The 10 most common errors you make when analyzing #SEO data.
These are quite dangerous for your websites.
BUT they can be easily fixed if you know them.
Let's see the full list 🧵
These are quite dangerous for your websites.
BUT they can be easily fixed if you know them.
Let's see the full list 🧵
1. Mixing branded with non-branded traffic.
This completely destroys your reporting efforts for big brands.
A big NO for Enterprise SEO but not a big deal for websites with weak brand recognition.
This gets the first spot because it's so wrong for big websites.
This completely destroys your reporting efforts for big brands.
A big NO for Enterprise SEO but not a big deal for websites with weak brand recognition.
This gets the first spot because it's so wrong for big websites.
2. Not cleaning data.
Analysts normally clean them and spend a lot of time to figure out if they make sense.
Non-technical people just go for the insights, that's super wrong.
This is the difference between making money and losing it.
Analysts normally clean them and spend a lot of time to figure out if they make sense.
Non-technical people just go for the insights, that's super wrong.
This is the difference between making money and losing it.
3. Wrong comparisons.
Comparing 3rd-party estimates to Google data or benchmarking different time periods.
It makes no sense, c'mon.
You can be lucky the first few times, but later you'll only do damage.
Don't compare data without a complete understanding.
Comparing 3rd-party estimates to Google data or benchmarking different time periods.
It makes no sense, c'mon.
You can be lucky the first few times, but later you'll only do damage.
Don't compare data without a complete understanding.
4. Understanding your metrics.
Every metric in GSC is sneaky, those details that can invalidate your insights.
Studying what those data mean can save you a lot of headaches.
Check Google documentation to see how they calculate them.
Every metric in GSC is sneaky, those details that can invalidate your insights.
Studying what those data mean can save you a lot of headaches.
Check Google documentation to see how they calculate them.
https://twitter.com/GiordMarco96/status/1595871340531023872
5. Thinking that a spreadsheet can replace a database.
No, it can't.
They serve completely different purposes, they are not alternatives.
This is a super common problem in enterprises.
No, it can't.
They serve completely different purposes, they are not alternatives.
This is a super common problem in enterprises.
6. Analyzing too much.
People want the short version unless your insights are gold.
Don't waste too much time on data, find what you need and then take action.
Don't spend money on tools or tech if you don't have a good staff first.
People want the short version unless your insights are gold.
Don't waste too much time on data, find what you need and then take action.
Don't spend money on tools or tech if you don't have a good staff first.
7. Thinking that code is the panacea.
An analyst is paid to interrogate data (and people) and to add value.
The code is only a means to achieve an end.
That's the difference with developers.
Analytics is not coding alone!
An analyst is paid to interrogate data (and people) and to add value.
The code is only a means to achieve an end.
That's the difference with developers.
Analytics is not coding alone!
https://twitter.com/GiordMarco96/status/1599372961353322496
8. Thinking that it's just hard skills.
Nah, analyzing data requires abstraction and hands-on experience too.
You can't rely on code or Math for every single task.
That's why you have to develop a critical spirit and practice.
Nah, analyzing data requires abstraction and hands-on experience too.
You can't rely on code or Math for every single task.
That's why you have to develop a critical spirit and practice.
9. ""SEO is different!""
It's just a domain like any other.
You may do it for Finance, Healthcare or SEO.
In our case, we only care about websites but the ideas are the same.
What you need is knowledge of actual SEO compared to people analyzing other types of data.
It's just a domain like any other.
You may do it for Finance, Healthcare or SEO.
In our case, we only care about websites but the ideas are the same.
What you need is knowledge of actual SEO compared to people analyzing other types of data.
10. Treating audits like a list of things to do.
It's not wrong BUT...
they're often a compilation of basic stuff.
Give actionable advice instead.
It's not wrong BUT...
they're often a compilation of basic stuff.
Give actionable advice instead.
https://twitter.com/GiordMarco96/status/1588620643737534464
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If you liked this thread, consider liking and retweeting it!🧵
If you liked this thread, consider liking and retweeting it!🧵
If you own a publisher or a content/niche website, I can help you.
I offer:
- Content audits to solve traffic and $$ loss
- Content Planning and Research
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bookk.me/marcogiordano
I offer:
- Content audits to solve traffic and $$ loss
- Content Planning and Research
- Training and mentorship for data skills
bookk.me/marcogiordano
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