Stop MRR leakage: detect failed payments and recover lost revenue

Many subscription businesses quietly lose several percent of monthly recurring revenue to failed payments and ineffective recovery flows; this problem is felt by an estimated 2,000,000 subscription companies that currently spend roughly $2,400 each per year on recovery and retention tooling. The consequence is predictable revenue leakage and higher CAC because lost customers must be reacquired rather than retained. You could build a SaaS orchestration layer that detects failed payments, classifies failure causes using richer Stripe/Braintree metadata, and executes intelligent retry schedules, card-updater integrations, automated omnichannel dunning, win-back offers, and continuous A/B testing — all exposed through an API and lightweight SDK for fast integration. A clear ROI dashboard and experiment framework would let finance teams measure incremental recovered MRR and justify the spend. This market looks timely: the subscription economy is still expanding so absolute failed-payment events are increasing, payment APIs now surface much richer failure signals, and companies under pressure from rising CAC are prioritizing retention where unit economics are strongest; the TAM implied here is $4.8B (2,000,000 businesses × $2,400), with a Market Score of 92/100 and Revenue Potential of 88/100. Those dynamics create a large, addressable opportunity for effective recovery tooling. To stand out you’ll need defensible data and models (shared learnings across merchants), seamless integrations that minimize engineering lift, and a rigorous measurement model that proves recovered revenue versus margin. Be honest about the challenges: competition is medium and includes payment processors and in-house teams, access to rich payment data requires merchant permissions and careful compliance, and pricing must demonstrate clear ROI to overcome switching costs.