Disclaimer: I work for WordLift.io, which focuses on Semantic SEO and on-page SEO automation. Thus my opinion might be biased.
The answer is SEO matters a lot.
Yet SEO today means something entirely different from what it meant a few years back.
Back in 2015 when I started my blog, I was writing what would be defined quality content. It was very in-depth, researched (at times it would take me weeks to write a piece of over three thousand words). However, when I hit the publish button I wasn't getting any traffic (at the time a few dozens visits per month!). True, quality content is the baseline, but if you don't have an idea of how search engines work, you might gain traction over a few years time, but the process is quite long and not guaranteed to succeed!
However, what SEO means today is different from what it meant a few years back. In the past keywords and backlinks were all that mattered. They still count. However, it will come a day when they will stop working. Why?
Since 2012, Google has been building a giant knowledge graph, which main aim is to gather information on the web, structure it in the form of nodes and edges to construct this massive graph. Thus, getting featured within Google's so-called knowledge vault becomes critical for an effective SEO strategy.
Thus, if in the past you might be targeting keywords to be positioned on the SERP. Today you might want to be more focused on long-tail keywords that can bring you in featured snippets or inside a knowledge panel. In fact, those are also the avenues to get into the Google assistant, thus voice search.
In short, while in the past it made sense to use backlinks and keywords because Google lacked the power to use more sophisticated methods to index and rank the web pages. Now you have to switch from a keyword centered content model. To an entity-based content model.
This kind of approach is more holistic and targets not only the SERP, but it allows you to get ready for voice search. What are some practical examples of having this approach?
- an internal glossary that targets specific questions your readers/potential customers might have
- structured data in the form of Schema injected as JSON-LD (in this way you're giving better data that does not affect the performance of the page)
- use a better internal linking strategy, that connects articles to topical pages (like the glossary pages) and back
There are more strategies to adopt, but those are the ones that come to mind right now.
The answer is SEO matters a lot. Yet SEO today means something entirely different from what it meant a few years back.
Back in 2015 when I started my blog, I was writing what would be defined quality content. It was very in-depth, researched (at times it would take me weeks to write a piece of over three thousand words). However, when I hit the publish button I wasn't getting any traffic (at the time a few dozens visits per month!). True, quality content is the baseline, but if you don't have an idea of how search engines work, you might gain traction over a few years time, but the process is quite long and not guaranteed to succeed!
However, what SEO means today is different from what it meant a few years back. In the past keywords and backlinks were all that mattered. They still count. However, it will come a day when they will stop working. Why?
Since 2012, Google has been building a giant knowledge graph, which main aim is to gather information on the web, structure it in the form of nodes and edges to construct this massive graph. Thus, getting featured within Google's so-called knowledge vault becomes critical for an effective SEO strategy.
Thus, if in the past you might be targeting keywords to be positioned on the SERP. Today you might want to be more focused on long-tail keywords that can bring you in featured snippets or inside a knowledge panel. In fact, those are also the avenues to get into the Google assistant, thus voice search.
In short, while in the past it made sense to use backlinks and keywords because Google lacked the power to use more sophisticated methods to index and rank the web pages. Now you have to switch from a keyword centered content model. To an entity-based content model.
This kind of approach is more holistic and targets not only the SERP, but it allows you to get ready for voice search. What are some practical examples of having this approach?
- an internal glossary that targets specific questions your readers/potential customers might have - structured data in the form of Schema injected as JSON-LD (in this way you're giving better data that does not affect the performance of the page) - use a better internal linking strategy, that connects articles to topical pages (like the glossary pages) and back
There are more strategies to adopt, but those are the ones that come to mind right now.