Detect hidden churn from logins, feature usage drops, and payment failures

Detect hidden churn from logins, feature usage drops, and payment failures targets a $1.2B = 200,000 subscription businesses × $6,000 ACV total addressable market with medium saturation and a year-over-year growth rate of 12% YoY estimated for customer success and subscription analytics tooling driven by subscription model adoption (industry analyst synthesis).

Key trends driving demand: Subscription economy growth — more businesses run on recurring revenue, increasing the importance of retention and churn prevention.; Event-driven architectures and SaaS instrumentation are ubiquitous — easier access to login, feature and payment events enables automated detection.; AI-driven predictive analytics are becoming affordable — low-latency scoring and anomaly detection can be delivered cheaply to SMBs.; Payments ecosystem improvements — richer webhooks and payment-failure metadata make automated recovery more effective..