Contractual Migration Prepaid to Postpaid

Problem & Business Impact

High-usage, regular prepaid customers represent a migration opportunity to postpaid, a more profitable and loyal segment. Without predictive targeting, operators miss these upselling opportunities.

Measured impact:

• +30% migration rate (vs. generic campaigns)
• +12-18% ARPU post-migration

• 90% retention at D+180 post-migration

• Lifetime Value (LTV) +45% vs. staying prepaid

Data & Key Features

Main data sources

• Recharge history: average monthly amount, frequency, trend
• Voice/data usage: consumption, regularity, overages
• Payment behavior: punctuality, automatic recharges
• Demographics: age, tenure, segment
• Credit scoring: payment capacity assessment (if available)

Engineered features

• Migration propensity score (0-100)
• Average prepaid ARPU 3/6/12 months
• Regularity score (recharge variation coefficient)
• Estimated postpaid ARPU potential
• Post-migration churn risk
• Recommended postpaid plan

Models & Methods

Modeling pipeline

1. Logistic Regression: Binary migration/no-migration classification

   • Accuracy: 81%
   • Key features: regularity, average ARPU, tenure
   • High interpretability for teams

2. Random Forest: Optimal plan prediction

   • Adapted postpaid plan recommendation
   • Accuracy: 76%
   • Voice vs. data usage consideration

3. LTV Model: Post-migration customer value estimation

   • 12/24-month ARPU prediction
   • Retention probability
   • Estimated migration ROI

Migration segmentation

• High-value regulars: ARPU >€30/month, regularity >80%
• Growing users: usage trend +20% over 6 months
• Business potentials: business patterns (IDD, roaming)
• Family groups: multi-SIM, family usage

Real-time Integration

Migration journey

Monthly prepaid base scoring
     ↓
Migration prospect identification (top 15%)
     ↓
Multi-touch orchestration:
├── T0: SMS postpaid discovery offer
├── T+3d: Email recommended plan details
├── T+7d: App notification limited offer
├── T+10d: Call center (if no conversion)
└── T+14d: Retail (advisor appointment)

Process facilitation

• Postpaid plan simulation in app
• One-click migration (if credit scoring OK)
• Guaranteed number portability
• 30-day trial period (prepaid return possible)
• Migration bonus (free data, discount)

KPIs & Performance Targets

| Metric | Target | Current | |--------|--------|---------| | Migration rate | +30% | +32% | | Post-migration ARPU | +12-18% | +15% | | D+180 Retention | >90% | 92% | | Campaign conversion | >12% | 14% | | LTV uplift | +40% | +45% |

Deployment & Monitoring

Migration cycle

1. Monthly scoring: Prepaid base score refresh
2. Prioritization: Top 15% propensity + LTV potential
3. Staggered campaign: Multi-touch over 14 days
4. Conversion: Rate tracking + chosen plan
5. Post-migration: Satisfaction, usage, retention monitoring

Critical post-migration tracking

• D+7: First usage, questions/blockers?
• D+30: Satisfaction, usage vs. prediction?
• D+90: Retention, early churn warning
• D+180: Realized vs. predicted LTV, model adjustment

A/B Testing

• Test group: Personalized offer + optimal timing
• Control group: Generic standard offer
• Metrics: Conversion, ARPU, retention, satisfaction

FAQ & Prerequisites

Q: Is credit scoring necessary? A: Not mandatory but improves accuracy. Alternative: recharge payment history.

Q: Post-migration churn risk? A: <8% with good targeting. 30-day trial period reduces risk.

Q: Impact on immediate revenue? A: Neutral short-term, +15-20% over 12 months via ARPU and retention.

Q: Multi-vendor compatibility? A: Yes, independent of network infrastructure.

Q: Deployment timeline? A: 2-3 months (data pipeline, scoring, CRM/billing integration).