make money out of web data?". How is this even profitable? The mainstream industry won't help you because most content is tutorials. Seotistics will assist you, though. This is the situation after talking to many of you: 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...
Use Data Or Be Used By Data! The December 2 issue of Seotistics is here for you! Last time we saw metric trees and analyzed why visualizing your metrics is important. Today, I show you the importance of giving context to metrics! You can list down all the cool stuff you want but you need context! It took me a lot to write this one, let me know what you think of it! P.S. Before we start I remind you tomorrow is the last day of limited offers for my products! Please move this email to your...