Use Data Or Be Used By Data!

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The September 30 issue of Seotistics is here for you!

It's 2024 and many of you always ask me what to focus on and why.

I love being blunt and showing you how to add business value.

If you want to upskill, this is the time.

Let's go over some web analytics tools/sources/skills and what YOU can do to learn the game.

P.S. I've announced some important time-limited offers below!

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📣📣 Important Announcements 📣📣

I will be at brightonSEO this week, reply to this email if you want to meet up!

Stay tuned on October 3, 1.30 pm GMT, Auditorium 2 as I will talk about BigQuery.

❗️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!

Coding (Python, R, SQL, Javascript)

You are not strictly required to learn coding in Web Analytics but I heartily recommend you to!

LLMs like Claude can help you write good code that gets stuff done.

Back then, it was so much harder and I struggled a lot.

There is no reason to not exploit AI to learn faster, especially the basic code you need for data analysis.

Unlike gurus claim, you don't need a high level of coding or a perfect understanding of Python/SQL.

If you really have to focus on one, start with SQL, it's the lingua franca of data.

Javascript if you are into GTM and R if you like data visualization or stats....

but there is no actual hard rule, right now 99% of my job is SQL!

The GA4 Madness

People didn't really like the GA4 launch... and for a good reason.

It's barely usable for non-technical people.

There are some competitors like Piwik Pro, Matomo and Fathom...

but GA4 has a direct connection to BigQuery and a bigger market share.

A decent knowledge of GA4 involves:

• Understanding how scopes work
• Creating custom dimensions/events
• Setting it up properly
• Being able to interpret the default reports (at least)

Google Search Console

A good chunk of my audience is SEOs but this tool should be used by EVERYONE.

If you are evaluating a website from an Organic standpoint, you can't miss it.

GA4 gives you information on events and all the channels, so it's more important.

But... it doesn't have data on keywords aka queries.

There isn't much to understand here, although I have a lot of content on the topic.

If you start considering SEO data as Audience data, you will make the most out of it.

Google Tag Manager

GTM is one of the most popular topics because you need it for too many reasons.

Mind you, I am not well versed in GTM as it's not my main priority.

Some focus excessively on tagging and completely ignore the analysis side.

For many, basic knowledge is enough...

I google how to use GTM often because I've never had the necessity to become proficient in it.

Google BigQuery

Now it's a must because you can get the best GSC/GA4 data with a click.

APIs tended to be the best choice back then but the meta is different now.

This is all explained in my article on how to combine GSC and GA4 data.

Getting a good knowledge of SQL is a must because it's the most common language in the data industry.

Luckily, it's one of the easiest tools to learn and you don't need to go that deep.

The GA4 linking is definitely one of the hardest to learn because the data looks messy, chaotic and it's honestly confusing.

GSC is quicker to understand, luckily!

P.S. Google Ads data is also valuable but I don't know much yet so I will talk about it in the future! (Same for social media)

And if you want to learn more about Analytics for SEO data (including GA4), I have the course for you at a 30% discount!

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

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

This is all you need to learn the trickiest data topics in SEO (but also the basics).

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 Data No One Cares About

Web Analytics isn't only Google tools (duh) because they don't give you the full picture on your website:

• Log files (from your server)
• Crawl data (Screaming Frog, Sitebulb)
• Backlink data (Majestic, Ahrefs)
• Sitemaps

I am not a big fan of sitemaps because they are usually confusing and not even accurate.

Log files, if you can ever get access to them, are the true MVPs.

You can track everything, including bot behavior.

Crawl data is needed to assess the structure of a website, as well as get valuable metadata like Title Tags.

Before you remove pages, it's recommended to check how many backlinks you have on each.

Some of these tools often get relegated to the SEO bubble but I disagree.

Any Web Analyst should be mildly familiar with these concepts because they are about the website as a whole.

If you come from such a background, I recommend this article.

ContentOps & Content Auditing (Airtable, Notion)

Content Auditing is one of the most common tasks yet it's not a common topic at all!

For this task, you need a decent level of SEO understanding first but also a clear picture of the other channels.

My 8-step process works for any website:

You can't rely on one channel in 2024, it just doesn't work anymore.

Speaking of which, try Airtable or Notion for your content planning.

Most likely, Airtable.

You need a content inventory to store your content data and information, as well as to manage operations and workflows.

If you are heavy on content websites like me, this is a nice skill to pick up.

The New Era Of Web Analytics

I agree with what my friend Adam Ziolkowski said:

Web Analytics is now evolving and it's not just about paying for the nth course in GA4 or GTM!

Companies have more complex needs and it's now time to develop holistic skills.

If we look at more specific industries, the situation has changed too!

I see a lot of nice work in the PPC community, although I don't have any strong connections inside it.

SEO-wise, it's clear that the hype behind Python is getting redimensioned toward more sustainable skills.

This is thanks to the huge shift caused by AI!

As I always say, focus on the business and use the tools as a means to achieve your goals.

What Is Wrong (And How To Avoid It)

Learning the right topics isn't necessarily a good thing!

You also need to avoid the wrong things like:

• becoming a code monkey
• overcomplicating the straightforward
• being obsessed with shiny things

Anyone with real data experience knows that most solutions should be easy, not complex.

In Marketing, it's often the other way around.

The coolest things are easier to sell because they look complex and necessary.

But no one cares in practice!

If you want to walk the right path, it's often about:

• asking the right questions.
• selling your solutions to your audience.
• figuring out the ROI/benefit. If there is none, quit it.
• solving actual problems. Vendors create problems out of nowhere.

And if I could only choose one it would be asking the right questions.

Beyond Data

The data industry is now much more mature compared to 5 years ago.

Now the topics have less hype and it's easier to learn properly.

Luckily we are past the era of Udemy certifications but be careful when reading content online...

it's hard to find the signal in all that noise.

I hope you have figured out that Analytics is not about hard skills but domain knowledge and how well you can communicate.

Sure, you are required a minimum of hard skills... but those will not make you stand out.

The Referral System

Refer Seotistics and get rewarded! Refer Seotistics to get amazing rewards: Your referral link: [RH_REFLINK GOES HERE] 🎁 Refer 3 Subscribers: Get tagged in a LinkedIn/X post 🎁 Refer 10 Subscribers: Get included in the next issue of Seotistics as a supporter 🎁 Refer 25 Subscribers: 25% discount for Analytics for SEO [Ebook] 🎁 Refer 50 Subscribers: 50% discount for Analytics for SEO [Ebook] 🎁 Refer 75 Subscribers: Free copy of Analytics for SEO [Ebook] 🎁 Refer 100 Subscribers: 1 hour of consultation 🎁 Refer 125 Subscribers: 25% off my Analytics for SEO Course 🎁 Refer 150 Subscribers: 2-hour consultation 🎁 Refer 200 Subscribers: 35% off my Analytics for SEO Course 🎁 Refer 301 Subscribers: 50% off my Analytics for SEO Course active 🎁 Refer 404 Subscribers: 75% off my Analytics for SEO Course 🎁 Refer 500 Subscribers: Free Analytics for SEO Course [RH_REFLINK GOES HERE] Twitter Whatsapp Telegram Linkedin Email PS: You have referred [RH_TOTREF GOES HERE] people so far See how many referrals you have

👥 Join Our Community

Our Discord community offers a small place where we can talk business and SEO.

If you hate all the noise of social media, then this place is for you.

🔎 Analytics For SEO Ebook (v8) - 50% Off!

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.

📚 Recommended Reads - Peak Content 🗻

Some good content you can use to upskill yourself now:

• ​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​
• ​Fundamentals of Analytics Engineering (the extra mile)
• ​How to Decide: Simple Tools for Making Better Choices​

LinkedIn Content:

• ​Domain Knowledge is key​
• ​Making order in Web Analytics​
• ​Content Clusters over time​
• ​Optimizing BQ costs​
• ​10 SQL concepts to learn​
• ​How long to get value out of web data​
• ​GSC VS BQ​
• ​Content Updates Over Time​

❗️ 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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