4 core ML models.
21 universal verticals.

Members quietly stop coming weeks before they cancel.

Patients drift to other providers when follow-ups slip.

Loyal regulars become "we used to go there" without a single complaint.

Morning regulars break their commute habit and settle into a new routine at a competitor café.

Clients miss their rebooking window and drift to competitors offering first-time discounts.

Guests rebook through OTAs instead of direct, costing 15–25% commission per stay.

Past attendees drift away between seasons and are expensive to re-acquire via ads.

Past clients drift to OTAs or competitors when you are not top-of-mind during their planning window.

Tenants send 30-day notices when it is already too late to find replacements without a vacancy gap.

Students mentally quit weeks before they formally drop — and most institutions only notice at the refund deadline.

Bill shock and service friction drive port-out requests — and once filed, save costs triple.

POS data shows a frequency drop only after the customer is gone.

Pre-approved leads go cold within days and at-risk borrowers shift to competitors with faster offers.

B2B accounts gradually reduce their share of wallet without warning until the quarterly report reveals a 30% drop.

Customers forget recurring service appointments and search for competitors when a problem appears.

Players close the app and may never return once they hit a friction point or boring cycle.

Workshop loyalty drops 60% once the free OEM service window ends and customers switch to independent garages.

Pet parents miss grooming and vaccination appointments, drifting to other local providers.

Policyholders shop for cheaper quotes on comparison sites during the renewal window when 90% of churn happens.

Users churn quietly when they stop getting value, often without a complaint.

High customer acquisition cost (CAC) makes one-time shoppers unprofitable.

High churn rates in the first 3 months of a subscription.

Retailers gradually shift orders to competitors without warning until your quarterly report shows a revenue drop.

Every business loses customers, but the patterns are unique to your industry and hard to detect manually.