As Search Engines Grow Smarter and People Less So, the Impact on Users and the Web

Amit Singhal, the head of Google Search, stated that the more accurate search results become, the lazier the questions users ask become. As artificial intelligences behind the search engines become smarter, people’s queries of them become more generic, less precise and often simpler in general. Let’s look at these changes in greater detail and their impact on both websites and users.

 

Location Data

 

When the search engine already knows where you are located based on the geographic area in your profile or specifically where you are based on GPS coordinates, the end result is queries with far less location information. Instead of a query “cheap pizza near intersection of X and Y”, the user asks for “cheap pizza” and assumes the results will only show pizza places near their current location. When they search for an emergency room, they may only enter “emergency rooms open now” without any location information on the assumption the nearest ones will be the only ones presented. And if you have location tracking set up for your device, it will be.

Another side effect of having devices navigate for us is reliance on those same devices to help us navigate places, whether familiar or unfamiliar. Your website cannot simply say “we’re on the northeast corner of Main and Jones”. It needs to have a map capsule next to the address showing where the business is located. Navigation information when walking from the nearest major venue or driving down from the highway to your parking lot is essential for your website today – and increasingly, for the users themselves. They are less able to navigate now without the guidance of the device and follow its directions often as gospel, as the repeated news stories of people driving into the ocean or small alleys where they get stuck demonstrate.

Context

 

Initially detailed queries can become less detailed in follow up questions because search engines remember the context. For example, an initial query on “what famous person did X?” followed by “when did he do Y?” answers the second question based on the identity of the person called out in the first. Queries on the Apple iPhone error messages with a later query simply for “repair services” is likely to come up with authorized Apple repair services or the nearest Apple store because it remembers that context. This context based help will only grow as AIs learn individual users’ habits and the AIs themselves grow smarter in recognizing context. To what degree people start using privacy modes to not have embarrassing voice search results come up during company is to be determined.

When you’re creating content for these increasingly vague search queries, your context must be clear. You can’t rely on search term density to rank well because search engines are forced to determine the context of the query and the context for your content and try to match them well. This makes latent semantic indexing more important, so related terms pepper content so the context is properly understood by the AIs behind the search engine.

Voice search is raising the priority of highly detailed queries like “What does X error message on a Y mean?” in addition to the search term “X error message” and “Y errors”. Even then, content that clearly identifies the context helps it rank well. Mixing detailed queries with vaguer ones also allows the content to rank well whether with long tail voice SEO or more general follow up questions on the topic. Websites themselves have to alter content to include the full questions users are asking in order to rank well with voice search.

Querying What We Used to Remember

It has been said that the smarter devices become, the stupider the users become. The more likely explanation is that skills unused atrophy, and as we get used to having devices do things for us, the weaker those skills become for us.

More people rely on quick internet searches for information instead of trying to recall what they learned in school. This is part of the drive for instant answers and search engines’ preference for sites that provide them. Fewer people remember facts, and more of them will query for those facts instead of trying to remember them. And if you can always get the answer quickly through a query, why commit the information to memory in the first place?

If you’re creating content, you aren’t going to be able to compete with instant answers from higher authority domains. You can still create content that answers the long tail search terms and detailed queries few others will, such as trivia that doesn’t make it into Wikipedia and local knowledge few others document.

Another side effect of searching the internet for answers is the practice of using search engines as calculators. Whether it is asking what day is 19 days from today, unit conversions or actual calculations, search engines are more often being used to do math. For very simple calculations like 583 divided by 4 or the 15% tip for a $15.99 dinner, there are long tail queries that you can still monopolize. And you see more online calculators for the more complex calculations no matter how obscure the niche because of the growing demand and their value for long tail search queries.

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