Customer Health Intelligence
Transform reactive firefighting into proactive customer success with AI-powered health monitoring that predicts risks and drives retention.
Customer Success teams manage hundreds of accounts with limited visibility into what's actually happening. BuildBetter changes that by analyzing every customer interaction, surfacing health risks before they become problems, and providing actionable insights that help you retain and grow your customer base.
Traditional health monitoring is fundamentally broken
- 60% of churned customers showed no obvious warning signs
- CSMs spend 40% of time gathering data instead of helping customers
- Health scores are 6+ weeks outdated by the time they're reviewed
- Only 23% of risks are caught before escalation
- $75B lost annually to preventable churn in SaaS alone
Capabilities
360° Health Scoring
AI analyzes all touchpoints to identify satisfaction trends and risk signals across product usage, sentiment, and engagement.
Risk Detection
Surface hidden risks across product usage, sentiment, and engagement before they escalate into lost accounts.
Churn Prediction
Identify at-risk accounts 90+ days before renewal with 87% accuracy, giving your team time to intervene.
Success Automation
Trigger proactive interventions automatically based on health score changes and risk signal combinations.
How to get started
A structured approach to rolling out this workflow in your team.
Foundation — Week 1
Connect your data ecosystem
Integrate CRM, support tickets, product analytics, and communication tools to create a unified view of customer satisfaction signals.
Define your health model
Build a multi-dimensional scoring framework covering product health (35%), relationship health (30%), support health (20%), and commercial health (15%).
Launch automated monitoring
Operationalize health tracking across all accounts with real-time workflows, alert tiers, and team enablement on intervention playbooks.
Intelligent Interventions — Weeks 2–4
Proactive risk management
Automate risk playbooks for high-risk accounts — schedule executive check-ins, generate recovery plans, and alert CS leadership within hours of a score drop.
Sentiment and engagement analysis
Track sentiment across calls, email, support interactions, and meetings to spot inflection points and predict future trajectory.
Usage intelligence
Compare each account's adoption journey against successful customer benchmarks, identify gaps, and recommend the next features to drive value realization.
Strategic Growth — Month 2+
Expansion intelligence
Score accounts for expansion readiness, analyze whitespace in licenses and departments, and surface optimal timing to maximize close rates.
QBR automation
Generate complete QBR packages — executive summary, value realization report, usage analytics, and strategic roadmap — in minutes instead of hours.
Renewal intelligence
Predict renewal probability months in advance, trigger automated outreach at the right intervals, and arm negotiators with historical patterns and pricing intelligence.
Playbook Execution — Ongoing
Red account recovery
Immediate AI triage, executive alignment within 48 hours, daily stand-ups with the account team, and stabilization monitoring through 90 days.
Expansion acceleration
AI-driven opportunity identification, ROI story development, strategic engagement with new stakeholders, and formal proposal to close.
Proactive success maintenance
Document and amplify wins, map the full organization to build multi-threaded relationships, and create long-term partnership through multi-year commitments.
Before & After
Real-world impact teams see after adopting this workflow.
Best Practices
Recommended Practices
- Monitor daily, act immediately — health scores checked daily catch 3x more risks than weekly reviews.
- Combine 5+ data sources for 90%+ prediction accuracy — multi-source truth prevents blind spots.
- Automate everything possible — CSMs using automation handle 2x more accounts without sacrificing quality.
- Segment intelligently — enterprise accounts need different health models than SMBs for 40% better accuracy.
- Close the loop — always measure intervention impact and refine playbooks based on what worked.
Watch Out For
- Ignoring gradual decline — slow health erosion is harder to reverse than sudden drops.
- Over-relying on single metrics — usage alone misses 60% of churn signals.
- Delayed intervention — every day of delay reduces recovery success by 5%.
- One-size-fits-all approaches — generic models miss segment-specific risk patterns.
Pro Tips
- The best churn predictor is often 2–3 indicators combined. Single metrics lie, patterns don't. Look for signal combinations.
- Build separate health models for enterprise and SMB segments — you'll see 40% better prediction accuracy.
- Share sentiment trends and feedback themes with customers in QBRs. Transparency drives accountability and often self-corrects issues.
- Use AI for data gathering and initial analysis. Save human creativity for relationship building and problem solving.
Ready to turn every customer conversation into actionable health intelligence?
Join thousands of teams already using BuildBetter to turn customer conversations into actionable insights.