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The Earth’s population is around 8 billion. That crazy number doesn’t include our nonhuman friends Siri, Alexa, Google Assistant, and other digital helpers, but perhaps it should, as they’ve stealthily become a force to be reckoned with. In fact, did you know that by 2024, there will be more digital voice assistant units on the planet than people?
The computer-science technology bringing our digital assistants to life is conversational search (not to be confused with conversational commerce). This game-changing digital tool lets people speak naturally, in English or their native language, as they might to a friend, instead of staring at a screen and typing or tapping a standard Google search query or entering words in a company’s search box.
Conversational search sounds like it should be the same concept as voice search. Not exactly. Voice search allows people to speak queries — such as when asking an app interface on their iPhone for information — but receive answers in text (or even spoken, but not in a way that resembles a conversation). Conversational search is just that: an easy-feeling dialog that can accommodate follow-up questions.
Traditionally, search engines have relied on keywords from query text to navigate indexes and databases. This process becomes more difficult with conversational search, as the keywords must be derived from sentences that are semantically and structurally more complex. With the rise in voice-first devices such as virtual assistants, search technology is being pushed to comprehend more-complex natural language patterns.
As opposed to what goes on with traditional keyword search, a conversational search system processes complex sentences and factors in context from users’ previous interactions to provide ever more comprehensive search results pages that get at the heart of a user’s intent. Machine learning and natural language processing (NLP) utilize algorithms to translate spoken queries into structured material and fetch relevant information.
As conversational search becomes more deeply ingrained, companies are realizing its value in creating meaningful, personalized recommendations that eclipse the transactional nature of search in the past. The improvement of conversational search is making people more reliant on their virtual assistants as they form implicit “partnerships” for exploration and problem solving with their go-to tools, rather than just executing basic transactional tasks. This technology is popping up virtually everywhere; for instance, now you can even talk to ChatGPT.
There’s no downside to businesses being able to provide interactive search capabilities that support shoppers and subscribers in locating exactly what they need, as opposed to being restricted by small targeted groups of keywords. And by tracking data about someone’s purchasing patterns, a virtual assistant can then authoritatively recommend products and services that meet their informational needs, even if they may not have necessarily been aware of those needs.
Conversational search boils down to this: rather than searching for specific products by inputting keywords, people can utilize this transformational technology to clearly deduce what they want and need, then focus on getting it.
What do these changes in search functionality mean for online businesses? The ways products and services are being marketed are changing profoundly. In the same way that consumers at home — whether they’re in the Bay Area or New York or beyond — have come to rely on their digital assistants, on ecommerce websites and in apps, they expect to have rich and rewarding conversations with chatbots.
The takeaway: Ultimately, they may be less likely to visit online platforms that rely solely on keyword-search mechanisms. Organizations that rely on search should upgrade to incorporate conversational search functionality that allows them to better meet their users’ needs.
If your search could desperately use a facelift, we want you to know we’re adding artificial intelligence–aided conversational search experience features to our user-experience toolkit.
We transform complex voice requests into structured patterns that a computer can understand. Removing irrelevant words and constructions that may complicate information retrieval is one tactic. We can also reduce the sizes of datasets to be searched. By applying filters based on search query rules and using personalization and context, our technology can return search results faster and with better accuracy.
In short, to optimize search, our API will be able to extract query information from even complex spoken sentences and add context based on people’s previous interactions.
So your search for help with upgrading could be over. What’s next?
We look forward to conversing naturally with you.
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