User Intent and Adaptive Search

Search engines have an impressively difficult job to do. Finding websites, out of the billions on the internet, that are relevant to a certain search query, and then ranking them by importance, is a formidable task. But it might not even be the most difficult part of the search process. Just interpreting what the user is actually trying to search for can be just as daunting.

The Problem of User Intent

Not everyone crafts the most articulate Google search query. Sometimes, they can be ambiguous, or downright confusing.

Suppose someone gets on Google and types in “jaguars”. Is this a search for the luxury car? The predatory animal? The iconic Fender guitar? The allegedly professional football team from Jacksonville?

Obviously, each of these four options would require a completely different set of results to satisfy the user. Because the user’s intent is hopelessly ambiguous, whatever search engine they’re using gets put in the difficult spot of having to guess what they really mean. If the guess is wrong, the user gets frustrated, and the search engine has failed.

Enter: Adaptive Search

Search engines like Google and Bing have come up with ways to avoid this sticky situation.

Oftentimes, people get online and enter a sequence of queries into a search engine. First, they might look for “Montreal”. After scrolling through the results and clicking on some pages, they might return to Google and search for “hotels”.

The search for “hotels” is similar to the search for “jaguars” – there are serious questions about what the user wants to see. However, from the sequence of searches – first, “Montreal”, then “hotels” – it’s pretty clear that the searcher is looking for a hotel in Montreal.

By tracking a user’s prior searches and what they clicked on, search engines get important clues that help them determine the user’s intent for later searches. This is called adaptive search, because later searches adapt to what has happened in the past to bring better results.

Using adaptive search methods, Google could provide better results for the search “hotels” by noting the prior search for “Montreal”, and then include some hits for hotels that are only relevant to the Canadian city.

Limitations on Adaptive Search

While adaptive search techniques help search engines bring the most relevant results to a user’s query, no matter how ambiguous or poorly-phrased, search engines put a limit on how much adaptive search changes the results: If their adaptive search models drastically altered the results pages based on prior searches or web activity, then everyone would pretty much have their own personal Google. Because Google runs on advertising money, this would make it far more difficult for advertisers to target the groups of users that they’re interested in, something that Google doesn’t want to do.

Adaptive Search Impacts Your SEO Strategy

Because it has the power to change what results appear on the search engine results page, adaptive search can be either a help or a hindrance to your search engine optimization (SEO) efforts.

Hosting a legal blog on your firm’s webpage is a huge step towards making it more prominent. However, using search engines’ adaptive search models to boost your site even more is a task for SEO professionals. Myers Freelance is a firm of professional legal blog writers that understands all the ins-and-outs of the SEO world, to make your firm’s webpage jump higher for Google searches that bring you clients.