B2B contract churn prediction

The problem

Recurring-revenue accounts rarely cancel loudly. Orders shrink, then the customer quietly switches supplier. By the time anyone notices, they have committed to a competitor, and blanket retention offers waste margin on accounts that were never leaving.

The approach

Score every account continuously on its behaviour, rank by revenue at risk as well as probability, and give customer success the why and the next action. In B2B one large account outweighs many small cancellations, and the right intervention is a person, not an automatic discount.

Lead example: building elevator service contracts. Multi-year, auto-renewing and safety critical; lose the contract and you lose the building. The tells are slow payment and competitor quotes ahead of renewal. Context: mid-sized independent service companies of roughly $5M to $10M revenue and 10 to 50 staff. Other fits: commercial HVAC for hospitals and data centres, medical imaging service, aviation engine "power by the hour", uniform and linen leasing.

How it works

B2B churn prediction fuses behaviour signals such as declining orders, missed touchpoints, complaint tone, champion departures and competitor quotes into an account health score, ranks accounts by revenue at risk, and routes each one to a person with the reason and the next action.

Watch-outs

• One-time capital purchases are poor fits. No rhythm, no signal.
• Do not automate the save. Arm the account manager instead.
• The same signals predict expansion, so use them across the whole customer lifecycle.

Accelerators and stack

• Classical predictive ML (propensity and uplift)
• Generative AI to draft the risk briefing and outreach
• CRM account-health scoring in Salesforce and Agentforce

What it takes to start

Three years of orders or service tickets per account, renewal dates and CRM activity. A first ranked risk list can reach account managers in six to eight weeks.

The value is the handful of large accounts saved, not the average churn rate.

In short

Questions