Original Summary

When 80 customers say they're leaving because of a missing feature. It may sound like a product problem. But what if 60 of those 80 customers signed up in the last 2 months? Suddenly, it is a different question. Maybe the feature isn't the real issue. Maybe we're attracting the wrong customers. Maybe we're setting the wrong expectations. Maybe onboarding isn't getting them to value. This is what makes churn data interesting to me. The reason tells you what happened. The pattern tells you where to look. I'm building ChurnIntel(my baby company) and have been digging into this lately. Do you segment churn reasons by things like tenure, plan, customer type or usage? Or mostly look at the overall numbers?   submitted by   /u/AppsolutelyGenious [link]   [comments]

  • 情报分类：综合情报
  • 分类依据：内容未命中明确的垂直分类规则，归入综合情报
  • 信息来源：Reddit · SaaS
  • 发布时间：2026/9/16 02:40:49