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AI & Machine Learning: Why Local SEO Experts Should Care

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The widespread use of artificial intelligence first gained the spotlight with Apple’s introduction of Siri on the iPhone. Since that time, other major companies like Google have announced that they also use artificial intelligence, and interest in machine learning and its application has skyrocketed.

What does this mean for SEO?

As it turns out, Google’s machine learning system, “RankBrain” is designed to help process its search results. That makes understanding how RankBrain works essential for SEO success.

Artificial Intelligence Versus Machine Learning

The terms artificial intelligence (AI) and machine learning (ML) are often used interchangeably but they are two different things:

  • Artificial intelligence can be described as the way machines operate intelligently. It’s the broader of the two concepts, encompassing machine learning and other “smart” tasks or operations.
  • Machine learning is a subset of AI that refers to how machines process data and learn on their own.

As technology has changed, AI has changed as well. Where the field used to focus on programming machines to complete complex tasks and calculations, the rise of the internet changed things. Now, with access to massive amounts of data, machines can be constructed to think like humans and make decisions on their own, as opposed to following instructions that told them what to do.

This affects search by allowing algorithms to try and understand the content they come across to deliver better results to search users. AI is one reason the “old hat” ways of optimizing sites no longer work.

Google and RankBrain

Google is putting AI and ML to good use. RankBrain is the machine learning process by which the Hummingbird algorithm works. RankBrain allows Hummingbird to sort through multitudes of data to find content that most accurately reflect the search query.

It is particularly effective on “long-tail” queries and unique queries because it is designed to recognize patterns and connect them with seemingly unconnected search queries. It alleviates situations where computers would typically get stuck on queries they were not familiar with or did not understand.

RankBrain works in conjunction with other factors or signals like links, content, and mobile-friendliness to help Hummingbird rank websites based on search queries. It refines search queries by identifying synonyms and related searches to return more appropriate results for users.

For example, if you searched for “shoes,” RankBrain would know to also include websites that contained the words “sneakers” or “flats.” As queries are conducted, the information goes into Google’s database of indexed pages, and RankBrain is able to learn which content is similar and which is not. It then uses that information to deliver more appropriate results as other queries come up.

In this way, RankBrain makes it less important for SEOs to use the exact right keyword to reach their intended audience and more important for SEOs to provide context around the keyword using appropriate content.

What About Bing?

We’ve spent a lot of time focusing on Google, but Microsoft and Bing also use artificial intelligence and machine learning to deliver SERP results. That system is called RankNet and it works in much the same way as RankBrain.

Microsoft has been a little more transparent about how RankNet works than Google has been about RankBrain. RankNet first emerged back in 2004 and is a “feedforward neural network model.” It processes data in a linear fashion, using parameters it has learned over time.

SEO Tips for Artificial Intelligence & Machine Learning

By now, you are probably wondering how you can work with these learning systems to optimize your websites. Unfortunately, since these systems are constantly learning and adapting to the way we conduct searches, there is no quick and easy answer.

It’s not practical to try and optimize for every obscure, long tail keyword a user may enter. Let’s take a look at what you can do to help make your site more visible to these systems:

  • Optimize content using semantic SEO to help search engines better understand the context of content.
  • Improve your internal linking structure to ensure links are relevant to the content.
  • Be judicious with your links. Too many links from one page reduces your authority.
  • Embrace mobile-first methods and technologies.
  • Adapt to voice search. Use natural language selections.
  • Build an active network of bloggers that you can regularly link to.
  • Take action to reduce bounce rates.

The use of artificial intelligence and machine learning in search is only expected to increase in the future. It will affect how sites are structured and the content they contain. The question is, when will you start to adopt AI-friendly strategies?

One Response to “AI & Machine Learning: Why Local SEO Experts Should Care”

  1. Soumya Roy says:

    Semantic SEO is the future. Topical, intent based and conversational keywords are to be analyzed and used on page content and those must come naturally in the flow of writing.
    Voice search is going to be one big shift from how we search traditionally using keyboard to how we can talk with search engines. Obviously conversational and long tail keywords are going to be more important in coming days.
    AI & ML are going to be really interesting to see in coming years.

    Regards
    Soumya Roy
    Founder & Lead SEO Trainer
    PromozSEO.com

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