AI-Driven Customer Query Categorization & Analytics for KBs

The post describes CrawlChat's new feature to categorize AI-tagged questions from user documentation queries, enabling metrics and filtering. This capability, while specific to CrawlChat, reveals a broader SaaS opportunity. Many businesses with extensive knowledge bases or support systems struggle to extract actionable insights from the vast amount of unstructured customer questions. A standalone AI-powered service could automatically categorize these queries based on custom-defined topics, provide detailed analytics (e.g., question volume per category, trends over time, areas of confusion), and highlight documentation gaps or common pain points. This would empower companies to optimize their knowledge base content, streamline support, and better understand user needs. The product could be offered as an API or an integration with existing helpdesks (e.g., Zendesk, Intercom) and knowledge management platforms. Expected revenue could be subscription-based, tiered by the volume of questions processed per month or the number of active categories, potentially reaching $10k-$50k MRR within a focused niche.