Fixed & Mobile Plan Optimization

Problem & Business Impact

Customers on unsuitable plans (over or under-sized) generate dissatisfaction and churn. Without predictive analysis, optimization opportunities are missed.

Measured impact:

• +30% plan satisfaction
• -18% churn related to unsuitable plan
• +25% voluntary migration to optimal plan
• +8% ARPU via rightsizing

Data & Key Features

Analysis sources

• Actual usage: voice, SMS, data (mobile), speed (fixed)
• Current plan: inclusions, price, commitment
• Overages: frequency, amount, type
• Under-utilization: % unconsumed
• Patterns: 3/6/12 month evolution

Recommendations

• Downgrade: economy plan if under-utilization >40%
• Upgrade: higher plan if frequent overages
• Alternative plan: better quality/price ratio
• Addons: for specific needs

Models & Methods

1. Usage Pattern Analysis: Clustering

   • Heavy users, moderate, light
   • Voice-centric vs. data-centric
   • Business vs. leisure

2. Plan Recommendation: Optimal matching

   • Cost minimization for usage
   • Satisfaction maximization
   • Constraint consideration (commitment)

KPIs & Performance Targets

| Metric | Target | Current | |--------|--------|---------| | Plan satisfaction | +30% | +32% | | Plan churn | -18% | -20% | | Voluntary migration | +25% | +27% |