কনটেন্টে যান

Customer Churn Prediction

ML pipeline for predicting and preventing customer churn.

Churn Prediction Flow

flowchart TD
    A[Customer Data] --> B[Feature Engineering]
    B --> C[Model Training]
    C --> D[Prediction]
    D --> E{Churn Risk?}
    E -->|High| F[Alert]
    E -->|Low| G[Monitor]
    F --> H[Retention Action]

    style F fill:#fff3e0
    style H fill:#c8e6c9

Feature Engineering

graph TD
    A[Raw Data] --> B[Usage Features]
    A --> C[Payment Features]
    A --> D[Support Features]

    B --> B1[Login frequency]
    B --> B2[Feature adoption]
    B --> B3[Session duration]

    C --> C1[Payment delays]
    C --> C2[Plan changes]
    C --> C3[Discount usage]

    D --> D1[Ticket count]
    D --> D2[Complaint rate]
    D --> D3[Resolution time]

Model Architecture

flowchart LR
    A[Input Features] --> B[Preprocessing]
    B --> C[Gradient Boosting]
    C --> D[Churn Probability]

    subgraph Training
        C --> E[Cross-validation]
        E --> F[Hyperparameter Tuning]
    end

    style D fill:#c8e6c9

Key Features

Feature Importance Description
Days since last login High Engagement indicator
Support tickets (30d) High Dissatisfaction signal
Payment delay count High Financial stress
Feature usage % Medium Product adoption
Plan downgrade Medium Cost sensitivity
Age of account Low Loyalty indicator

Prediction Output

{
  "customer_id": "CUST-12345",
  "churn_probability": 0.78,
  "risk_level": "HIGH",
  "top_factors": [
    "No login in 14 days",
    "3 support tickets this month",
    "Payment delayed twice"
  ],
  "recommended_action": "Proactive outreach"
}

Training Pipeline

flowchart TD
    A[Data] --> B[Split 80/20]
    B --> C[Train on 80%]
    C --> D[Validate on 20%]
    D --> E{Metrics OK?}
    E -->|Yes| F[Save Model]
    E -->|No| G[Tune Hyperparameters]
    G --> C

    style F fill:#c8e6c9

Evaluation Metrics

Metric Target Critical
AUC-ROC >0.85 <0.75
Precision >0.70 <0.50
Recall >0.75 <0.60
F1 Score >0.72 <0.55

Business Impact

Action Cost Effectiveness
Discount offer $50 40% retention
Personal call $25 60% retention
Service upgrade $100 75% retention

Next Steps