How It Works

InQuira 7 Intelligent Search applications improve the quality of the customer experience across all customer interaction channels, including the Web, email, chat and phone. The key to InQuira's superior performance is its unmatched ability to understand natural language search intents. InQuira leverages that foundation of understanding natural language search queries to deliver a superior customer experience. InQuira's natural language search engine enables companies to directly answer their customers' immediate sales and service needs, and the ability to anticipate and fulfill subsequent needs during the same customer experience. Here's how natural language processing works:

  1. The first step, of course, is to capture the customer's question.
     
  2. In the second step, the natural language search engine technology processes the question for its intent by analyzing the language used, user session context and company-defined business rules. In terms of context, InQuira considers the customer's location on the website when he or she is asking a question, which can give further understanding of the natural language search intent. Customer profile and history information can be passed into InQuira from external systems, including security systems, CRM applications or any other application containing customer profile or history data that can be leveraged by InQuira to more effectively determine the intent of the natural language search. In parallel, company-defined business rules specify the delivery of marketing or sales information to a results page based on the intent of the customer's natural language search, the context of his search, or a combination of both.
     
  3. In the third step, the natural language processing system takes its understanding of the customer's search intent and creates a separate expert query for each appropriate content source that is going to be searched. Each of these expert queries is in the form that is going to be the most effective for delivering exact results, and the queries are processed in parallel. So there can be one natural language search engine query for web-based information, one for managed answers, one for applications, one for database, one for knowledge bases and one for any of the ad hoc information that may have been added to the InQuira repository.
     
  4. In step four, each query finds exact answers to the question from across various enterprise content sources.
     
  5. In step five, natural language search engine technology prioritizes, selects, and delivers exact answers to the dynamic results interface, which then presents a personalized results page and unique customer experience including relevant promotional offers, related information, and a relevant listing of related website links. The dynamic results interface returns sentence-level excerpts that directly answer the question, as well as the related information that makes it possible to anticipate and fulfill subsequent customer needs as part of the same customer experience.