Voice search is growing, and we’re gradually moving away from keywords to semantic (and natural-language) search. In the process, search engine optimization (SEO) is about to get a lot more interesting.

I’ve talked before about the importance of voice recognition, and that trend has accelerated since I first started talking about it. We have Siri, and Cortana, and Alexa, and Ok Google. As a result, we’re asking questions and looking for directions and recommendations more and more via voice. And buying stuff too.

Here are just three key statistics:

  • There are now an estimated >1 billion voice searches per month (Alpine.AI)
  • 50 percent of all searches by 2020 will be voice searches (ComScore)
  • Voice commerce was a $1.8 billion retail segment in the U.S. in 2017 (Voicebot.AI)

Moreover, OC&C Strategy Consultants predicts that voice-based commerce will account for $40 billion in sales by 2022.

Is your business ready?

Voice search is different.

Voice search is different

We’ve been trained to think of search engines as inherently imprecise. Sure, Google’s always been pretty good at delivering your 10 blue links. But we were trained to talk in keywords and ask precise questions. So we’d type in “Chinese restaurants, Washington, DC,” rather than “What’s a good Chinese place to eat around here?”

Here’s another example of how voice search is different. When I did an initial keyword search for “voice search statistics,” I got some good answers but not exactly what I was hoping to find. Then I grabbed my smartphone and asked: “Ok, Google, how many voice searches were there in 2017?” Same results. But then I asked, “how often was OK Google used in 2017?” Alright, I didn’t find THE answer — but can you see how voice search moves away from keywords?

I’m no expert in this area, but it’s clear that organizations are going to have to rethink how consumers search for information. And then we’re all going to have to figure out how to adapt to this new reality.

Watch semantic search in action.

Google just unveiled two examples of natural language search. I’ve played with each, and each gave me a little better understanding of my keyword search tendencies and what’s possible moving forward.

In an article posted to Google’s Research Blog, the authors write:

We are proud to share Semantic Experiences, a website showing two examples of how these new capabilities can drive applications that weren’t possible before. Talk to Books is an entirely new way to explore books by starting at the sentence level, rather than the author or topic level. Semantris is a word association game powered by machine learning, where you type out words associated with a given prompt.

This stuff is fascinating. And it’s our future, so we better be prepared.

Search by João Silas (Unsplash).

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