Some #SEO concepts that are not so common across mainstream resources. They will probably become more known with time (I hope).

This is a thread 🧵
1. Phrase-based indexing. The usual SEO guide suggests you to put keywords here and there.

You should try to understand common sentences across competitors, it works and it's better!
2. Entities. I post about them like everyday but there is often no mention of them in what can be considered "mainstream" beginner material.

Having a CSV with 100K keywords is certainly not going to change anything if you don't know Semantic SEO.
3. Knowledge Graph. Same as before, it's not a new concept, yet it's not considered mainstream.

It should be one of the key ideas of modern SEO.
4. Syntax. Words weight a lot, especially if you don't have a good syntax.

Everyone talks about the structure and that's great, but what about sentence structure?
5. Topical maps. Your action plan to start doing real Semantic SEO.

However, it's more common to hear Keyword Research and Content Plan than topical maps.
6. Understanding data. One of the most common mistakes that you will probably have seen is presenting GSC data without filtering out branded queries.

This is just one example to show you how not understanding data can be fatal.
7. Considering the big picture. Looking at clusters instead of keywords, looking at content and considering important technical fixes, etc.

Imho there is no absolute winner, one should focus on what makes sense, without dismissing the work of others
8. Don't follow a "simple" checklist. Fixing titles, alt texts and tags is not a strategy.

Sure, it can be helpful in some cases. The problem of checklists is that people often misuse them and stop thinking laterally.
9. SEO doesn't reduce to SEO alone. You can learn from other fields and apply what you understood to improve your SEO career.

Nonetheless, the best advices you usually read on mainstream resources are the same takes from 10 years ago (kinda)
10. Google Patents. A lot of useful stuff is buried within patents but it's not as attractive as recycling the same concepts.

Jokes aside, check this out: seobythesea.com

That's all you need, nothing else.
11. UX/UI. User Experience is essential if you want to create a good experience for your potential customers.

This is not a SEO concepts, it's a totally different subject.
12. Providing actual audits or reports. Let's be honest, a good share of audits/reports are just data dumps from 3-4 SEO tools.

They provide 0 value and make fixes even more complex. Don't be that guy that calls audits this type of work.
13. SEO means knowing "some" business. If you are optimizing a tech blog you should have some degree of confidence when creating a topical map.

How can you restructure an e-commerce if you don't have the idea of what they are selling?
14. Brains win over tools. A shiny new tool is not going to make you better.

Learn some strategy and create a methodology first and then find the most suitable tools.
15. Right is not always right. There are some SERPs which make no sense (e.g. bad machine-translated content dominating a SERP).

This can happen and it's part of the game, Google is not perfect.
I wish I had this resource when starting, it's the best you can get (and also free).

learningseo.io

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More from @GiordMarco96

Jan 27
A handful of lessons I learned (and I am still learning) while trying to apply #DataScience to #SEO. Some of them are not so obvious either.

This is a thread 🧵
1. Communication is hard and you will get mad a lot of times. Non-technical people have no clue what you are talking about and you have to educate them.

Easier said than done, but I think that you should stay strong and keep trying.
2. Data quality is all. In SEO it's way harder as you are working with estimates and you don't even know the original data distribution.

That is why I am very careful when using Machine Learning models for SEO.
Read 17 tweets
Jan 26
Today I tweet about something different. Some things I learned while studying and practicing #SEO that some people may find extremely valuable (or not).

This is a thread about my personal 15 lessons 🧵
1. Soft skills are extremely important. The first time you heard about them they seem fluff, it's actually the opposite.

Convincing stakeholders and negotiation are the most valuable skills for my own experience.
2. Variety is great. This doesn't just apply to your workplace but to skillset as well.

Exploring new things and going over prejudices involving other disciplines is a super valuable learning.
Read 17 tweets
Jan 25
Ok, why should I learn #NLP concepts if I am a #SEO Specialist? I give you some good reasons to get started in 2022.

This is a thread 🧵
Better understanding of everything regarding Semantic SEO.

Topical maps and entities will be a breeze for you.
You can apply NLP techniques to analyze content and organise your work based on some measurable concepts.

It's not an opinion if a sentence has a bad structure.
Read 9 tweets
Jan 23
The best resources to learn Semantic #SEO, think around topics and not just keywords.

This a thread 🧵
holisticseo.digital

The most useful and interesting case studies are here, a must have for all
rankranger.com/blog/what-is-s…

Very good resources to get started now, pretty simple to follow.
Read 7 tweets
Jan 22
Some quick tips based on Semantic #SEO and #NLP (but also good #copywriting) that can improve your writing skills.

🧵 This is a thread 🧵
Avoid weasel words and fluff. Go straight to the point and remove useless adverbs or prepositions.

You should just leave the essential stuff as long as it conveys what you are trying to communicate.
Put important entities at the beginning of your page (i.e. in the introduction).

Don't fool around and make it clear that you are talking about a given topic from a certain angle.

🔽🔽🔽
Read 14 tweets
Jan 20
Some other tools/ideas that can guide a #SEO Specialist in your journey towards being more data-driven.

There are a lot of loanwords from #datascience in here!

Another thread again 🧵🧵
SQL and DBMS (Database Management System): the former is a language to perform queries on a database, the latter is a system to manage a database.

If you're tired of ""storing"" your data in unreliable Excel sheets then you're in the right place...
...Google BigQuery is one top-tier tool that you can explore for storage and for queries/calculations.

SQL is the most important technical data skill you can wish for!
Read 10 tweets

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