Machine Learning & SEO: Where Are We Now?
Machine learning is having a substantial and growing impact on the traditional Google ranking algorithm. This has a large impact on the ways SEO professionals analyze keywords and ultimately build a strategy to improve rankings. Find out more here...
For many in the SEO world, the idea of machine learning influencing the industry is making substantial waves. The technology inevitably promises to alter the way in which business is done — and it may even change what successful SEO ultimately looks like.
In light of this information, many SEO professionals and marketing experts are frantically attempting to gain a greater understanding of how the system may be changing and how that is going to impact their processes. Advances in machine learning may negatively impact those that have long been worried about fluctuations in analytics; however, it may prove beneficial for those that have long been focused on working to improve the experience for end users.
The technology may actually help to expand the importance of quality SEO work, and it’s likely to significantly benefit all those searching the internet for information. Understanding the change and potential impacts is key to success. Let’s take a look at how machine learning is shaping the future of SEO.
The Machine Learning Buzz
Machine learning is the term given to a method of analyzing data automatically. It is a branch of artificial intelligence, where data is digested, patterns are identified, and decisions are made without direct human guidance. In recent years, the technology has rapidly developed, meaning computers are getting better at recognizing and responding to information that is fed to them.
Within the world of marketing, machine learning can be powerful for its ability to notice patterns that would otherwise go unrecognized. This is particularly pertinent when it comes to identifying behaviors of potential customers and capitalizing in company engagement. Because of this, businesses with machine learning and artificial intelligence specialists are rapidly diversifying the skills of their workforce, with many clamoring to attract young professionals to meet their needs.
Machine learning as it relates to anticipating customer desires is so impressive that it is beginning to be utilized by companies such as Google. In 2015, Google introduced machine learning into its search engine, called RankBrain, to help provide users with more relevant search results. As time goes on, RankBrain’s ability to associate words and phrases with similar meanings will only continue to grow.
SEO and Machine Learning
It may be obvious at this point, but Google’s developments have had huge implications for those working within the SEO industry. RankBrain ultimately collects data from similar search phrases, connects them, and delivers more relevant results to users. User interaction with SERP rankings is also factored into this as a learning data point. This process can substantially alter traditional notions of which companies and organizations are likely to be in the top search results for a given search.
This means a couple of really big changes took place for those in SEO: Keyword rankings are no longer affected by dramatic shifts, and different algorithms may be used for different searches. An additional change that continues to develop in 2019 is Google’s focus on migrating sites to mobile-first indexing, meaning that mobile-friendliness in terms of layout, orientation, and page loading speed is a big factor in rankings.
In order to adapt, many SEO professionals are looking toward add-ons that help to crunch new data using existing tools. A number of new SEO-focused tools are also beginning to emerge that can help to model shifts in algorithms and better enable professionals to anticipate the best ways to capitalize within certain niches. Many frequently used tools, such as Moz’s SEO Stack and Google Analytics, have been adapted for mobile analysis. However, for many SEO professionals, a renewed focus on the end user experience is in order.
Remember the User
Perhaps the best way for SEO professionals to adequately adapt to machine learning developments is to take a hard look at content and end-user satisfaction — essentially crowd sourcing and using crowd analytics. The phrase “produce good content and they will come” has never been more relevant. RankBrain links similar phrases to bring value to search results; therefore, filling these niches has an increased potential of rocketing your clients to the top.
SEO professionals that are creating content should focus on creating natural links by providing relevant and useful information to end users. Use natural language that reflects what a real user might actually be searching for. For instance, long-tail keyword strings rather than single words have been shown to offer larger payoffs to those attempting to build a client’s ranking in the SERPs.
Remembering the user also means making sure their online experience on a given client’s website is the best and as user-friendly as it can be. This means focusing on ease of access regardless of device by adapting to mobile and cleaning up any broken links or dead ends that could make using the website frustrating. It also means providing quality evergreen content that will continue to be useful information and will likely gain shares over time. Some aspects of quality SEO work never go out of style.
Machine learning is having a substantial and growing impact on the traditional Google ranking algorithm. This has a large impact on the ways SEO professionals analyze keywords and ultimately build a strategy to improve rankings. The advent of machine learning underscores the importance of the end-user experience and encourages many SEO professionals to take a hard look at improving this in their own work.