Original Summary

I’m building a SaaS product around churn detection, and I’m trying to understand how other SaaS founders actually approach this. The problem I keep running into is that most churn reporting tells you what happened after the customer has already left. What I'm more interested in is the period before that happens. For example, a customer: suddenly uses the product less stops using a feature they previously used regularly hasn't logged in for a while starts having more failed actions was previously active but their overall activity is declining Individually, these signals don't necessarily mean much. But together, they might indicate that a customer is becoming disengaged. I'm building Churnor around this idea: combining customer activity into a risk signal and showing why a customer is being flagged, rather than just giving a random churn percentage. I'm curious how other SaaS founders handle this today. Do you have a specific process for identifying customers at risk of churning, or do you mostly find out when they actually cancel? Disclosure: I'm the person building Churnor. I'm posting this primarily because I want to understand how other SaaS teams currently approach the problem.   submitted by   /u/Active_Pianist_5213 [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SaaS
  • 发布时间：2026/9/28 20:11:08