We build the analytics layer that turns subscriber data into retention decisions. Churn cohort analysis shows how subscriber retention varies by acquisition date, acquisition channel, first product selection, and box tier. You see which cohorts churn at month two and which run for twelve months, and can target retention investment accordingly. MRR movement reports break down monthly revenue change into new subscriptions, expansions, contractions, pauses, and churn so you have a clear picture of what's driving revenue growth or decline.
LTV by channel and product surfaces the acquisition channels and product tiers that produce the highest lifetime value, and connects that data to the cancellation reasons captured at offboarding. Predictive churn scoring uses subscriber behaviour signals (skips, product swap frequency, support contact history) to flag subscribers who are likely to cancel before they do, so your retention team can intervene with a targeted offer.
Built for subscription brands making acquisition and retention decisions from blended metrics, operators who know their total churn rate but not its causes, and D2C brands that have subscriber data but no system that surfaces it as actionable retention intelligence.