Keywords are language-dependent and are susceptible to language nuances, whereas entities are language-agnostic, a cat is still a cat, no matter the language.
Given the fact that a page can cover multiple queries, instead of optimising for a single keyword you should adopt the topical maps approach.
It won't be strange at all once we cover it.
A topical map is your action plan containing a collection of different entities and relationships among them (ontology) as well as their hierarchy (taxonomy).
If you are talking about games you'll put PlayStation 2 below consoles but on the same level as Xbox and GameCube.
This "modern" approach gives you the freedom to reason like your end user would and to organize a proper site structure that helps crawlers.
Of course, keywords play a huge role in SEO, topical maps and entities do not replace anything, think of them as helpful allies to create websites that can have their own Knowledge Graph.
To sum up, you can create maps where you connect different entities with relationships.
For instance, the entity Obama can be connected to Michelle Obama via a reciprocal relationship like "married to".
Continuing in the wake of Semantic #SEO, today we talk about Knowledge Graphs, a very interesting topic that represents the intersection between graphs and SEO.
A compilation of cool and useful ideas to leverage #Python for #SEO purposes. These are just some ideas on how to improve your workflow (automation) or to gather new insights in a smarter way
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1. Sitemap analysis: check content velocity and how much content your competitors have per section. You can also look for most common words in their URLs to have a high-level overview of what they post about
2. Broken link checker: pretty basic. Highly suggested when you need a lightweight function and don't want to launch Screaming Frog or other tools.