Use Data Or Be Used By Data!

The February 24 issue of Seotistics is here for you!

It's easy to build a dashboard in Looker Studio and call it a day.

What about a complex project with many moving parts and different teams?

The advice I give you today is practical but niche because not many tell you about the dirty reality.

Please, remember to check out my previous issue first because this is the sequel!

P.S. New course preorder is out and 30% off my other products until next Tuesday, go check them out!

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📣📣 New Course + Discounts + News 📣📣

You can now preorder my new course at a 30% discount until launch (May 12)!

It gives you all the missing business and marketing skills I mention when talking about Web Analytics...

including the FULL content of the topics in this newsletter.

If you purchased my previous course, go to this lesson here and the last section contains a special promo code for you:

My other products are also 30% off ("Analytics for SEO" course and the ebook) if you use the promo code "FEB25" at checkout (valid until March 4).

Some of you got a special email with an even better promo code...

Next week I will attend the Winter Data Conference in Zell am See on March 7.

P.S. Some of you got a special discount... be sure to check your inboxes 👀

P.P.S. Don't forget to follow the LinkedIn page for Seotistics.

The Overview of the Seotistics Framework

This framework is based on all the projects I did and formalized recently.

Before I wasn't managing all the steps but now I have a much broader view.

You can get the full insights and learnings in my new course.

Most of what's in here is flexible, the important is that you understand the core concepts.

As mentioned before, please check my previous issue for more details.

Requirements

Get the requirements right and you can continue with the rest of the project.

This involves some of the concepts we covered last time, like:

asking stakeholders what they actually want
questioning the request
guide stakeholders

In most cases, you won't have doubts about the data sources to select for your use cases.

You don't need anything fancy, write the requirements down wherever you wish as long as it's clear what you want to achieve.

Framing Problems (Ideation Once More)

This is my favorite step because you can get quite creative.

Many struggle with this because they aren't trained in Marketing or Business...

and this is where Seotistics helps you.

The idea is to figure out what to do with data. Normally, it shouldn't happen like this.

You first define problems and then gather the data sources that are required to solve them.

The other side of the coin to consider is action.

You can build all the dashboards and reports you want and still go nowhere.

You need to understand how actions, processes and systems can increase business value.

Simply put, it's utter chaos without systems.

Engineers often do the mistake of thinking this is about technology and databases...

and not only those.

The core component of every process will always be people.

Listen to the meme. Web Analytics and Business are about people.

Yes, even fully automated processes involve people because there is a human stake.

Some people are interested in this form of automation to achieve some goal.

Strategy-wise, I've talked about this topic in this article on my website.

Testing + Pilots

This is super important, if you get this phase wrong, you are done.

You need to get comfortable with MVPs. Build the barebone of what is required and let your users decide if it's worth it.

If you become a perfectionist and make the super complete version, chances are you it's harder to spot mistakes early on.

Once you get feedback, iterate over the MVP and build a new version.

This will also make your users more involved.

Recently, I applied this exact reasoning to some PowerBI dashboards I was working on.

Instead of making them perfect, I asked 2-3 users to give me their feedback...

the final result was great!

Before you create anything, gather the most common questions people ask.

If people want to know the list of events on their website, this MUST be answered in your data product.

User Feedback Is Life

I like to get feedback early on to gauge expectations and have some user stories on my side.

This is what you should make sure to get out:

is my data product easy to use?
is it working as intended?
does the user like it? Or they didn't get the answers they needed?
is access management working correctly?

You don't know how many times I found mistakes in the access management or even with dashboard usability.

All of these mistakes can be prevented easily.

Analysis - Revisited

The last time I talked about moving from questions -> actions, which is the biggest takeaway from this stage.

The analyses I did were covered in this other issue instead.

Analysis is still the underdog of Web Analytics but it's the MVP in other industries, like:

Business
Finance
SEO (yes, audits)

Literally the opposite of what we notice in Web Analytics...

people love their audits.

There is a subtle difference though:

Audit: tells you what to fix, uses historical data, can be technical. At the same time, you have content audits that sit in the middle.
Analysis: starting from complexity and ending with a simple output. Exploring your data is one example but also answering specific questions with data.

You can use the 2 terms interchangeably because many don't care about semantics.

What you should care about is that Analytics actually focuses on generating better questions.

Simple questions you can easily answer, e.g. how many users did we have?, but complex stuff requires Statistics and testing.

Luckily, most Web Data projects require simple efforts and the real challenge lies in Data Engineering and Business.

If you want to learn the hard skills to analyze and audit websites with SEO/GA4 data, this is the course for you (under limited offer too):

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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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✅ 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!

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A Recap of the Models covered before

This picture serves as a recap of what we discussed the last time:

ask the right set of questions before you start
understand the business model with a logic model
build a metric tree to decompose the business model
model the data accordingly
define problems and possible solutions

This approach is quite conservative and structured but prevents a lot of disasters.

If you don't feel sure about a data project... it's better NOT to start it.

Every penny you lose, it's more expectations you failed to meet.

Most use cases don't even require complex data, just common sense.

Designing Success

As you have noticed, we try to frame problems properly and then build the simplest solution possible.

My mental schema when thinking about all of this is:

Problem(s): which problem(s) I want to solve.

Goal(s): what I want to achieve exactly.

Audience: who is the audience of my work.

KPIs/Metrics: how I want to measure my work.

Data products: can I build something or I don't need to?

I am working on the full blueprint for my new course, if you are interested, you know what to do 👀

👥 Join Our Community

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.

Join our Discord Community!

🔥🔥 Analytics For SEO Ebook (v8) - 30% Off 🔥🔥

💴 Promo code for 30% off: FEB25. Valid until March 4.

If you want to learn about Analytics for SEO and prefer self-study, this is for you!

It will teach you or your employees to:

👉 Prepare audits that make sense and are actionable 🔥

👉 Avoid common pitfalls that cost you money 💸

👉 Create analyses that add value and money💯

👉 Move the needle faster with efficient SEO systems ⏳

This comes with periodical updates to keep the content fresh.

Unlock Powerful Insights Now!

📚 Recommended Reads - Peak Content 🗻

These Analytics books are among the best out there. If you want to think like a true Analyst, look no further.

Logic Model Development Guide
Strategy + Web Analytics: How To Tie Data To Results
Data and Analytics Strategy for Business
A Business-Oriented Framework For Web Analytics
Solomon Kahn's newsletter - great newsletter about data leadership
Ergest Xheblati's newsletter - evergreen content on data as a whole
Analytical Skills for AI and Data Science : Building Skills for an AI-Driven enterprise
Data Literacy In Practice
Becoming a Data Head
Storytelling with Data

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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Seotistics - Web Analytics + Business + Strategy

💥 Building Use Cases & Web Success