Fordel StudiosSaaS Churn Predictor
Predict churn 60–90 days before it happens and trigger retention while it still works.
The problem
being solved
A B2B SaaS company with 500+ accounts loses 5-8% of ARR monthly. The CS team reviews accounts at renewal — by which point a customer who stopped using the product 3 months ago has already decided to leave. Reactive retention has low success rates.
Gainsight pioneered health scoring with customizable metrics for proactive risk management. But scoring only works connected to action: knowing risk without triggering a workflow is just a dashboard.
The pattern: churn signals are visible 60-90 days before cancellation. Declining logins, reduced feature usage, fewer active users, negative support sentiment, payment delays. Companies that catch signals early and respond with targeted interventions retain significantly more.
How this
agent works
The agent monitors health signals continuously: product analytics (feature usage, logins, active users), support (volume, sentiment, satisfaction), billing (payment timeliness, plan changes), and engagement (email opens, CSM meeting attendance, NPS).
A gradient-boosted model trained on your churn history predicts per-account risk, updated daily. It learns which signal combinations predict churn for your product — for some, declining API usage is strongest; for others, support sentiment. Feature importance transparent.
When risk threshold is crossed, configured workflows trigger: CS alert with context, automated check-in, usage tips for undiscovered features, or AE escalation. Each intervention mapped to the specific risk signals.
A senior engineer connects your existing stack — Segment, Amplitude, or Mixpanel for product usage; Salesforce or HubSpot for CRM; Stripe or Chargebee for billing — and trains an XGBoost model on 12+ months of your historical churn data. Feature pipelines run on dbt, with Celery handling scheduled scoring jobs and Redis caching live health scores for low-latency API reads via FastAPI. Risk thresholds trigger downstream actions: CS team alerts, automated check-in sequences, or AE escalations, mapped to specific signal combinations. Setup takes 2-3 weeks including data validation, model tuning, and workflow configuration.
- 01
Multi-Signal Health Scoring
Combines product usage frequency, support ticket volume, billing events, and engagement metrics into a single composite health score per account. Scores update on a configurable schedule — daily by default — so your CS team always has a current view without manual reporting.
- 02
Gradient-Boosted Churn Model
XGBoost trained on your own historical data, not industry benchmarks. The 60-90 day prediction window gives enough lead time for meaningful intervention, and SHAP-based feature importance shows exactly which signals are driving each account's risk score.
- 03
Risk-Triggered Retention Workflows
When an account crosses a risk threshold, the agent fires a configured action: a Slack alert to the assigned CSM, a CRM task in HubSpot or Salesforce, or an automated in-app nudge toward an underused feature. Actions are tied to specific signal patterns, not just a generic risk score.
- 04
ARR-Weighted Risk Prioritization
Every at-risk account is ranked by ARR at stake, not just churn probability. A mid-risk $80K account surfaces above a high-risk $2K account — so your retention effort goes where the revenue impact is highest.
Build this agent
for your workflow.
We custom-build each agent to fit your data, your rules, and your existing systems.
Free 30-min scoping call