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6. Removing Exact Keywords from Search (Classification)

The Challenge​

Search engines and internal systems that depend on exact keyword matching present several issues. Users may not always know the precise wording or phrasing to use, resulting in poor search results. This is particularly evident in platforms that have multiple layers of categorization, where a simple variation in word choice can drastically affect the outcome of the search.

For example, a user trying to find information on "Income Growth" may enter "increase money" or "get rich" and fail to find the appropriate resources if the system is reliant on exact keyword matches. This disconnect between how users search and how information is stored can lead to frustration, increased customer support inquiries, and wasted time.

Key Problems:​

  • Keyword Dependence: Exact keywords are required to retrieve relevant results.
  • User Frustration: Users often don’t know the correct terminology.
  • Poor Search Accuracy: Inconsistent or irrelevant search results due to keyword mismatches.

Gen AI Solution​

Gen AI-powered search systems move beyond exact keyword matching by leveraging natural language processing (NLP) and intent recognition. Instead of requiring users to input specific terms, Gen AI understands the user's intent behind a search query, even if it doesn’t match predefined keywords. By interpreting the broader meaning and context of a query, the AI can map it to the most relevant category or result, improving search accuracy and user satisfaction.

For example, if a user types in "I want to find ways to get rich" the AI can infer that the request relates to "Income Growth" without needing an exact match. Similarly, for internal systems, if a user searches "how to set up email," the AI can recognize that this falls under "IT setup" or "email configuration" categories, even if the words don’t directly match the stored keywords.

This adaptability makes the search experience more intuitive and dynamic, catering to a wide variety of user inputs.

Key Benefits:​

  • Improved Search Relevance: AI understands the meaning behind user queries, offering more relevant results.
  • Reduced User Frustration: Users don’t need to remember exact keywords, leading to a smoother experience.
  • Learning and Adaptation: AI models learn from user behavior to improve over time.

Illustration​

  • Before (Anti-Pattern): Users must input exact keywords, which often results in failed searches or irrelevant results due to minor mismatches in terminology.
  • After (AI-Powered): Gen AI analyzes the intent behind the search query, classifying it into the appropriate category and returning relevant results even when exact keywords are not used.
Exact Keyword SearchAI-Powered Natural Language Search
Users must know and enter specific keywordsAI understands and classifies based on user intent
Limited search results based on predefined termsBroader, more relevant results from natural language
Frustrating and rigid search experienceDynamic, intuitive search that adapts to user needs

With AI-driven search classification, organizations can drastically enhance the user experience by reducing the dependency on exact keywords, making the system more intuitive, and ensuring that users always find the most relevant information quickly and efficiently.