The Way We Search Is Changing: Why It Matters

Blog / Jess Parks Turcotte

Since the inception of the Internet, search engines like Google have been a primary access point of user experience. We rely on search engines to provide solutions to our problems. Anything we want to know--from driving directions to product research to a question about our favorite television show--is funneled through a search engine. Paths to consume content have begun to change, and businesses will want to adapt their web and mobile strategies to remain competitive and relevant.

Voice search and human language search are on the rise

Human language search, or natural language search, is not a new development (think back to Ask Jeeves in the 1990s), but it is one that has begun to catch on along with the rising popularity of voice search. Human language search differs from a more traditional keyword search in that queries are phrased as if you were talking to another person rather than generating a search solely using important terms. So you might ask “How many people live in New York City?,” versus searching “New York City population.” The end result of this trend is that users are posing questions with clearer context and intent and are receiving simple and direct answers in response.

Digital personal assistants are in our pockets

Many of us have access to our own AI assistant via our personal devices and smartphones. Apple’s Siri, Microsoft’s Cortana, Amazon’s Alexa, and the somewhat less popular Google Now all allow users to pose a question and receive an immediate, accurate response without having to dig through a list of search results. The implications that this advancement in technology have for SEO are significant. Businesses have typically aimed to be included in a search engine’s top three results, but digital personal assistants generate their responses solely from the top search result--meaning that the top search result will be the only one to maintain its relevance.

In-platform search results limit the need to scroll

In 2012, Google introduced its Knowledge Graph function. The goal was to enhance its search results by presenting semantic search information condensed as a short but detailed summary on the search topic as a “knowledge panel” at the top of a list of search results, negating any need for users to navigate beyond the search page or click through to other websites. This sort of direct data delivery has become more commonplace across other platforms, encouraging users to remain on or organically return to the original platform. This is one strategy to capture and maintain users’ attention, which is remarkably short. According to data from the Nielsen Norman Group, the average visit to a webpage lasts a little less than a minute, and often even less than ten seconds.

Personalized search results target users 

As search algorithms continue to develop and advance, search results as well as advertisements are becoming all the more targeted and personalized. Demographic data, browsing history, purchase history, geographic data--all of these data points can be compiled and used to connect to existing and potential customers on a completely individualized level. It may not be long before you are able to ask a question of your mobile AI assistant such as “What should I do today in Philadelphia?” and fully expect to receive a response that takes into account the day’s weather, the fact that you just purchased breakfast at a nearby café, and your personal interest in U.S. history based on your former search queries and purchases

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