Original Summary

I built Clovia. It is a Shopify app that watches every checkout journey, calculates the revenue lost to abandoned checkouts, and attaches the likely root cause with the evidence trail: payment decline codes, shipping failures, invalid discount codes, broken buttons, script errors. The lesson that shaped it: most stores I looked at were optimizing the wrong thing. They killed ad creatives when the real problem was an invalid discount code, or redesigned product pages when payments were failing silently at checkout. Aggregate analytics hide this. Session-level evidence does not. We launched on Product Hunt today: https://www.producthunt.com/products/clovia?launch=clovia Free plan is 200 checkout investigations a month, full features, no feature gates. Would appreciate your support, and I am curious how other SaaS builders here think about this: when your product's value is showing people a problem they did not know they had, what actually gets them to install?   submitted by   /u/yvcn [link]   [comments]

  • 情报分类：开源项目与落地
  • 分类依据：内容涉及项目实践、创业、副业或变现
  • 信息来源：Reddit · SaaS
  • 发布时间：2026/9/28 15:30:06