SEO, also known as Search Engine Optimization, includes all those techniques we use to make Google like our contents.
Google will put good SEO contents higher in SERP (Search Engine Results Page), making them visible to possible readers.
As you as marketer certainly know, SEO techniques changes according to Google algorithms updates.
However, it is much more than keywords, backlink and metadata optimization that are only the basics.
Now there is Artificial Intelligence.
Let’s see together how Artificial Intelligence affects SEO.
Google and AI, the mastermind behind our searches
Before AI, Google used to rank a website according to keywords fitting. Google algorithms crawled the site and found correspondences in navigators searches. The system was easy to cheat. There were thousands of sites filled with keywords, visible and invisible. Writers were used to stuff as many keywords as possible inside their articles. The result was a lack of readability and sometimes total missing of value inside the contents.
Nowadays, AI, in particular, Machine Learning and NLP (Natural Language Processing), make writing SEO content much more accessible, valuable and accurate.
NLP, because of its syntax analysis capabilities, understands sentences’ content and context.
Machine Learning makes it understand better and better what kind of content is more similar to the user’s intention recognized through the NLP. Then, it suggests the right type of content to read.
This makes almost impossible, or at least not recommended, try to fool the SEO to have a better position in SERP, or insert not valuable links. For example, it’s almost impossible to do keywords stuffing.
It was 2013 when the first AI-based update was born. It was called Hummingbird, and it aimed to start understanding human language. It’s a huge task, and we haven’t ultimately reached it yet, but progress is stunning.
Machine Learning and Natural Language Processing for SEO
Nowadays, AI has become a crucial component of how search engines rank pages.
Artificial Intelligence models analyze keyword concentration, while others check for the quality.
In 2016 Google presented RankBrain, “a machine-learning algorithm that identifies patterns and buckets data”. RankBrain is an example of a tool based on Artificial Narrow Intelligence, the only kind of AI we’re capable of creating right now.
15% of queries had never been seen before, and RankBrain processes each one of them to train itself to recognize them and, hopefully, answer them.
Google aims to know how people are searching – and adjust to it.
It wants to collect as many pieces of information as possible (learning how to improve with time) to mix as best as it can. In this way, it can mix the other algorithms in the search engine, so it can show the most useful results to the final user.
Machine Learning let computers learn more and more about a specific theme.
The more you feed (and train) them, the better they go.
In addition to that, NLP models can understand not only single words but whole sentences.
Thanks to these models, Google can suggest results that match consumer needs.
The merge between NLP and SEO came really handy also for voice search. We use it every single day, with Alexa, Siri or Google Voice.
Recently, the development of speech recognition technology has improved. We are now experiencing big important changes in voice search. This led us to VEO, the Voice Engine Optimization. When we tell Siri to find a falafel restaurant near Piccadilly Circus, we are using voice search. The device selects only the meaningful words we say and tries to catch the speaker’s intention. After that, it selects a relevant response, or more than one. The same happens when we ask Alexa to play, for example, our favourite Spotify playlist.
What comes later? RankBrain is, actually, competing with Google! How is it possible? It is because the tool collects and analyses a massive amount of data from websites it crawls (we’re actually talking about millions and millions of data).
This trend will evolve along with consumers’ needs and approach.
SEO includes everything: blogging, social media marketing, newsletter. If it’s written, it can be analyzed by SEO. Not only text but also pictures and images become searchable thanks to the alternative text that describes them with what you put in the “alt” tag.
If it’s not possible anymore to make keyword stuffing, the way to be on top of SERP will be to create high-quality contents. In this way, algorithms will be more likely to select our text and mark it as authoritative. This means that to make AI like our content, we have to build it in the most human-friendly way as we can.
Journalism and copywriting, for example, are two fields that are getting benefits from AI and SEO relationship.
Let’s have the example of some articles that need to be particularly SEO-friendly because they need to drive traffic to our website. For example, Associated Press uses since 2014 AI algorithms to write some financial and sports articles.
But for other kinds of writing, AI and SEO can combine to generate automated text that Google likes, allowing humans to dedicate themselves to more complex work.
Maybe AI will change the way we think about content, but something will never change: the target or, better, the person we create those content with. His (or her) engagement is the most powerful tool we can think of.
- SEO is useful to make Google like our contents and put them first in SERP.
- Machine Learning and NLP (Natural Language Processing) make SEO content much more accurate.
- We can already see SEO and AI applications in journalism and newsmaking.