How Search Engines Use Artificial Intelligence

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Search engines are incredible. You pop onto your favorite one, type in a few keywords, and magically the search engine has scoured the entire internet to find the most relevant content. Except it’s not magic, of course. It’s algorithms and a lot of ideas from a lot of brilliant people. And we’ve started to wonder: With all the brilliant minds behind them, to what extent are search engines using artificial intelligence?

Thanks to those same search engines, I was able to find some great research explaining how search engines use artificial intelligence.

Search Engines Use Artificial Intelligence For Quality Control

Back in the day, certain SEO “specialists” beat the system with shady practices that we’ve come to know as “black hat SEO techniques.” These include aggressive keyword stuffing, cloaking, invisible text—the list goes on.

Of course, this was damaging to search engines because the pages that were at the top of their results weren’t necessarily the highest quality content.

Nowadays, they’ve updated their algorithms and use AI to separate the high quality content from the low quality spam. We suspect that as AI progresses, it will completely take over this responsibility and remove the need for human quality raters entirely.

Search Engines Use AI To Create Ranking Algorithms

Not only does artificial intelligence protect search engines from manipulation, but it also helps them with their ranking algorithms.

It’s impossible to tell how big of a role AI plays in this, but search engines definitely use artificial intelligence to improve their ranking algorithms.

To get a little more technical, this specific area of artificial intelligence involves learning to rank algorithms. Machines are taught to create an optimal list from a set of possible outcomes, learning from each of the variables over time.

For example, if one result on a search engine is ranking third but has a higher click through rate than the options above it, the search engine would learn from this anomaly and bump that result to the top.

Search Engines Use NLP and Image Analysis To Understand Search Queries

Search engines are computer applications, but they need to be able to understand human language in order to find users the information they’re looking for.

That’s a textbook application of natural language processing (NLP), a field of AI dedicated to teaching computers to understand our written language.

At the very least, both Google and Microsoft are using NLP to understand their users.

A University of Washington study looked at Yandex, the world’s fourth largest search engine, and noticed that it has some advanced applications of NLP and machine learning. Yandex developers found that they could take all of their users’ previous searches and use them to optimize future searches. By creating these personalized search results, they’ve increased click through rate by about 10%.

Search Engine Journal also points out that Google uses some of the same practices by optimizing search engine results based on recent previous queries, and allows  users to conduct a search with nothing more than a photo (which uses another field of artificial intelligence).

What Does This Mean For SEO?

Here’s the big question for marketers: how will AI change the way we we optimize for SEO?

It’s pretty simple. Search engines are meant to find users what they’re looking for. With machine learning, it will get to the point where they will find exactly that.

That’s great for marketers because it means that the best, most relevant content will win. Choosing the right keywords and following best SEO practices will remain important, but, as search engines become more intelligent, the relevancy and quality of content will be the top ranking factors.

This article first appeared in www.marketingaiinstitute.com

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About Author

Mike Kaput

Mike Kaput is the Director of Marketing AI Institute and a senior consultant at PR 20/20. He writes and speaks about how marketers can understand, adopt, and pilot artificial intelligence to increase revenue and reduce costs

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