Turn renewal risk into renewal readiness — weeks before the window opens.
For businesses running on multi-year service or subscription contracts, renewal revenue is the most predictable — and most preventable — source of churn. Yet most organisations manage renewals on a calendar, not on risk signals.
By the time a customer signals disengagement, the renewal conversation is already compromised. The accounts that needed proactive attention three months ago are the ones that lapse today.
Contract age & term structure · Service delivery performance history · Engagement frequency & recency · Support ticket sentiment & volume · Payment pattern changes · Prior renewal behaviour · Economic & market context
We map every active contract against its renewal timeline, service tier, and historical renewal pattern — establishing a baseline that distinguishes at-risk portfolios from stable ones.
We train renewal risk models on your historical outcomes, incorporating service performance, engagement decay, and payment signals — producing a calibrated risk score per contract.
Contracts are scored continuously, with risk elevations triggering alerts to service and sales teams well ahead of the renewal window — when intervention is still effective.
Beyond the score, we deliver actionable playbooks: which accounts to call first, what issues to address, and what interventions have worked for similar risk profiles in the past.
A global B2B services company with 250,000 renewable service contracts deployed our renewal forecasting model alongside an AI-powered retention assistant — shifting the entire organisation from reactive to proactive renewal management.
Read the case study →Before the engagement, renewal outreach was calendar-based — teams worked renewal lists in date order. After deployment, outreach was risk-ordered and contextualised, with the highest-risk contracts receiving attention months before their renewal dates.
We can model your contract portfolio and give you a risk estimate before the engagement begins.
Get a portfolio assessment