Churn Risk Analyzer

Identify customers most likely to churn before they leave. Uses behavioral signals, usage patterns, and engagement data to score accounts and recommend retention actions.

When to Use

• Customer success reviews
• Quarterly retention planning
• When usage data or support ticket logs are available
• Proactive outreach prioritization

How It Works

1. Gather Data

Ask the user for available data sources: - Usage metrics (logins, feature adoption, API calls) - Support tickets (frequency, sentiment, resolution time) - Billing history (downgrades, late payments, discount requests) - Engagement signals (email opens, meeting attendance, NPS scores)

If no structured data, work from what the user describes qualitatively.

2. Score Each Account

Apply this risk framework:

Score: 0-100 (higher = more likely to churn)

3. Categorize

• 🔴 Critical (75-100): Immediate intervention needed
• 🟡 At Risk (50-74): Schedule check-in this week
• 🟢 Healthy (25-49): Monitor monthly
• 💚 Thriving (0-24): Expansion opportunity

4. Recommend Actions

For each at-risk account, suggest specific retention plays: - Executive sponsor call - Custom success plan - Feature training session - Pricing review / loyalty offer - Roadmap preview (show upcoming value)

5. Output

Generate a retention report with: - Ranked list of accounts by churn risk - Top 3 actions per critical account - Estimated revenue at risk - 30/60/90 day retention calendar

Integration Notes

• Works with CSV exports, CRM data, or manual input
• Pair with the AfrexAI Context Packs for industry-specific retention strategies ($47/pack)
• For a full AI-powered retention system built for your business, try the AI Revenue Calculator to see what you're leaving on the table