Revenue Rescue Inbox: Find customers at risk before you lose revenue

Revenue Rescue Inbox is the win-back workspace for SaaS and subscription teams. Detect churn risk, automate win-back flows, and recover MRR from one unified inbox.

I built Revenue Rescue Inbox after noticing a simple but costly problem: most small teams don’t lose customers in one big moment — they lose them silently, without noticing until it’s too late. In conversations with founders and operators, the pattern kept repeating: they know churn exists, but they don’t have a clear, daily view of who is at risk and what to do about it. Most tools either focus on high-level dashboards or require complex setup that doesn’t translate into immediate action. I started by exploring Stripe-based churn analysis and retention dashboards, but quickly realized the real need wasn’t more charts — it was a simple, actionable inbox of “who might churn today” and what to do next. That’s how Revenue Rescue Inbox evolved: from analytics ideas → to a lightweight CSV-driven workflow that surfaces at-risk customers and turns them into a daily action list. It’s still early, and I’m mainly trying to validate one question: If you had a daily inbox showing revenue at risk + suggested actions, would that actually change how you work? Would love feedback on whether this is useful in real workflows or still too noisy / abstract.

finally something that puts churn signals and reply drafting in the same screen, saved me from jumping between three tools. the risk scores felt accurate on my test accounts too.

@ltfiyeksakg6v5 Really appreciate this — this is exactly the problem we were trying to solve.

We found most users were switching between 3+ tools just to understand churn signals + draft responses.

Curious: what type of accounts did you test it on? We’re improving the scoring model based on real usage patterns.

finally something that puts churn signals and reply drafting in the same screen, saved me from jumping between three tools. the risk scores felt accurate on my test accounts too.

@ltfiyeksakg6v5 Really appreciate this — this is exactly the problem we were trying to solve.

We found most users were switching between 3+ tools just to understand churn signals + draft responses.

Curious: what type of accounts did you test it on? We’re improving the scoring model based on real usage patterns.