Customer Health Score
Optimization
Most health scores are vanity metrics — green lights everywhere until an account suddenly churns. We build health scores that actually predict risk, surface expansion signals, and drive your team to action.
Why most health scores
don't work.
Wrong inputs
Health scores built on login frequency and NPS alone miss the signals that actually predict churn: usage depth, feature adoption, stakeholder engagement.
No action triggers
A score that turns red without triggering a playbook is just a notification nobody reads. Scores need to drive specific, automated next steps.
One-size-fits-all
Enterprise accounts and SMB accounts have different health indicators. A single scoring model can't serve both segments accurately.
Health scores that drive
revenue, not dashboards.
Calculated Metrics Engine
We leverage Planhat's calculated metrics to combine product usage, engagement depth, support sentiment, and financial signals into composite scores weighted for your business model.
Segment-Specific Models
Different scoring models for enterprise, mid-market, and SMB segments — built with custom dimensions so each is calibrated to the behaviors that actually predict retention in that tier.
Time Series & Usage Intelligence
Planhat's time series data tracks feature adoption, MoM engagement trends, and usage velocity over time — not just login counts. We turn that raw signal into scoring inputs.
Playbooks & Automated Sequences
Health score changes automatically trigger the right playbook or sequence: CSM alerts, executive escalation, expansion outreach, or renewal preparation.
Trend Analysis
Track health score trajectories using time series data. A score of 70 trending down is more dangerous than a score of 50 trending up — our models capture this.
Continuous Calibration
Health scores aren't set-and-forget. We continuously calibrate calculated metric weights and thresholds against actual churn and expansion outcomes.
What optimized health scores deliver.
Automated health scoring and proactive churn playbooks identified at-risk accounts 60 days before renewal. Team went from reactive to data-driven within one quarter.
Health scores and automated alerts caught three renewals the team would have lost. CSMs saved 15+ hours per month on manual health checks.
Leaders who trust our work.
We finally stopped guessing which accounts were at risk. The health scores and automated alerts caught three renewals we would have lost.
Working with NRR Partners gave our CS team real structure for the first time. We finally have visibility into account health and a playbook that doesn't depend on tribal knowledge.
They rebuilt our entire Planhat instance in six weeks. Our CSMs went from dreading the tool to relying on it daily. The forecasting alone was worth it.
Ready to build health scores
that actually work?
Tell us about your current setup. We'll audit your health score architecture and show you what's missing.