SEO

What Is Machine Learning as It Relates to SEO?

Machine Learning is a known concept now in the IT industry. There are many fields in which Machine Learning is currently used but how it will impact the way SEO is done at present? That’s the question we need answer to.

Before we go into what will change in future of SEO with the implications of machine learning, let’s just start with what exactly machine learning is.

What Is Machine Learning

Machine learning is often considered as one and the same with Artificial Intelligence, but it is not. Though they both are related and interlinked, there is a thin blurred line between the applications of both the technologies.

Machine learning is basically a subfield of Artificial Intelligence (AI) that uses algorithms instead of explicit programming to make computers learn on their own.

Whereas, artificial intelligence is the science of making computers do the tasks that usually involves human intelligence.

In the last few years, many search engines including Google started to use machine learning to have in-depth understanding about the quality of the web pages and search queries in order to provide the best and satisfactory results to the end users.

How Search Engines are using Machine Learning

  1. Pattern Detection

Machine learning is used by search engines for pattern detections to identify and eliminate spam or duplicate content.

Earlier this used to take a lot of time as actually manpower was reviewing everything. Machine learning let search engines to go through low-quality pages without any actual human to review it first.

Machine learning performs pattern detection in relatively less time and with more accuracy.

  1. Identify new signals

Google’s ranking algorithm RankBrain is the first ever machine learning based algorithm which not only identify patterns in search queries but also run predictions and data on its own.

This takes away the task from the human force, so that they can focus more on field like innovation and creative projects that machines can’t do.

  1. It’s weighted as a Small Portion

Machine learning is gradually transforming the way search engines fine and rank websites, but it’s still a long way to take over the entire search ranking.

Machine learning at present is a small portion of the complete algorithm which Google uses to provide the best experience to the searchers.

  1. Custom Signals Based on Specific Query

Machine learning has the capability to personalize searches by learning the user’s preferences from the past queries.

This also meant the search results depend largely on the query category or phrasing. Suppose you search for “New York football stadium” in an incognito browser, you will get the top results as “MetLife Stadium”.

Now if in the same browser you just search for “New York stadium”, Google assumes that since your last query was about a football stadium, this query is also about football and it will display the result as New York Stadium, a football stadium in South Yorkshire, England.

Now if you shift the search to “zoo”, it will automatically suggest you “zoo new England” and “zoo in new York” because your past searches and result include New York and England somehow.

This is how machine learning is personalizing the searches to provide better results.

  1. Image Search to Understand Photos

All over the world, tons of millions of images are being uploaded daily on different platforms. This speaks the volume of photos that need to be cataloged and analyzed on the web daily.

Machine learning help the search engine understand what an image actually is by analyzing color and shape patterns and comparing that with any existing data about the photograph.

This is how Google’s reverse Image search allows users to search by an image instead of any text query. Searchers will get the other instances of the photo like in different resolutions, along with some similar images that contain same objects or color pattern or information about the subjects in the photo.

  1. Identifying Similarities between Words in a Search Query

Machine learning doesn’t just personalize a user’s later queries but it also shape the search results for other users.

Suppose a user search for something like a slang term or phrase, Google may provide some nonsensical results for the same.

Over the time if the search for that term or phrase increases than machine learning will be able to display more accurate and relatable results for the same.

With the continuous development in machine learning, machines are able to get the meaning of our words in a better way and based on that they provide us with better information.

  1. Identification of Synonyms

Sometimes it happens that the result we get doesn’t contain the exact search term, that’s because the search engine is using machine learning to identify synonyms.

Search for “PhD degree” on Google and you will see many results with words like “Doctor”, “Doctorate” and “PhD programs” as these terms can be used interchangeably.

In some results, you will also notice these synonyms highlighted that means the Google is recognizing the synonyms through its machine learning algorithm RankBrain.

The Future of SEO with Machine Learning

While machine learning will never be able to replace the human interaction, it continues to be more accurate and smarter as the time passes by.

With machine learning, search engines are checking the quality and relevance of the content on the website. If any user finds your content irrelevant and unhelpful, your website might not rank on Google for related queries.

Google has a plenty of user data that help it to understand what users find helpful and relevant. This further helps the machine to determine users’ interests and preferences based on which it decide to sort and rank the search engine results.

SEOs must focus more on content that:

  • Is high quality
  • Meets users intentions
  • Provide a positive content experience to the user
  • Is useful
  • Is relevant
  • Is trending
  • Is easy shareable
  • Guides user to what they are actually aiming for
  • Generates good user experience

Conclusion

SEO is changing fast with the advancements in machine learning. User intent is an important factor to consider while generating relevant high quality content.

The SEOs must work in accordance with the Google’s algorithms so that they provide audience with the right content, at the right time, with the best user experience. This will help them reach to the ranks on Google.

As it is said that “time stops for no one”, SEO must keep themselves updated with the latest technologies and practices to give the best result to the clients.

SEOs must not limit themselves to their skills and strategies. They need to focus more on what is important for the client, what they expect from the SEO and how they can provide them by using the continuous development in technology.

 

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