To calculate the health score, we give each customer's event(which we collect using Intercom) a weight that reflects the impact it has on the likelihood churn, then multiply the weight by the event count, and sum them up. In many existing tools, the weights are determined by gut. 😮
We love data. We don't have confidence using gut to determine which attributes or events contribute the most for a customer to churn. We find that using machine learning to analyze data gives us the most accurate result. 🤖
Seamless integration with Intercom's customer data as inputs to compute health scores.
Use machine learning to automatically assign weights to get more accurate health scores.
Receive timely notifications for your whole team via Email or Slack on health score changes.
Get early access before we launch on Product Hunt 👐