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What Is Natural Language Search?

Search engines have improved dramatically since their introduction over two decades ago; they are now more capable of understanding more complex queries — which makes life a lot easier for us users. Remember back in the day when we would have to type in a query in Yoda-speak?

The quest for natural language search improvements across all search engines was accelerated due to increased use in mobile devices. With helpful tools such as Apple’s Siri, more users are finding it easier to perform a verbal search. Talking is natural to us, so why shouldn’t a search engine understand our natural language?

Enter: Natural Language Search

This type of search involves typing a query into a search engine using full phrases or even full sentences and questions. Google now has an answer for just about any “What,” “When” and “Where” question out there when it comes to anything regarding times, dates, distances and the like. Natural language search is different from keyword-based searches which are more simplistic and don’t involve compound words such as “and” “or” and “the.”

How Natural Language Search Improved Search Engines

These days, users expect an answer to any question they type into more advanced search engines such as Google. Not only do we expect an answer, but we expect it on the first try. This has put pressure on search engines to improve the quality of their search engines. Now, Google can understand questions that involve height, age, weight and ordered lists.

The push towards instant answers has brought about significant visual changes in SERPs. For example, when typing a question into Google, the answer will appear in the Knowledge Graph so users don’t even have to lift a finger to scroll down and click on a link.

What to Look for in the Future

Natural language search will continue to improve as more mobile device users get used to voice command searching. Don’t be surprised if you see more search engines, such as Bing, taking the natural language search further by allowing users to ask a follow-up question.

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