Chattermill is an AI-native voice of customer and feedback analysis platform. It brings feedback from every channel into one place, tags and categorizes each comment with models trained for customer experience, enriches signals with context such as customer ID, channel and location, and then answers questions about it. Its Lyra Agent works like an analyst: ask why NPS or CSAT moved, spot churn signals or understand product returns, and receive answers backed by quantified evidence, charts and direct customer quotes.
Chattermill is built for CX, insights and voice of customer teams at large organizations, along with product and operations leaders who depend on customer signals. Teams that currently read survey comments, reviews and support tickets by hand can hand the heavy analysis to the agent, while data and AI teams can plug Chattermill's verified intelligence into their own AI agents via MCP and Skills. Customer stories include Uber, which scaled CX intelligence over eight years, and HelloFresh, which reports raising average order values by 30% using feedback insights.
Typical uses include getting proactive insights delivered on autopilot, finding the precise issues behind a drop in satisfaction, identifying the big drivers that move NPS, and building custom reports and dashboards with advanced filters. Anomaly detection sends real-time alerts to Slack, email and Jira so critical issues are caught as they emerge, and impact analysis links customer signals to retention, churn and revenue with the help of a dedicated expert team. Enterprise-grade security and a library of integrations round out the offering.
