Detect Churn Risk & Capture Retention Intelligence

Most companies learn why customers left after they're gone. Exit surveys get 3-8% response from people who've already decided and moved on. Win-back rates are 15-20% because you're fighting an executed decision.

Pulse Retention Agent detects churn risk through behavioral signals and direct questions, flags at-risk customers for retention team intervention, and captures patterns that inform systemic fixes—preventing churn both individually and strategically.

This bridges learning and action: Save high-value at-risk customers through early intervention + prevent future churn by fixing what drives it.

How It Works

Detect → Churn risk signals (declining usage, support issues, pricing page visits from existing customers, stated dissatisfaction)

Diagnose → Questions reveal dissatisfaction, value gaps, competitive consideration ("How likely are you to continue?")

Dual outcome → Flag individual for retention team intervention + capture patterns driving churn across base

Tactical value: Identify who's at risk while there's time to save them. Strategic value: Understand what causes churn to prevent it systemically.

The Big 3 Risk Detection Moments

1. Likelihood to Continue (Direct Risk Signal)

Strongest churn predictor.

Signals: Quarterly check-in, after support issues, billing events, usage declines

Question: "How likely are you to continue using [Product]?"

What you learn:

• Individual risk level ("Very unlikely" = emergency retention flag for team)

• Pattern by segment ("Enterprise customers in month 6 show declining intent")

• Reasons driving hesitation (informs both intervention approach and product strategy)

Tactical value: "Unlikely" responses trigger immediate retention team outreach within 24 hours

Expected lift: 25-40% save rate when early detection enables proactive intervention

2. Value Perception Gap

Customers who don't see ROI won't renew.

Signals: Before renewal, after price increases, periodically for active customers

Question: "How would you rate the value you're getting for the price?"

What you learn:

• Individual risk ("Poor value" = considering canceling, needs immediate ROI demonstration)

• Pattern by tier (which pricing tiers have value perception issues)

• What outcomes would justify price (informs retention messaging and product positioning)

Tactical value: "Poor" or "Fair" value scores trigger retention outreach to demonstrate ROI or offer alternatives before renewal

Expected lift: 30-45% improvement in pre-renewal save rate with early value gap detection

3. Competitive Consideration (Imminent Risk)

Active comparison = highest-priority saves.

Signals: Pricing page visits from logged-in users, declining usage, support escalations

Question: "Are you currently considering alternatives?"

What you learn:

• Individual urgency ("Yes" = actively shopping, decision imminent)

• Competitive intelligence (who you're losing to, what they offer that you don't)

• Why they're looking (product gaps, pricing, support issues, specific features)

Tactical value: "Yes" responses are emergency flags—retention team intervenes within 24 hours with competitive positioning

Expected lift: 20-35% save rate when competitive consideration detected before decision made

Five More Intelligence Opportunities

Frustration Point Identification
After support interactions, during usage, quarterly. Ask: "What frustrates you most?" Learn: Individual pain points + most common frustrations driving churn. Flag: Severe frustration triggers at-risk status.

Success Outcome Gap
After onboarding, quarterly, pre-renewal. Ask: "Are you achieving what you hoped to?" Learn: Who's not succeeding + common success gaps. Flag: Low success scores trigger customer success intervention.

Retention Driver Identification
From long-term happy customers. Ask: "What keeps you here?" Learn: What creates loyalty (emphasize in retention outreach and onboarding).

Improvement Priority
From at-risk customers. Ask: "What one change would make you stay?" Learn: Whether customer is saveable and with what + common requests to prioritize.

Feature Dependency
From all customers periodically. Ask: "Which feature would you miss most if removed?" Learn: What creates lock-in vs what's expendable.

How This Works

The dual approach:

1. Detect risk - Stated intent + behavioral signals flag at-risk customers

2. Route for intervention - High-risk responses alert retention team within 24 hours

3. Capture patterns - Why people consider leaving, what competitors offer, value gaps

4. Fix systemically - Product/experience changes addressing top churn drivers

5. Track effectiveness - Do interventions save customers? Do fixes reduce future risk?

Tactical saves revenue now. Strategic intelligence prevents churn forever.

What Makes This Different

Early detection - Identifies risk during consideration period, not after cancellation
Actionable - Flags individuals for human intervention, not just aggregate analysis
Pattern-focused - Reveals what drives churn across base to prevent it systemically

Measurement

Tactical metrics:

• Detection accuracy - Do "unlikely to continue" customers actually churn without intervention?

• Save rate - % of flagged at-risk customers retained through intervention

Strategic metrics:

• Churn rate reduction - Overall improvement from fixing systemic issues

• Pattern identification - Top churn drivers by segment to prioritize fixes

Customers decide to leave long before they cancel. Early detection enables intervention while they're still yours to save.