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:

c'mon do something | C'MON, GIMME SOME ROI | image tagged in c'mon do something | made w/ Imgflip meme maker

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📣📣 Weekly Announcements 📣📣

I will be attending the Google Search Central event in Zurich on December 12, see you there!

For my SEO readers, I want to remind you that Majestic finally released the "SEO in 2025" book:

(I was featured with my tip too 👀).

UK link: https://www.amazon.co.uk/dp/B0DPMHSRRH/

USA link: https://www.amazon.com/dp/B0DPMHSRRH/

Start From Questions

Many companies don't really know what to look for and they need guidance.

Start with questions or objectives like:

We want to know what are our best pages and what we can do about it
What's the most profitable time of the year?
How can we improve our engagement on LinkedIn?
Is there any way to get more leads?

Once this step is clear, you can figure out where you can find the answer.

Exploratory analysis is fine.

In most cases you want to start with questions, goals and hypotheses, though.

This tip will make your life easier.

Yes, you can look for the data sources that answer your question.

If you want to know what are your best pages for Google, GSC will surely help.

Want to know about all the channels? Use GA4.

Want more information about your leads? Maybe Salesforce can help.

The table below will help you:

And before you embark on a Web Analytics project, consider the following questions:

If your client/project doesn't allow you to answer most of these, ditch them.

You can rush to execution but the result will be terrible.

It's important to understand what's been done before and what the current situation is.

Once you have this knowledge, you can plan and execute.

This is already more than enough!

Asking the right questions adds immense value to your decisions.

Data As A Product

Data is not sorcery or the absolute undeniable truth.

You'd better consider it as a product, meaning that the focus is on the final user and not on the data per se.

It's finalized to serve some goals and not to be self-referential.

Keep in mind that this concept is not absolute because:

people don't know what they want... listing requirements isn't enough
Analytics is research first!

Building Stuff

You are not always required to build stuff to create value but you will notice that this is often the case.

Dashboards, apps and even forms of automation are your ways of showcasing the value of data to others.

Reports are part of the equation too but who is even reading them?

In most cases, it's all about slides, videos and other forms of communication.

A big part of data is about communication, not simply building.

This is why you need to always keep honing your social skills... or else you can just become an Engineer lol (irony)

Estimating Profits

A big misconception that is sold in Marketing is that money can only come via revenue, sales and that's it.

If you are large enough, you can actually save a lot of money and consider efficiency as well.

The best example in history is provided by Microsoft Excel.

Its productivity boost has revolutionized the world, especially when you think of how things were done before.

Saving 40 hours/month doesn't look impressive.

That would be 480 hours/year.

Now we have the opposite problem, Excel is causing mess and bloat.

The idea is that being faster at something gives you:

the ability to allocate your resources better
more tempo
a competitive advantage over others

If Process A takes you 100 hours/month and my automation takes only 2 hours/month...

would you say this use of data is not profitable? Ofc not!

All of that time saved means less money you need to pay in the future.

It also means you can better allocate your energy and efforts.

Some Examples

There are infinite examples we see every day of how web data makes companies money.

The first notorious example is provided by SaaS, we pay for tools because they are convenient and save us time and money (in theory).

Semrush and Ahrefs are 2 big players that make money with web data and help with research.

Lee Foot's apps are always great examples of products.
Link here: https://leefoot.co.uk/portfolio/lightweight-streamlit-google-search-console-app/

Those are 3rd-party data though, I prefer using my private stuff.

A lot of nice apps like Clustering or even automation for PPC and analyzing social media comments do help companies.

You can say that the value of data is tied to the outcome, not just the output.

Many big companies have custom internal tools they use every day.

You can bet these add a lot of value considering how much they use them!

Scaling processes > 1 analysis sitting inside your Excel

Changes Across A Large Company

So we have said that most data use cases are better with a large company/website.

If you deploy a dashboard that will be used for critical processes, 2 things may happen:

no one will use it, very common
you integrate it within a process and make it work

Option 2 is the most favorable (who would have guessed?) and the one producing actual value.

The rest of the work is all about documentation and boring stuff that everyone hates to do.

This is an example of how you can map problems to potential solutions. This isn't only for SEO!

A good dashboard does help with monitoring issues and going in the right direction.

The same is even more true for custom tools and proper reporting.

The point of no return happens when these products are treated like the ends and not the means.

If you want to master these aspects of data and coding as well, you can check out my course:

[Analytics For SEO Course - v3]

If you want to be guided and start from scratch, this is the course for you!

Especially for making value out of web data...

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!

More Is Better Than One

I still see companies and agencies relying on ONE data source for important decisions.

For example:

Data pros using GA4 and ignoring GSC, GAds and all the myriad of data sources
SEOs using GSC and ignoring GA4
Content Marketers not using their content plans to augment their data

The picture below is a great summary of what you can do with your existing data sources:

Only log files are fine if alone.

The other data sources should always be used with others to make actual sense of what's going on.

Evaluating an Ecommerce performance with GSC data alone is a disaster.

You are excluding what actions people take on the website and product data!

The same goes for GA4.

If you rely on it for every single analysis, you omit important channel-specific data.

For example, GA4 doesn't tell you anything about your queries or rankings.

Elite Team

Web data is essentially Marketing data.

I've talked to countless agencies and a good chunk of them missed this important aspect.

They built a lot of dashboards with vanity metrics or even worse, filled with technicalities.

But how could a marketer use them!?

There is often 0 care for processes and real usage.

The reason why I obsess over the concept of Domain Knowledge is that data without context is 🗑️.

While building data products, you need to know your craft.

An elite team of marketers and business people makes a real difference.

That's why I often teach marketers analysts how to become analysts and rarely vice versa.

Web data suffers from several problems:

ambiguity
tracking
accuracy

A strong knowledge of the industry is enough to use the data properly.

My personal experience (and yours too) is a testament to that.

How You Can Start Today

I always include this section because I want to create something actionable for my readers.

Develop mental frameworks
Learn some coding
Get your communication straight

It's a mix of technical and soft skills, both must exist.

Working with purely technical people is problematic for requirements and planning, as well as focusing your energies in the correct direction.

People with 0 tech skills are good at talking but not much in executing.

The most common mistake is learning Python/SQL and thinking you are done.

No matter how many times I say it, people will still get this wrong.

Then learn the mistake and get back to the basics.

Don't be like those people, go beyond a simple tool.

Avoid the extremes and you will be OK.

The usual picture I post tells you that you need to tie your insights to actions, otherwise it's fluff.

The other mistake on a company level is treating the data team like a service desk. ❌

If you think data work is building dashboards and models, you are completely wrong.

Sure, you should also work on that but you are a business partner first!

The more you perpetuate the stereotypes, the more you will get to do the service stuff.

Most of the content I read in Web Analytics is unfortunately focused on making you a nice tech guy.

Nothing wrong with it but it's not enough to add value and communicate to stakeholders.

The Short Recap

If you have come this far, you deserve a summary of how you can use web data:

to improve your decisions
to save time and costs
to discover new revenue opportunities

In most cases option 1 allows you to get everything else.

👥 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)

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 🗻

Some nice peak resources for you to read:

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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💸 Monetizing Web Data & Adding Business Value