3. Machine Learning/ Deep Learning (especially #NLP): since Semantic SEO is a thing, some people can focus their attention on how certain algorithms work...
...Be careful, ML and DL are different from Data Science, although if you focus on one you should at least have some minimum degree of comfort with the others.
4. UX/UI Design: knowing how to structure and present information is a big plus for site structure and for creating effective pages.
5. Business/Management: understanding business is crucial for every #SEO.
Having a solid grasp of management principles however is something else...
...If you work as in-house SEO you are probably going to need some management knowledge.
Improving your communication with stakeholders or external parties is a big plus.
6. Content marketing: this is the most natural and obvious for many. Writing good content and being able to recognize it is quite challenging, so don't take it for granted.
Content is referred to all of its forms...
...not only text. Infographics and videos can be key points of a content marketing campaign.
This section includes effective communication as well!
7. Computer Science: Having knowledge of web servers and the Internet is the bare minimum.
Nonetheless, some people may find invaluable to study a variety of CMSs or more technical topics.
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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.