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7 Ways Search Engines Are Leveraging Machine Learning that Impact SEO

7 Ways Search Engines Are Leveraging Machine Learning that Impact SEO

Machine learning is the subdivision of the artificial intelligence (AI) field, which plays a vital role in algorithms that allow computers to learn. It is a no-brainer that machine learning is being utilized by search engines to comprehend the nature of a website’s SEO that helps them to rank the results in an orderly manner. If you own a website and still have no clue about what machine learning is and how it can define your search rankings, it is time to pay attention and customize your SEO accordingly.

According to experts, every SEO professional must master the new skills and be flexible to the recent technological changes that are taking place due to machine learning. Search engines always like to practice new things and the case is same with machine learning where search engines are trying to use the technology for redefining SEO and search results. As an SEO professional, you must know the following ways where search engines are presently putting machine learning into use and how it influences your online marketing campaign:

Pattern Detection

Search engines are bringing machine learning into the light for pattern detection that allows them to discover duplicate or spammy content. They look out for the availability of SEO malpractice variables such as plenty of synonyms and many outbound links to discrete pages. With machine learning put into application, search engines can easily detect such patterns that are highly time-consuming when done manually. Even though all these endeavors are still carried out by humans, Google prefers using machine learning increasingly for detecting low-quality web pages without taking the assistance of a person to analyze the page first. Being an ever-evolving technology, machine learning analyzes many pages and provides accurate detection results.

Finding Out New Signals

Apart from identifying patterns in search engine results, machine learning also assists search engines in detecting the likeliness of new ranking signals. Owing to the high demand for these signals, Google can resume its efforts to enhance the quality of the results for search queries. In order to achieve this feat, the signals of Google is becoming more and more machine learning-based. Since machine learning has allowed search engines to run predictions and analyze data without using manpower, humans can dedicate their efforts to projects that cannot be handled by machines.

It Has No Significant Influence on SERPs

Although search engines have put machine learning into use, this has nothing to do with the current performance of SERPs. Machine learning is simply a facet of their overall ranking signal platform that is apparently availed by Google to improve the experience of users while making queries on the search engine. In simpler terms, machine learning can be defined as a minute portion of Google’s overall search algorithm. Hence, do not possess the misconception that machine learning will manipulate the search engine result pages.

It Focuses More on Certain Query-based Custom Signals

According to a study conducted on machine learning and its impact on search engines, it has been found that this form of automated learning in search engines might focus more on variables or place less weight on certain queries. Further research has revealed that this nature of machine learning completely depends on the phrasing of the search or query category. On the whole, SEO professionals discovered that personalized queries that were customized by machine learning helped in bolstering the CTR or click-through rate of results by ten percent. In general, machine learning helps search engines to decipher the needs and preferences of specific users. This allows the search engine to formulate results based on the information of past search queries.

Image Search to Analyze Photos

Thanks to the influence of social media, users nowadays upload and share millions of images on visual-sharing platforms like Instagram, Flickr and social networking sites like Twitter and Facebook. As brands avail these platforms for promoting their business and rank well on search engines, there is a huge volume of photos on the web that require being examined and cataloged daily. This task is where machine learning comes into play, owing to their ability to understand color and shape patterns. Also, they can pair the photos with any existing schema information related to the image that can be of great help for the search engines to acknowledge all the details about the photograph. This helps Google to not only catalog photos for Google Image search results, but it also eliminates the need for text query and instead offers the user with a photo file to access the images.

Acknowledges Patterns in Search Queries

Not only the existing query information is leveraged by machine learning to discover and customize a user’s further search queries, but it also allows the search engines to create patterns in data that formulates the search results, which helps other users later on with the same query. Nevertheless, the same phrasing and related user searches will be used with the passage of time; machine learning will become more capable to offer accurate data for those search queries.  With the development and transformation in language, machine learning excels in its ability to predict the meaning behind the phrases that users want to put in the search box, something that you can identify in the recent times while using Google.

Understanding the Intent of the Query

Users might input a search query to buy something or to do in-depth research or maybe just for finding resources. Moreover, a keyword can be used for any one or all of these search intents. Search engines utilize machine learning for identifying the intent behind every particular query by evaluating the type of content and click patterns of the users.


Machine learning is leveraged by search engines like Google to improve the user experience, which also determines the success of SEO. It helps in detecting the user intent and offers them with the best results that make high-quality content more important than ever. All you can do is optimize your site and its content relevant to search engine queries that can be easily favored by machine learning.

Author Bio

Vinod Jethwani is the CEO and Founder of Walnut Solutions and he helps web based companies with his SEO strategies to grown their revenue. He started his career in 2007 as a software developer with an Indian based MNC and later in 2011 became an entrepreneur. Follow him on Twitter @VinodJethwani or through his blog.

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