60–70% of B2B SaaS churn is predictable 90+ days ahead — signals sit in usage, NPS, and billing long before cancellation (OpenView). Only 28% of CS teams run systematic prediction (Gainsight); for the rest, 70–80% of the intervention window closes before risk surfaces.
Most CS teams learn about risk from the customer — 30 days before contract end, when root-cause resolution is impossible. The AI agent surfaces risk 90–120 days early, when the full retention toolkit is still available.
Without AI, enterprise accounts get weekly reviews while SMB tiers — 40–60% of total count — get only reactive support, accumulating silent churn. The AI agent monitors every account continuously.
CRM renewal pipelines run on rep optimism, not signals. AI probability-weighted forecasts improve accuracy 15–25 points over stage-based estimates, reducing the planning variance that forces conservative headcount decisions.
Six capability pillars that help CS and revenue operations teams protect ARR and drive NRR above 110%.
Six capability pillars that help CS and revenue operations teams protect ARR and drive NRR above 110%.
Scores every account across 50+ usage, CRM, support, billing, and sentiment signals — delivering real-time renewal risk probability, not weekly batch snapshots.
Monitors DAU/MAU, feature adoption, seat utilisation, and workflow completion rates — flagging deviations before they become irreversible.
Configurable playbooks for each risk tier — usage recovery, champion departure, competitive defence, executive re-engagement, and renewal acceleration.
Tracks login frequency by role, executive vs. end-user adoption gap, multi-threading score, and single-contact dependency risk per account.
Native connectors for Salesforce, HubSpot, Gainsight, and Totango — bi-directional sync of account health, opportunities, contacts, and activity.
Real-time ARR risk dashboard: renewal pipeline by risk tier, AI probability-weighted forecasts, and intervention coverage by segment.
At $50M ARR with 8% churn, $4M lost requires $20M–$28M in new bookings to replace. The AI Renewal Risk Agent monitors every signal across every account, triggering playbooks 90–120 days before risk becomes confirmed churn. Book a renewal risk assessment.
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A static health score is a weekly composite on a handful of signals. This agent monitors 50+ signals continuously, weights them with ML trained on your actual churn outcomes, and acts autonomously — triggering playbooks and escalating to leadership without waiting for a CS manager to notice.
50+ signals across five domains — Product usage (DAU/MAU, feature adoption, session frequency), CRM engagement (CS touchpoints, QBR recency), Support (ticket volume, SLA compliance, sentiment), Financial (payment timing, billing vs. commitment), and Relationship (champion stability, LinkedIn activity, multi-threading score).
Champion departure raises churn probability 40–60%. The agent monitors CRM inactivity, LinkedIn job changes, email delivery failures, and conversation intelligence drop-off, flagging the account the moment signals cross a departure threshold — so CS can build new stakeholder relationships before renewal.
Playbooks are configured in a no-code builder, no engineering required. Standard tracks cover Usage Recovery, Champion Departure Response, Competitive Displacement Defence, Executive Re-engagement, and Renewal Acceleration — every action is a CSM-reviewed draft, and the agent never sends without human approval.
CRM: Salesforce, HubSpot. CS platforms: Gainsight, Totango, ChurnZero. Product analytics: Mixpanel, Amplitude, Segment, Pendo, Heap. Support: Zendesk, Intercom, Freshdesk. Conversation intelligence: Gong, Chorus, Clari. Billing: Stripe, Chargebee, Recurly, Zuora. Custom sources connect via REST API and webhooks.
CRM stage-based forecasting ("Commit", "Best Case") ignores the usage and support signals that actually predict intent. The agent replaces static stages with signal-weighted renewal probability across 30/60/90-day cohorts, backtested and recalibrated each cycle.
6–8 weeks: API integration and historical data pull, model training and validation, playbook configuration, then phased go-live and CS training. Prerequisites are API access to CRM, product analytics, and billing, 18 months of renewal outcome data, and a CS or RevOps sponsor.
Bonami deployments consistently cut preventable churn 30–50% within 12 months — recovering $840K–$1.2M ARR annually for a $30M ARR company at 10% churn. CS monitoring time drops 40–60% and first-year ROI runs 300–500%, with investment recovered in 3–5 months.
Churn prediction software focuses on scoring renewal risk early; renewal management software focuses on running the playbooks that act on it. This agent combines both — scoring 50+ signals across every account, then triggering CSM-reviewed playbooks 90 to 120 days before cancellation, so prediction and action live in one tool.
Yes. The agent works as retention and churn analytics software at once, scoring every account continuously rather than in weekly batches. It surfaces at-risk accounts 90 to 120 days early, and its real-time ARR dashboard gives CS and revenue leaders churn analytics by risk tier, vertical, and cohort — trained on your own historical renewal outcomes.
