Use Data Or Be Used By Data!

The August 12 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.

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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.

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:

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.

Data is not objective and doesn't stand for anything alone.

Learn this and you will be ahead of many people, even those working in data.

That's because data reflects our assumptions and measurements, that are human, you can't find them in nature.

This perspective allows you to build better products and think more strategically about data.

Otherwise, no one will use your products.

Being data is bad for your ego because a lot of stuff you do is based on feedback from other people.

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

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 if you think of how things were done before.

Saving 40 hours/month doesn't look impressive.

That would be 480 hours/year.

Assuming each hour is priced at $100, it's $48K less per 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 in action 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-

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 - v2]

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

A lot more about decision science will be added later on ;)

You will:

✅ Use GSC and GA4 Data to their fullest potential

✅ Learn Python/R/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!

P.S. (Ab)use the referral system and get additional discounts 👀

Learn Analytics for SEO Now!

How Can You 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 directing the energies in the correct direction.

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

The most common mistake is to learn Python and think you are done.

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.

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