Intercom + Improvado MCP — Conversations, Instantly Queryable

CSAT fell 12 points last month. Finding out why means manually reviewing low-rated conversations, tagging themes, cross-referencing assignees and response times, and building a summary. By the time the analysis is done, another month has passed and the underlying issue has grown.

Improvado's MCP server lets your AI agent query all low-CSAT conversations for the period, extract the common themes, identify which teams and topics drove the score down, and generate a root-cause summary — in under 10 minutes.

Customers who are about to churn often signal it in support conversations — mentioning competitor names, asking how to export data, or expressing repeated frustration. But nobody reads every conversation. By the time CS notices a churn risk, the customer has already decided.

Your AI agent scans Intercom conversations for churn signals at scale. It identifies customers using churn language, tags them in Intercom, and alerts your CS team — giving them a window to act before the customer churns.

A product change causes a surge in support tickets. The first sign is the support team complaining they're overwhelmed — hours after the spike started. There's no automated monitoring, so response times deteriorate before anyone adjusts staffing or triggers an engineering response.

The MCP server monitors Intercom conversation volume continuously. When an anomaly is detected — volume spike, new topic category emerging, or SLA breach rate climbing — your AI agent sends an immediate alert with topic breakdown and affected customer segments.