Use Data Or Be Used By Data!

The October 28 issue of Seotistics is here for you!

Google Analytics 4 is a hot topic and mostly because it's a bad product.

But do you actually need to learn it all?

No, and I am here to show you why!

P.S. More content to come on Seotistics, I was quite busy!

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Why So Hated?

GA4 has a terrible UX and it's hard to find what you need, there isn't much room for discussion.

Universal Analytics wasn't a technical tool and GA4 isn't either.

The average marketer doesn't have to go through heaps and leaps just to see who visited your pages.

Speaking of which, I show you 2 ways to tackle this problem...

Option 1: Learning GA4

If you want to stay in the non-technical limbo forever, GA4 is a great choice!

You can study all you want and memorize the most common processes.

There is nothing wrong with this opinion, although it's a bit subpar and cranky.

But still, I wouldn't say it's too hard.

Option 2: Use GA4 As A Data Source (Recommended)

GA4 and GSC aren't only tools but also data sources.

In most cases you need their data, not the interface they provide you.

When working on large projects, it's wrong to work with UIs.

Google Cloud Platform offers many well-documented tools for playing with web data.

GA4 even has a free connector to send data to BigQuery!!!

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This is huge if you consider how easy it can be to use such tools today.

If no one stored the data, you have to start linking GA4 to BigQuery and then wait.

My subscribers got my BigQuery handbook and are already trained with GSC data!

In the meantime, you can use the GA4 API to get the data you need (with some limitations).

Embracing The Dark Side

If you love being fast and doing proper work, you will always go with Option 2.

GA4 isn't supposed to be a tool for most of the use cases, you have to just get the data and DIY.

I know... this isn't the typical marketing advice.

It's the most correct though.

It's 2024 and the influence of IT is everywhere...

you can choose to be a player or be played by data and technology.

The only downside is that you need to understand the schema of GA4 data in BigQuery.

Learning this schema above will inevitably lead you to master GA4.

Once you figure out the inner workings of the tool, the rest will follow.

GA4 BigQuery is hard, don't let it fool you.

Is it harder than learning GA4? Absolutely not!

I'd do it over and over, learning how to play with data warehouses is key in Marketing Analytics.

GA4 Isn't Enough

Your first data source is GA4 unless you have to analyze a given channel first.

For SEO, GSC is the winner.

GSC contains the most valuable information for us but lacks details about user engagement (and all the other channels).

GA4 alone is too broad for SEO, so you need to combine the 2 datasets and take the best from both.

Check my dedicated article on combining GSC and GA4 in BigQuery.

This is also why BigQuery makes it so easy.

"You start adopting best practices and abandon the clumsy process of using spreadsheets and VLOOKUPs in 2024."

Unfortunately, not even GA4 and GSC can compensate for the extra power of Google Tag Manager.

Events like:

button clicks
form submissions
sign-ups

are all custom events you need to implement via GTM.

Which Metrics To Pick?

I could start a war on this topic because the majority of the content out there is basic.

Many dashboards often report on standard metrics, such as:

Users
Pageviews
Sessions
Bounce Rate
Engagement Rate

The outcome is that you get a dashboard conveying a lot of information but 0 action.

And make sure people actually use your stuff!

At a strategic level (i.e. you talk to the board), this is OK.

They just want information and you need to show off.

But if you have to create a dashboard to be useful, then you can't afford to show me Users and Sessions and call it a day.

There are other valuable options like:

Leads/Conversions
Custom events
Custom metrics
Custom dimensions

Every business is different so you'd better have custom criteria.

Avoid relying on the baseline metrics that don't make much sense for you.

(Still, there is a degree of standardization, we agree that revenue matters in Ecommerce, right?)

As shown below, you can rely on more advanced traffic metrics but those should NOT replace the financial ones!

What Everyone Gets Wrong About GA4 Metrics

After years in Marketing, it's normal to notice some recurring mistakes:

Taking Bounce Rate seriously
Using engagement metrics without a benchmark
Users/Sessions/Pageviews everywhere
Not cleaning/filtering data (again)
Comparing different scopes

Avoid these mistakes and you will be a "power user".

If you understand how the different scopes work and their attribution models, you are already good.

Bounce Rate and many other metrics don't make any sense in isolation.

Your page has a Bounce Rate of 90%, we have to improve SEO!

Average agency trying to upsell you

CRO is important but it's not limited to contextless metrics!

Google does track user engagement in its own way but not with the metrics we see in GA4.

Unless you can provide a baseline, those numbers have no meaning.

Is an average time on page of 2 minutes good or bad?

My answer: this alone is worth $0.

Using critical thinking is what differentiates quality from quantity.

In some cases, high bounce rates can be a very positive signal. People can convert in weeks or even months...

don't take every number at face value!

Beyond The Mainstream

Many current practices are suboptimal and we all know deep down.

Dashboards in most cases shouldn't even exist as no one is actually going to use them.

The only certainty is that you need to store and monitor your data.

GA4 isn't that hard to learn but it's not going to make a difference if you want to add value.

You must know SEO or any other channel to understand the data you play with.

My course is ideal if you want to learn all you need to analyze websites. Yes, it covers GA4, GSC and BigQuery in detail.

I am adding additional GA4 content soon!

[Analytics For SEO Course - v3]

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

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 👀

Learn Analytics for SEO Now!

The Struggle For Logic

One of the problems I always complain about is how Web Analytics is treated.

The majority of the industry is too focused on tools and not on the data itself.

Read it again.

On tools, not on the data.

This is problematic because many learn how to use Google tools but not how to interpret data or extract meaning from it.

That's why Seotistics exists.

GA4 happens to be the most striking example...

How many articles have you seen detailing data interpretation in depth?

Integrating More Data Sources

A good analysis doesn't require all the data but more is certainly better in some scenarios.

Spending time to practice with other data is important, for example:

Google Ads
Social media
YouTube
Crawl data
CMS
CRM
Log files

If you can play with SEO data, then you will have no problem catching up.

In most scenarios, GSC and GA4 will often do the trick along with some crawl data.

In SEO there is a weak focus on user behavior in terms of data and this can be a great starting point to do the opposite.

(No folks, checking heatmaps and saying write great content is not analyzing user behavior).

The ideal outcome is having a table with all the page information you need, for example:

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More information about a page allows for clearer classifications.

Financial metrics, engagement and traffic data give you the best overview of what to prune.

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