Digital brands come in all shapes and sizes, and their customers are equally if not more varied. Despite the numerous differences among digital brands, one thing unites them all: their customers want highly personalized and relevant product recommendations and customer service. One of the methods of delivering a hyper-personalized experience is through cognitive search.

What Is Cognitive Search?

Cognitive search is AI-powered search technology that can understand and anticipate the needs of a customer who visits a brand’s website, and connect them to the information they are looking for. At its core, the technology employs AI techniques such as natural language understanding and machine learning to ingest, organize, and query from multiple data sources. Cognitive search allows people to find digital content from multiple sources and goes beyond returning single documents with keyword matches, and actually is capable of sharing full answers contained within said document. Through these techniques, it can understand the needs of customers and match them with content or people that would provide a better experience.

How Does Cognitive Search Work?

Cognitive search deepens the level of personalization for customers by using Natural Language Processing (NLP) and machine learning to understand product specifications, descriptions, and images in a catalog. Both machine learning and NLP also enable the ability to predict and create personalized experiences for each individual customer. Cognitive search has the ability to support multiple channels (such as customer profile, product content itself, customer service repository, or third party data) and continuously learn and iterate from each customer interaction.

What to Consider In a Cognitive Search Platform

There are a lot of ways cognitive search is highly beneficial to digital brands, and brands should heavily consider the benefits of investing in cognitive search technology. Among those benefits are a handful of key elements that every brand should consider:

  • Information: The best cognitive search platforms will be capable of connecting massive catalogues of information including product info, customer transaction data, point of sale data, inventory data, sales and CRM data, supply chain info and more.
  • Intelligence: Cognitive search must understand customers’ intent in their moment of need, understand the relevancy of content it surfaces to each customer, and automatically tune to improve intent and relevancy on an ongoing basis.
  • Operations: Usage analytics measure the success of search results. Tuning tools let users override what the solution has learned in special circumstances such as a promotion or overstocked inventory. Combining these operationally delivers a powerful but flexible digital commerce application.
  • Applications: Pre-built applications and solution accelerators can create cognitive search applications beyond simple search results. A RESTful API, software development kits and visual development tools allow businesses to infuse cognitive search in their digital commerce applications.
  • Architecture: If the commerce application goes down, the business goes down. Therefore brands need a highly scalable distributed architecture that allows for a variety of deployment models.
  • Innovation: There are few technologies innovating as rapidly as AI. The open source community is hosting much of this innovation, meaning solutions based on technology such as Apache Solr can be desirable.

Through a combination of natural language understanding and machine learning, cognitive search can enable the highly relevant and personalized experiences that customers now demand and empower brands to give that to them.

Interested in what cognitive search can do for your brand? Take a look at our Cognitive Search Continuum designed to help retailers optimize their search platform from simple catalog search to a hyper-personal customer experience. Or get in touch with us today for a demo.

About Dev Bhat

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