Use Data Or Be Used By Data!

The April 15 issue of Seotistics is here for you!

Last time we discussed Google Analytics 4 and what you should learn.

Today we examine some tricks and tips for our beloved Web Analytics tools, Google Analytics 4 and Search Console.

Many use these tools incorrectly, I show you how to avoid it!

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Understanding Metrics

Google documentation is quite good and yet, many barely read it.

The most important takeaways for GA4:

Bounce Rate is crap (even in GA4)
Pageviews > Sessions > Users (where ">" means bigger than)
Engagement is tough to measure with GA4 alone
Reports and explorations have different sampling/thresholds
Traffic scopes matter (user > session > event)

For GSC:

the average position is pesky
an increase in impressions isn't always good
filter by search_type
filter by country and device too

This is extremely important because international websites have "skewed" positions by default in Search Console.

I see many people claiming that Semrush/Ahrefs have more accurate positions...

but it's because many don't know that GSC should be filtered!

This is even more visible for low-traffic pages, where sometimes you have days without a position (normal).

Google Analytics 4 Shenanigans

Google Analytics 4 is dispersive and rich in details but you only need a small percentage of metrics.

Bounce Rate is often fluff because some pages don't need to be "engaged".

It's fine for publishers or content websites to have high values and this is NOT a problem.

Source: https://support.google.com/analytics/answer/11986666?hl=en#zippy=%2Cin-this-article

As you can see from the picture above, Google actually made it more useful in GA4.

Still, it's not my first choice.

If you want useful advice to improve your UX, use Microsoft Clarity.

Or create a new engagement metric based on Engagement Rate and others.

Pageviews are not my favorite metric to track, I usually focus on users and filter by First user source / medium, if needed.

Mind you, this value will include any search engine, including Bing and Yahoo, as you can see above.

Google Search Console Shenanigans

Search Console is much smaller but tricky nonetheless.

The most common mistake with GSC data is when aggregating data or doing reports.

Especially with the BigQuery export, you get a raw position metric named sum_position.

As shown in my BigQuery handbook, dealing with it requires you to calculate it whenever you aggregate data.

So I recommend you calculate the avg. position when running queries and NOT before, depending on the aggregation you want.

The other important detail is understanding what position means.

It's calculated from the left of SERPs, so a Knowledge Panel will have a lower number (position 6 below).

Position counting order on a 2-column result set. — Source: https://support.google.com/webmasters/answer/7042828?hl=en

The position metric is an average because there is NO absolute position.

It changes depending on the other dimensions, such as country, device, etc.

If many pages rank for the same query, Google will take the best position.

This is understandable, a common example is:

Page A (relevant) ranks 10 for query a
Page B (non-relevant) ranks 42 for query a
Page C (non-relevant) ranks 83 for query a

A's position is taken into account.

Google documentation is once again spot on and makes more examples.

Last Warnings

For this reason, I avoid relying on this metric because it doesn't make much sense for serious analysis.

It's also unreliable because it's affected by how much you publish.

I do one exception and that is when tracking query count changes across position bands and time:

Never ever use the GSC UI for audits, you should use its API or what's in BigQuery for advanced use cases.

The UI is completely unreliable and well, you will make terrible decisions.

Sampling

Google will never give you ALL the data.

Once in a while, I defend them and say that it's a good idea given that many companies won't use it.

In GA4, standard reports aren't sampled but Explorations may be.

The latter gets you much more data and are the best option between the two.

But they can be subject to sampling and threshold limits... so you get less data.

In GSC, data is always sampled and if you filter by query/page it may be more because anonymous queries get excluded.

My personal experience has seen cases where 60-80% of the data is lost!

I recommend reading Google's documentation because it's boring text you need to know.

As already discussed in my past Seotistics issue, sampling per se is not a tragedy:

It's not like we can't make good decisions because of this.

If you feel like you need more data... I have bad news for you.

It's often about HOW you use it rather than simply having anonymized queries available.

The Light At The End Of The Tunnel

The solution in both cases is to use BigQuery exports to get the most out of both sources.

Even so, GSC won't give you anonymized queries but at least you see their metrics!

So yes, you can know how many anonymized queries you have and what's their contribution.

Sampling is quite annoying when doing comparisons for your reports... as you can be easily thrown off guard.

The best solution is to compare data from the same source and document how you get data.

Were users filtered by source or country?

All of this can be avoided if you just use BigQuery.

The GSC API gives you a maximum of 50K rows per day which is not a lot for bigger websites.

All of these limits may seem useless for small websites but they do make the difference for bigger websites.

My new article explains to you how to combine GSC and GA4 data in BigQuery + all the details you need to know.

The Misinformation In The SEO Industry

We are surrounded by misinformation and low-level advice given by marketing people.

You can hear all types of buzz:

Use this simple trick to find good keywords
Cool Looker Studio dashboard to see your best pages (c'mon it's 2024)

There are even plugins to use GSC data... but if you are an SEO, you should know your data and save your earned money.

You can use Search Analytics for Sheets/a Google Analytics plugin or a Python/R API to get your data without relying on stuff built by other people.

What Can You Do Today?

The answer is always the same: inform yourself!

Studying and upskilling are what make you immune from misinformation.

The "I don't need that" narrative is short-lived and proved to be completely ineffective in the last few years.

Gone are the times when you just needed to be decent at SEO alone.

My current advice is to:

Create your custom metrics and play with them (check this past issue)
Think twice before using GA4 metrics without context
Details are optional, focus on the actions

After all, it's all about decisions and actions. Otherwise, you are building cool stuff that has no impact.

Speaking of custom metrics, I love to:

Classify pages by performance
Score Content Decay
Spot Evergreen Content
Create a new engagement metric
Count queries (unique)

Most of this is covered in my BigQuery handbook and the rest in my ebook...

If you want a more structured alternative, check out my course with a 30% off limited offer:

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Even if you leave SEO, the foundations are the same for other jobs!

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📚 Recommended Reads

These Analytics books are among the best out there. If you want to think like a true Analyst, look no further.

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❗️ Feedback and Recommendations

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Marco Giordano
SEO Specialist & Data Analyst

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GA4 & GSC - Tips & Tricks To Excel