conversational search

We are witnessing the immerse rise in voice based devices and services (like virtual assistants, voice based apps and services) over the past couple of years. Accordingly, search technologies are also being pushed to improve and understand more complex natural language patterns. It is estimated that by 2023 there will be 8 billion voice assistants used around the world. So it is no surprise that conversational search is consistently being lookedat as the technology that will drive this search revolution. 

Conversational search allows users to express their ask (e.g queries), using free language in either voice or text, and receive answers that mimics the feels and looks of a conversation. In contrast to the more traditional keyword based search, the conversational search technology can analyze complex grammatical sentences and will draw from previous interactions to provide better and more comprehensive results.

Conversational search differs from voice search that allows users to submit spoken queries, but which returns answers in text, voice, or other formats that do not convey the feeling of a conversation.

Say goodbye to traditional keywords

Search systems are traditionally using literal keywords extracted from the query text to navigate their databases and indexes. However, with conversational search, this becomes significantly more challenging, as the underlying keywords have to be derived from sentences that are semantically and structurally more complex. Here, machine learning and methods of natural language processing (NLP) come into play in order to convert these human interactions into structured formats that can be used to retrieve relevant information.

conversational search elaborates the need for specific keywords
No need to exhaust your consumers with looking for exact keywords

Designing a new conversational search

There are a number of strategies that can be used to convert voice requests into structured patterns that the computer can understand. One tactic is to modify or remove stop words, or to ignore irrelevant words or constructions that might complicate the search. Other techniques aime at reducing the haystack, or the volume of what needs to be searched. By applying filters based query rules and incorporating personalization and context, the search engine is able to return results more accurately and faster.

Search: from transactional to interactive

Currently, search is mostly transactional, in that users ask for something particular and search engines try to deliver it. However, this is rapidly changing. Retailers realized the huge value of creating meaningful, smart and personalized interactions and recommendations that will encourage user engagement (and discoverability) with specific products or content. 

Today, it is obvious that businesses have to provide search capabilities that are better than ever and can support users sophisticated search patterns and needs, whether it is through text or voice.

The future of conversational search

As conversational capabilities improve and translate into better search experience, different platforms (virtual assistants, websites, and apps) will have a more comprehensive interactive dialogue with customers. For example, with enough data based on a user’s history and purchasing patterns and behaviors, an AI assistant can recommend products and services that better fit the unique needs of a customer, and that the customer may have not been aware of otherwise. 

Conversational search find the best product for your need
Conversational & isual earch with nexc.ai

These major improvements in conversational and search technology, could also create users that rely more on their AI assistants. It is not just for simple transactional tasks anymore, but a true personal help. As technology increasingly becomes a tool for smart, personal exploration and product discovery and deep product understanding. Rather than looking at numerous products, countless websites and reading endless reviews, consumers are now able to begin the search process by deducing what they actually need and accordingly find specific products that best fit their unique requirements (you can learn more about nexc.ai)

The full implications and options presented by these new technologies present are yet to be realized. What is clear is that the methods of marketing products and services are about to change very quickly. Customers are already expecting elaborated experience that is very efficient, personal and has conversational AI options in it. What is clear is that new ways for shopping are on the verge of exploding. For example LG announced a new smart TV app that will support voice based shopping that includes the visual experienxe as well (unlike smart voice assistants in which you can not see the product). This type of new options will enforce retailers to create sufficient infrastructure that will support these coming shopping trends.