From Web Data ➡️ Products & What Pros Think


Use Data Or Be Used By Data!

The October 7 issue of Seotistics is here for you!

Using web data is cool but what about delivering something?

I will show you how and why to deliver products to your audience.

3 data professionals were so nice to give us their opinions on the topic!

If you don't know how to present your data, this issue is for you.

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📣📣 Important Announcements 📣📣

Thanks to everyone who attended my brightonSEO talk about BigQuery and GSC data to get actionable insights!

You can find the slides here.

❗️My learning material got crazy discounts:

  • 50% discount on my ebook (until October 12)
  • 30% discount on my course (until October 15)

I have added some more content in the past week and planning on adding even more!

Adding Actual Value

Actual value is hard to quantify if you are used to thinking in terms of raw numbers.

Data can add value in multiple ways:

  • by reducing costs
  • by improving efficiency
  • by unlocking new opportunities that lead to more revenue

If you think about them, it's quite simple to get some ROI out of data!

For example, one of the best ways I added value in the past was by identifying which pages didn't serve the website.

Of course, this process does NOT only consider one channel, you have to consider everything.

Content pruning executed properly is good at reducing fixed costs and can, occasionally, improve organic performance.

Another example is how I used my international cannibalization framework (described in both of my products) to monitor a nasty SEO problem.

In that case, the solution was easy but the problem was gnarly.

Data alone doesn't work if you don't know what to do in your industry.

It all boils down to business knowledge in the end!

Many are attending Udemy courses or even going to college again to learn new technical skills.

That's cool but remember that understanding the context takes practice.

Most of my daily work is understanding the business and the context of data.

You'll realize why understanding an industry is important once you actually work with data.

The Product Approach To Data

For this reason, some people like thinking of data as a product.

Data products can be used to add value with the end user in mind by addressing specific problems.

The DAAP (Data As A Product) approach consists in treating your data as manageable assets:

If you are analyzing some web data, you want to ideally serve this information to your audience.

What about a dashboard?

Yes, a dashboard is a product and it needs maintenance.

Like Balazs Vajna, Head of Analytics at MarketingLens, says:

Like with all data solutions (e.g. dashboards), the most important aspect of a data product is how it drives business decisions or how it contributes to the business process.

It is this process that harvests the value.

If no action is performed based on the output of the data product,

or this output is not directly used by some downstream process...

the ROI will not be realized!

P.S. Balazs will be speaking on MeasureSummit this week about Google data transfers to BigQuery, subscribe here for free.

With A Caveat

Yes, data can be considered a product but be careful.

My friend Ergest Xheblati, a data professional with 18 years of experience says:

There are 3 tiers of value for data teams:
-Measuring performance accurately
-Research & Development
-Data-powered automation

The first and last fit the product lifecycle but the 2nd is an exception!

P.S. Subscribe to his newsletter on patterns.

Analytics is mostly research and exploration, the product approach doesn't really work at this stage!

Once you have understood what there is to understand, you can follow the product approach.

As per measuring performance accurately, remember that in Web Analytics, you will never get great accuracy.

The majority of the data we work with is accurate enough to make useful decisions.

But accuracy and value are not the only thing to take into account!

Adam Ziolkowski, Marketing & Data Consultant for Ecommerce, says:

One of the biggest issues when trying to turn data into usable & practical dashboards/data products is the lack of common language between:
- Data/Analytics teams
- Marketing/Business teams
Therefore, people able to understand both worlds (e.g. analytics translators) are bringing tremendous value to the table.

When analyzing a website for the 1st time, you need to figure out what really matters.

How is the website making money?

Based on that, it's easier to figure out what to crawl and what to focus your attention on.

When Solutions Replace Problems

If a stakeholder comes to you requesting a dashboard, something is wrong.

A dashboard is a solution, not the actual problem they are trying to solve.

It's better if you tell them which solutions they need.

In most cases, you can send emails or quick information instead of creating a data product.

Can you create a dashboard for this?

Well, saying NO is part of the job.

Output Types

Dashboards aren't the only way you can showcase your prowess with data!

Scripts: most of the stuff you find on social media is loose code. You run it on your machine (or on your cloud) and that's it.

Apps: pretty much like scripts but you have an interface and some nice features.

Dashboards: do I even need to explain them?

Reports: if you can't really summarize your findings and need to go into detail.

Notebooks: for analyzing websites, you can either use Google Colab or Jupyter Notebook.

Canvas: it's like a notebook but better. It's literally a canvas where you can drag and drop components, tell stories and show a process.


To be fair, most of the time you can just send emails with what people need, really.

I don't work much on scripts or apps because I need to do 1-off explorations or write SQL code.

Once you start getting used to data, you will get familiar with notebooks and less with spreadsheets.

Notebooks give you infinite freedom and are ideal for dissecting and transforming data.

I still open stuff in Excel to inspect it but notebooks are omnipotent.

If you want to master notebooks and level up your data game for SEO data, my time offer for my course will help you:


🚨🚨 [Analytics For SEO Course - v3] - 30% Off!!! 🚨🚨

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

Not only technical skills but also the soft skills you need to excel.

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!

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


The Average Workflow For A Marketer

You don't need to try ALL of the output types I described...

you can get away with much less!

The process I recommend for content auditing can apply to any channel and for the majority of use cases:

I have to play with canvases a little bit more because as of now, I am only relying on notebooks, dashboards and reports.

The reason is that canvasing software is usually paid or expensive, but notebooks aren't.

When training other people, we always start and end with notebooks!

In general, this is most of the coding stuff you need for Web Data:

How It (Inefficiently) Works Now

Companies pay expensive agencies to implement dashboards based on irrelevant data.

How often have you seen the following:

  • vanity metrics
  • bounce rate, avg. position
  • pie charts (ugh)

This is the bingo of bad web dashboards.

Sure, they may look cool but they don't serve any business purpose.

And you have also seen:

  • Using API data for both GSC and GA4 (instead of the BigQuery exports)
  • Semrush/Ahrefs instead of GSC for your query data (ugh)
  • Tracking generic events
  • Setting them as key events

This loop creates a load of data products that will never be used and will only create more costs.

Against The Mainstream

Most of Web Analytics focuses on technical skills and very very marginally on business value and marketing.

Companies care about money, though.

This is why knowing more business is absolutely crucial for winning the game!

Technical skills are always important but those are implicit.

Soft skills aren't obvious at all!

The Referral System

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This comes with periodical updates to keep the content fresh.

📚 Recommended Reads - Peak Content 🗻

The usual reads I recommend to everyone:

🗣 Some Brighton Talks + My Comment

This brightonSEO edition was super cool!

Thanks to everyone who attended my talk and made me feel appreciated.

It was a huge success (and I didn't expect it lol).

Once again, you can find the slides here.

Some technical talks caught my attention:

  • Lazarina Stoy's talk on ML for SEO. A lot to untangle and some nice ideas! Slides here.
  • Giulia Panozzo's talk on testing. An advanced topic explained perfectly and with some nice '90s references. Write her for the slides.
  • Myriam Jessier's talk on what to measure. A lot of important concepts to remember! Slides here.
  • Gianna Brachetti-Truskawa's talk on robots.txt and GSC, slides here.
  • Manuel M. Maddeddu's masterclass is a nice summary of Core Web Vitals. You know it's not my favorite topic, so I never really studied it lol

    Slides here.

P.S. No LinkedIn content this week since I didn't post anything new lol

❗️ 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

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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