Use Data Or Be Used By Data!

The October 21 issue of Seotistics is here for you!

Social media are landmines of information.

You can find pretty much everything and most takes aren't even correct.

Today I will show you some concepts to get started with web data in any company.

This won't be a tutorial, this is about processes, mindsets and thinking correctly.

I'll go over most of them in detail in the next issues!

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Hey folks, thanks to all of those who purchased my products recently (and to all of my lovely readers).

I am going to publish new articles on the Seotistics blog soon.

Let me know if you have any recommendations or feedback!

P.S. I had the pleasure to discuss with Gus and Paulo about BigQuery, go check the video out (and see me getting the 1st question wrong 💀).

Stages Of Analytics

You can't skip the foundations, it's nonsense.

This is a rookie mistake I often see.

Companies rush to use cool methods but don't ask the basic questions, like:

how do we make money
how can this solution help us
what does the data mean
how was the data collected

People overcomplicate it, you need to use common sense and ask the "stupid" questions right away.

In most cases, you can simply stop at the beginner stage.

If a business isn't mature enough, you can start by reporting and monitoring what's going on.

Based on that, you can think about plans, corrective actions and stuff.

Yes, that's it! This is already valuable.

Leading VS Lagging (Misconceptions)

If you approach Analytics or every marketing channel just by measuring the outcome, you are missing out.

The outcome should always be to make money, though.

Paying for ads or content is not for awareness (doesn't mean anything) but for making money.

That's why we distinguish between leading indicators and lagging indicators.

All the traffic metrics are leading indicators, they inform you that you are on the right way.

The lagging metric is what happened or the outcome. For example, getting money.

It's easy to say we only care about money but that is wrong!

Monitoring leading indicators prevents catastrophes in your outcomes.

Ranking for fewer keywords may (or may not) lead to less money.

Less engagement on social media may translate to monetary losses.

The Case For Web Analytics

The focus is often on vanity metrics or too much on money.

Having balance is what is needed, both extremes are subpar.

Impressions and Unique Query Count are the rawest types of leading metrics.

They tell you that you may eventually get traffic.

Users, Clicks, Sessions, etc. are also leading metrics but they occur after people see you.

I stick to one traffic metric in my reporting because no one really cares about having multiple.

Too much information means no information.

What you should usually be more interested in is:

Revenue
Conversions
Leads

As said before, these outcomes (lagging) are affected by other drivers (leading).

Depending on your perspective, conversions and leads can also be lagging/outcomes!

Data-driven VS Data-informed

Data-driven is the worst buzzword to be ever created.

A lot of non-technical people use it to mean absolutely nothing.

I can tell if someone is not experienced (in Analytics) if they use this word.

Are many companies actually using data to make decisions?

Not really, they cherry-pick what makes sense for them (the big shots).

I prefer the word data-informed because the focus is on the human side again.

The difference can be summarized like this:

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The issue with all the information online is that it's too techie...

but this isn't where companies struggle.

Let's be real, anyone has data and they have no clue how to use it.

What's the point of building tools that people won't use?

And this is why the next section exists...

Product VS Research

As said in my previous issue, a product mindset can benefit you but it's not the only thing to look out for.

Once you have defined the issues and you are past the research phase, that's it.

If you are exploring a website for the first time, you can't adopt the product mindset.

Take your time with research and don't overload yourself with pointless tasks.

The requirements will change anyway!

Just to be clear, Analytics doesn't really get along with Scrum and Product Management.

I've attached a great article in the resources... and I think the same!

(My old readers will know that I even mentioned Lean and Six Sigma).

If we have to summarize what worked for me:

ask users what they need. If they don't know, you either know it yourself or don't do anything
documenting what matters to avoid inconsistencies and definition problems
know your industry dude!

You can use Scrum for specific parts though and that's OK.

But if you are coming from that background... data is just built different!

The level of complexity and exploration required is much higher... leading to severe unpredictability.

Data Dictionaries & Governance

If there is one thing no one talks about is data governance.

Have you ever heard someone talking about governance in web analytics? Not sure!

A data dictionary is a necessary piece of governance and helps you univocally define the meaning of your data.

Literally a dictionary where you define your metrics/dimensions and list down everything.

As an example:

GA4 data is a hot mess, so you need one or even more if you are using BigQuery data.

Some metrics have no official calculation and there needs to be clarity.

I love investigating and asking users what they need or how they define things.

It's a great business exercise since not many would actually start from the basic definitions.

The Boring Work No One Does

Most of the Analytics work is boring, pretty much like anything effective.

Boring is a good indicator that something works.

Too much variation is a bad thing, especially if you are trying to streamline processes.

For this reason, spend time on documentation and processes because this is where you can add the most value.

I've spent countless hours fixing mistakes made by other people or simply understanding GA4 events.

In my experience, a lot of companies need this kind of service in addition to what we already offer!

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