Measure user intent & friction inside chat-based interfaces

Measure user intent & friction inside chat-based interfaces targets a $6.0B = 200,000 businesses × $30K ACV (conversational analytics & observability across enterprises and mid-market) total addressable market with medium saturation and a year-over-year growth rate of 30% YoY (MarketsandMarkets / industry reports estimate conversational AI and voice/chat analytics growing ~30% CAGR through 2028).

Key trends driving demand: Chat-first products are proliferating across SaaS, e-commerce and support which creates demand for specialized analytics to measure success.; LLM and embedding-based intent classification has improved accuracy and lowered cost, enabling automated labeling and clustering at scale.; Companies are centralizing telemetry and observability which opens the door for a conversation-centric analytics layer to plug into existing data stacks.; Privacy and compliance requirements are pushing businesses to audit conversational data and outcomes, increasing demand for tools that can both analyze and redact appropriately..