With the rapid rise in voice first devices like virtual assistants over the past few years, search technologies are constantly being pushed to understand more and more complex natural language patterns. It is estimated that by 2020 there will be over 100 million voice assistant users around the world. Conversational search is being consistently looked to as the technology that will power this search revolution.
It allows users to submit queries, typically through voice, and receive answers in the form of a conversation. As opposed to a traditional keyword search, a conversational search system takes complex grammatical sentences and can use context from previous interactions to provide more useful and comprehensive results.
Conversational search is distinct from voice search which allows allows users to submit spoken queries, but returns answers in text, voice, or other formats that don’t resemble a conversation.
Say goodbye to traditional keywords
Traditionally, search systems use literal keywords taken directly from query text to navigate their indexes and databases. This process, however, becomes significantly more difficult with conversational search, as the underlying keywords must be derived from sentences that are semantically and structurally more complex. Machine learning and natural language processing (NLP) help translate these human interactions into structured formats that can be used to fetch relevant information.
Designing conversational search
A number of strategies are used to transform complex voice requests into more structured patterns that a computer can understand. Removing stop words, or ignoring irrelevant words or constructions that may complicate the search, is one tactic. Others techniques aim to reduce the haystack, or the volume of what needs to be searched. By applying filters based on query rules and using personalization and context, the search engine can return results faster and with increased accuracy.
From transactional to interactive search
At this point, search is mostly transactional, in that users ask for something specific and search engines try to deliver it. However, this is quickly changing. Companies realize the value of creating more meaningful, personalized interactions and recommendations to encourage user engagement with specific products or content.
Therefore, it is important that businesses provide search capabilities that can support users with more complex search patterns and needs, particularly through voice.
The future of conversational search
As conversational search capabilities improve, virtual assistants, websites, and apps can have more intricate dialogue with customers. For example, with sufficient historical data on a user’s purchasing patterns and behaviors, a virtual assistant can recommend products and services that better fit needs a customer may have not been aware of otherwise.
The improvement of conversational search could also lead users to become more reliant on their virtual assistants, effectively forming an implicit “partnership” whereby the technology increasingly becomes a tool for exploration and problem solving rather than simple transactional task fulfillment. Rather than actively searching for specific products, people could begin to utilize the technology to better deduce what they actually want and need.
What these changes mean for online businesses is less clear, as the channel for marketing products and services will very quickly change over the coming years. It is very likely, however, that users will begin to expect this type of rich conversation with websites and apps, and they will be less likely to use those that rely solely on traditional keyword search. Organizations that rely on search should start building a rich, context-based search function that allows them to meet user needs better than before (and without being restricted by a small, targeted group of keywords).
Conversational search and Algolia
Conversational search is allowing consumers to more effectively interact with businesses with a personalized and context-based interface.
To help businesses more effectively interact with their customers over voice, Algolia has built a suite of technologies to help extract explicit query information out of complex sentences and to add context to searches based on previous interactions with users.
Learn more about the future of search in our ebook “The Next Tech Revolution Will Be Spoken.”