Open Qlik’s Data Manager, configure the REST connector with your Intercom API token, and pull https://api.intercom.io/conversations . Your first insight is five clicks away. Have you connected Intercom to Qlik? What metric surprised you most? Share your experience in the comments below.
In Intercom, agents should tag conversations with topics (e.g., #billing-error , #export-slow ). In Qlik, count conversations by tag per customer. Then overlay that with your churn dataset. intercom to qlik
Load your conversations table and join it to a users table with a signup_date . Create a pivot table comparing first response time for week-1 users vs. year-1 users. Hypothesis: New users tolerate slower responses, but power users expect instant help. Open Qlik’s Data Manager, configure the REST connector
Avg(Churn_Rate) by Tag If #export-slow has a 40% churn rate and #forgot-password has 5%, you know where to send the product team. What metric surprised you most
Every day, your support team fires up Intercom to answer chats, close tickets, and engage leads. But buried inside those conversations is a goldmine of product feedback, churn risk signals, and sales intelligence.