Machine learning is a type of artificial intelligence. Artificial intelligence is intelligence demonstrated by machines and is the ability of a computer to do tasks usually done by humans. Alternatively, it consists of a machine that seems like a human and can imitate human behaviors, including problem solving, learning, and planning. These behaviors are achieved by analyzing data and identifying patterns.Machine learning is defined as “the use and development of computer systems that are able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyze and draw inferences from patterns in data.” In other words, machines take in data and learn about the world, drawing conclusions that go beyond human intelligence. By being able to surpass humans in processing information, machine learning can spot patterns and identify anomalies, which helps point out potential issues that humans can now identify and handle.
Search engine optimization is “the process of maximizing the number of visitors to a particular website by ensuring that the site appears high on the list of results returned by a search engine” or “the process of making your site better for search engines.” In short, SEO is a “set of practices designed to improve the appearance and positioning of web pages in organic search results.”SEO is important because organic search is the best way for people to discover and access online content and to improve the quality and quantity of traffic to your site, which will help your business. Organic search results are “unpaid listings on a search engine results page that the search engine has determined are most relevant to the user’s query,” based on organic ranking algorithms rather than paid placements. With improved quality of traffic, a higher number of conversions is possible because the products, information, and other resources are more relevant to the site visitors. Additionally, the closer a site is ranked on search engines to page 1 of results, the more likely people are to see it and click on it, improving traffic quantity, which is another reason why SEO is so important.
Today more than ever, people are looking for instant insights and results, which is why machine learning is even more important in SEO. Machine learning technology learns over time to better answer search queries through adapting and responding to data. This allows accuracy of search results to happen at a speed that far surpasses the capabilities of humans.There are several ways that search engines use machine learning. Machine learning detects patterns that indicate spam or duplicate content. Another way search engines use machine learning is through RankBrain, that helps identify new ranking signals. More on this later. Machine learning allows for a search engine to create personalized search based on a user’s past behavior. Additionally, machines can better predict the meaning behind words we say and provide better information through things like BERT, bidirectional encoder representations transformers. BERT is a “natural learning processing framework that Google uses to better understand the context of a user’s search query.” Machine learning also analyzes and catalogs images as they are uploaded to the internet, identifying what images are and allowing search results for images to be more accurate. These are just some of the many ways that machine learning is used in search engine optimization.
Google RankBrain is an essential part of Google’s algorithm. RankBrain “is the first attempt at machine learning and will be paving the path for the future of search.” It is defined as “a machine learning algorithm developed by Google that helps identify patterns in queries and helps the search engine identify possible new ranking signals” or “a component of Google’s core algorithm which uses machine learning to determine the most relevant search results to search engine queries.” Through RankBrain, Google can discern a searcher’s true intent and deliver more relevant search results. RankBrain allows Google to speed up the algorithmic testing for various keyword categories to choose the best content for any particular keyword search. There are over 200 different ranking factors that make up the ranking algorithm.Machine learning comes into play when Google “feeds [RankBrain] data from a variety of sources. The algorithm then takes it from there calculating and teaching itself over time to match a variety of signals to a variety of results and to order search engine rankings based on these calculations.” In 2022, this google AI algorithm is likely to become one of the most important ranking factors for Google’s search engine results page. Now, rather than just using diversity, content depth, and keyword matching, SEO should determine the content that best serves a user’s needs. Google RankBrain can also solve problems that Google used to face, such as how to handle search terms that have never been entered into Google.
There are many benefits to search engine optimization and machine learning. Machine learning ensures that users are getting the most relevant search results to their search queries. As a result, site owners get higher quality traffic when machine learning provides the best possible matches of search to result. Developing content around intent becomes increasingly important with the greater role of machine learning in SEO.Machine learning can also help you with content development and determining what content to write about, what types of topics are trending, and what resources to utilize to develop content. Machine learning helps with understanding queries, personalization, and voice search. These allow businesses to “focus more on content experience and providing high-quality content experiences for clients” which is vital to getting quality leads and more conversions for your site.As SEO rapidly changes with machine learning advances, we must provide content that is high quality, meets end-user intent, gives users a positive content experience, and is useful. This will help deliver the desired results when it comes to site traffic and successful conversions.
Machine learning is also utilized through Google Ads. Google Ads uses machine learning through responsive search ads and smart bidding. Responsive search ads “will automatically allow you to test different combinations of headlines and descriptions to determine which combinations work the best.” Google’s smart bidding includes a “set of automated bid strategies that help you achieve specific goals for your business.” These strategies adjust bids in real time with the help of machine learning. The parameters that are used to determine bidding amount are wider with the algorithms used in machine learning. They far surpass what would be possible for a human to compute.During auction time bidding, a wide range of signals are factored in to bid optimizations, including device, physical location, location intent, weekday & time of day, remarketing list, ad characteristics, interface language, browser, operating system, demographics, search query, search network partner, web placement, site behavior, product attributes, mobile app rating, price competitiveness, and seasonality. These signals are “identifiable attributes about a person or their context at the time of a particular auction” and help determine bid adjustments.Overall, when it comes to search engine optimization, machine learning has become a vital part of how SEO works and the future of SEO. It’s important to keep in mind how machine learning functions, especially with Google RankBrain, and to form SEO strategies around that to keep ahead of the curve. This will lead to greater success for your site, higher traffic, and more conversions.