One of the most underrated topics in SEO and Marketing is decision-making.
How can I make better decisions with data?
You may think that knowing some coding is enough... wrong!
I teach you how to make better decisions in 5 minutes!
P.S. My Analytics for SEO course will be announced next week!
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Throwing Darts
In SEO you often hear that testing is crucial and there is no alternative.
I 90% agree with this take because you should always test what Google claims.
I 10% disagree because you shouldn't test what doesn't add value (or it's known).
Reading the nth case study on meta descriptions and CTR won't make you rich.
Testing if AI content works... same story. We know it can rank, but it doesn't mean it's sustainable.
The key point here is that testing is better than random guessing.
Question: is it better to use Copy A or Copy B?
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If you randomly guess, you can be 50% correct.
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If you run tests, your % should be higher than 50 to make sense.
We test to make better decisions and avoid relying on luck.
How Much Data Is Enough Data?
This is one of the most pressing questions in the world of Marketing.
We live in a swamp of data and have too many tools that can generate marketing data.
Google Analytics 4 and Tag Manager can track almost ANYTHING.
SEO tools like Screaming Frog or Sitebulb can add a lot more to your datasets.
And yet, what if I told you there is no need to work with larger datasets?
Small Data 4 The Win
Despite popular beliefs, small data is more interesting than big data.
You may have heard everywhere that the more the better...
but it's not true with data because:
- more data costs
- the value of more data is questionable
- you need someone to handle it
Thanks to inference, it's possible to draw conclusions from samples.
You don't need to measure every page on your website to come to a conclusion.
You need a representative enough sample!
For example, if you have a website with 100K pages and want to know if you have to change their format...
you don't have to analyze all of them, you'd take some and perform A/B tests.
The same goes if you want to prove that a certain element is performing well in one cluster compared to another.
Usually 10/15% of your website is a good sample but it's not so simple so we'll talk about this in the future.
Doing The Right Thing
I love this picture because it summarizes one of my favorite books:
Many entrepreneurs make bold decisions thanks to their experience...
but how many do they get wrong?
You shouldn't rush into a decision just because you have no data, in most cases, you actually have.
I like preparing a decision tree to evaluate different outcomes:
Reducing Risk
This is where I see many fall short.
The best SEO strategy is pointless if it doesn't take risk into account.
Is this competitive advantage sustainable in 5 years?
What you recommend or do should weigh the risk and avoid focusing on short-term gains alone.
It's also true that you need buy-in and quick wins... but not every company should do SEO.
A big SEO risk isn't worth the hassle.
The general advice is always the same:
If you recall my past Seotistics issue, I mentioned the importance of monitoring systems.
Data Accuracy & Quality
Let's face it, the data we work with isn't 100% accurate... and we can't do anything about it.
Google doesn't help either because their data is subject to heavy sampling and anonymization.
This problem is not only in Marketing... because it's everywhere!
Be it business or healthcare, construction or engineering, 100% accurate data is a theoretical construct.
That's because data is not objective, it's warped by our assumptions:
βThis means that asking for 100% accuracy is madness.
The good news is that you don't need that much to make informed decisions.
The goal is altering your course of action or beliefs.
How does this new info change what I knew before?
If you still do the same things after analyzing the data... you solve nothing.
Research > Staleness
It's necessary to invest in R&D, test new processes and experiment with what you have.
You have seen many content agencies close last year because they never worked on future-proofing.
AI isn't remotely close to actual quality content but...
if you have been offering low quality all along, AI is definitely better!
I've seen many quality agencies innovate and some in-house teams push their boundaries with:
- Automation of any sort
- Creative uses of AI
The results may not be immediate but those who tested always come out on top.
Our friend DDM, a goliath of digital publishing, has been quite innovative:
If you don't test and rely on whatever the SEO tool industry sells you, you're being left behind.
Inefficiencies stack up easily if you work with big websites and don't have solid systems in place...
2024 (and beyond) will be rough.
2024 & Beyond
There is no denying that 2024 is one of the strangest years to be in SEO:
- violent updates
- inconsistent SEO advice
- impossibility of predicting trends
- Google taking Ls
Stay sure that AI will stay and we will have to find ways to deal with it, as we already do today.
Despite what some think, coding will be even more important.
Code is an accurate way to communicate with machines, unlike English.
I am not very positive about the future of Google as I think many alternative ways of doing search can pop up.
The only certainty is that studying software and code never fails you.
My personal takes:
- Forget niche sites
- Invest in multiple channels
- Tech is the quickest way to future-proof yourself
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It will teach you or your employees to:
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π Recommended Reads - Peak Content π»
Some cool resources you should read to drive better decisions:
Remember, making decisions is the key to progress!
Some useful content for BigQuery:
Yes, optimization heavily matters!
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βοΈ Feedback and Recommendations
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Marco Giordano
βSEO Specialist & Data Analyst
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