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: 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 customers‘ needs when they visit a brand’s website and connect them to the information they seek. The search technology employs AI techniques such as natural language understanding and machine learning to ingest, organize, and query from multiple data sources. This form of search allows people to find digital content from multiple sources beyond returning single documents with keyword matches and can share complete answers contained within said document. Through these techniques, it can understand customers‘ needs 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 customer. Smarter search can 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

Cognitive search is highly beneficial to digital brands in many ways, 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 catalogs of information, including product info, customer transaction data, point of sale data, inventory data, sales and CRM data, supply chain info, and more.
  • Intelligence: 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 smarter search applications beyond simple search results. A RESTful API, software development kits, and visual development tools allow businesses to infuse cognitive search into their digital commerce applications.
  • Architecture: If the commerce application goes down, the business goes down. Therefore brands need a highly scalable distributed architecture for various deployment models.
  • Innovation: Few technologies are innovating as rapidly as AI. The open-source community is hosting much of this innovation, meaning solutions based on search technology such as Apache Solr can be desirable.

Real-World Applications of Cognitive Search

Search technology has been making waves across various industries, helping organizations unlock the potential of their data to deliver enhanced user experiences. Here are a few real-world applications and the industries they are transforming:

  • Retail: Retailers are leveraging cognitive search to provide personalized shopping experiences. By understanding shopper preferences and behavior, smarter search delivers product recommendations that hit the mark every time.
  • Healthcare: In the healthcare sector, cognitive search is utilized to quickly sift through vast amounts of medical records, research, and patient data to provide critical insights and expedite patient care.
  • Finance: The finance sector employs cognitive search to manage and analyze vast data. This enables them to perform better risk analysis, fraud detection, and customer service.
  • Education: Educational institutions are employing cognitive search to create dynamic learning environments. This type of search is shaping the future of education through personalized learning paths and easy access to educational resources.
  • Legal: Legal professionals use cognitive search to navigate libraries and case law. This makes legal research far more efficient and thorough.

These are just the tip of the iceberg. These applications can be seen across many industries, demonstrating their capability to speed up discovery and enhance decision-making.

Cognitive Search vs Traditional Search

The leap in search technology from traditional to cognitive search is a move from keyword-based retrieval to understanding user intent and context. Let’s break down the primary distinctions:

  • Understanding vs Retrieval: Traditional search operates on keyword-based retrieval. It locates documents that contain the specified keywords. In contrast, cognitive search understands the context and the intent behind the search query to provide more relevant and insightful results.
  • Static vs Dynamic: Traditional search results are static and do not change with user interaction. Cognitive search learns from user interactions and aims to refine the search results. This makes them far more personalized and accurate.
  • Single Source vs Multiple Sources: Traditional search often pulls data from a single source. In contrast, cognitive search pulls information from multiple data sources to provide a more well-rounded response to the search.
  • Keyword Dependency vs Natural Language Understanding: Traditional search relies heavily on exact keyword matches. Cognitive search employs Natural Language Processing to understand queries conversationally.

The transition to cognitive search represents a significant stride towards more intuitive, insightful, and user-centric search experiences. This aligns with the evolving expectations of today’s digital-savvy consumers.

Interested in what search can do for your brand? Look at our 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 Paolo Padua

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