Business Intelligence

Predict customer churn risk for energy suppliers

Predict and prevent customer churn with ML-powered risk scoring. Churn scoring system (0-100 points):

Scoring Components:

  • Contract status (30 points): <3 months to contract end = CRITICAL (30 points)
  • Price sensitivity (25 points): Price complaints, >10% above market, recent price increase, competitor comparison
  • Service quality (20 points): >5 support contacts, unresolved tickets, NPS Detractor (<6), negative feedback
  • Payment behavior (15 points): >2 late payments, payment method changes, manual vs. automatic payment
  • Usage pattern (10 points): Consumption declining >20%, no app usage (3+ months), no login activity

Customer Segments & Business Value:

  • Residential: ARPU 600€, LTV 3k€, churn 10-12%, retention budget max 600€
  • Prosumer: ARPU 1,450€, LTV 10k€, churn 5-8%, budget 2,000€ (HIGH PRIORITY! Must protect)
  • Commercial: ARPU 10k€, LTV 50k€, churn 3-5%, budget unlimited (MUST WIN! Strategic accounts)
  • Premium: ARPU >5k€, LTV >25k€, churn <3%, no budget limit (VIP treatment required)

Retention Strategies by Risk Level:

  • HIGH RISK (80-100): Immediate personal call + retention offer (max 200€ for residential, 2k€ for prosumer)
  • MEDIUM RISK (60-80): Automated email campaign + targeted incentive (max 100€ for residential)
  • LOW RISK (40-60): Proactive engagement (loyalty program, app activation, community features)

Use Cases:

  • Retention campaigns: Target high-risk customers before contract ends
  • Customer lifetime value protection: Focus on prosumer and commercial segments
  • Segmented marketing: Different strategies for different risk/value segments
  • Service quality improvement: Identify systemic issues causing churn
  • Budget optimization: Allocate retention budget to highest ROI segments

ROI Metrics:

  • Typical retention cost: 150-2,000€ depending on segment
  • Expected retention success rate: 40-60% with proactive intervention
  • Prosumer segment ROI: 19.3x (1,500€ cost saves 29k€ revenue)
  • Commercial segment ROI: 33x+ (unlimited ROI for strategic accounts)

Critical Success Factors:

  • Act early: 3-6 months before contract end (not 1 month!)
  • Segment ruthlessly: Prosumer/Commercial = high touch, Residential = automated
  • Personalize approach: Different reason = different retention strategy
  • Measure religiously: Track retention rate by segment, reason, intervention type
post/api/business-intelligence/churn-prediction

Request

  • Base URL: https://api.cernion.de
  • URL: https://api.cernion.de/api/business-intelligence/churn-prediction
  • Auth: none declared

Query parameters

tokenstring

Optional Cernion MCP token as URL query parameter. If provided, it overrides CERNION_TOKEN for this request. Prefer Authorization Bearer header in production to reduce token exposure in URLs/logs.

Request body

customerSegment'residential' | 'prosumer' | 'commercial' | 'premium' | 'all' required

Customer segment to analyze

regionstring required

Region/postal code

riskThreshold'high' | 'medium' | 'low'

Minimum risk level to include

limitnumber
predictionWindowMonthsnumber

Prediction timeframe in months

includeRetentionStrategyboolean
includeValueSegmentationboolean
includeChurnReasonsboolean
includeCompetitiveAnalysisboolean
tokenstring

Optional Cernion MCP token for this request. Overrides CERNION_TOKEN when provided.

Example request

{
  "customerSegment": "prosumer",
  "region": "Bayern"
}

Response

Successful response

object required

Changes

No recorded changes to this operation across all 2 revisions of this API.