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A Renewal Risk Prediction Playbook ties usage trajectories, support patterns, and stakeholder activity to your contract calendar, so risk is visible 4 months before renewal instead of 4 weeks.
The Challenge
Most renewal motions kick in 60 to 90 days before contract expiry. By then the buyer has compared alternatives, started internal procurement conversations, and often had a competitor in for a discovery call. Discounting and "save" motions in the final 60 days mostly preserve revenue at lower margin, they rarely change the outcome.
CSMs and AEs flag risk based on the calls they have had recently. Quiet accounts default to "should be fine" even when the underlying data tells a different story. There is no systematic scoring that combines product usage, support history, stakeholder turnover, and sentiment into a single renewal-specific signal.
A budget-pressure renewal needs a different conversation from a champion-loss renewal which needs a different conversation again from a product-fit renewal. Most teams run a single playbook against every flag, which means the right tactic only lands by accident.
How eyko Solves It
A Renewal Risk Prediction Playbook connects usage data, support history, stakeholder activity, and CRM notes to the contract expiry timeline. It surfaces high-risk renewals 4 months out, attributes the risk to a specific driver, and recommends the retention strategy that fits the cause.
The Playbook flagged 9 contracts worth $3.6M ARR as high renewal risk for the coming quarter. Earliest risk signal in the cohort was detected 4 months before contract expiry. Product utilization below 30% is the primary driver in 6 accounts. Competitive displacement is suspected in 3 accounts based on a combination of executive sponsor changes and discovery-call language captured in CRM notes.
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Primary indicator | Flagged | Target | Action needed |
| Secondary indicator | Monitoring | Within range | On track |
| Trend direction | Declining | Stable | Review required |
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FAQ
Everything you need to know about Renewal Risk Forecast (Next 4 Months).
Renewal Risk Prediction is an AI-driven analysis that scores every active contract against expiry, combining product utilization, support history, stakeholder activity, and CRM notes into a forward-looking risk score. The output is a ranked list of at-risk renewals with the specific driver attached to each, so retention motions can start 4 months out instead of 4 weeks out.
The Playbook reads from your CRM (contract dates, account hierarchy, opportunity history), customer success platform (health scores, NPS, sentiment), product analytics (usage by feature and seat), and support system (ticket cadence, severity, sentiment). It also incorporates billing and pricing data to size the ARR exposure and any prior renewal history to calibrate the model.
The earliest reliable signal typically appears 4 to 6 months before contract expiry, when product utilization patterns diverge from the cohort norm. Stakeholder turnover usually shows 2 to 3 months out. The Playbook produces a confidence band so teams can prioritize the renewals where the signal is strongest and act early, rather than waiting for the formal evaluation phase where the decision is mostly already made.
Yes. The Playbook attributes every risk score to a specific driver: utilization decline, suspected competitive displacement, stakeholder turnover, support friction, or budget pressure. Each driver has a recommended retention motion attached: utilization risk pairs with an executive business review focused on adoption, displacement risk pairs with a competitive defense motion, stakeholder risk pairs with sponsor realignment. The result is a tactic chosen by the cause, not a single saver motion run against every flag.
Join the enterprises replacing weeks of manual analysis with a single prompt. See what eyko Playbooks can do with your data.
