<aside> This comprehensive guide walks you through implementing advanced customer intelligence systems for your DTC brand using Nector's powerful analytics capabilities.

</aside>

1. Setting Up Predictive Churn Modeling

Implementing purchase velocity pattern analysis to predict and prevent customer churn:

graph TD
    A[Purchase Data] --> B[Velocity Analysis]
    B --> C[Risk Scoring]
    C --> D[Intervention Triggers]
    D --> E[Automated Actions]

• Implementation Steps

2. Micro-Segmentation Framework

3. CLV Prediction Algorithm Setup

Key components of the CLV prediction model:

• Historical purchase patterns
• Category affinity scores
• Engagement metrics
• Seasonal factors
• Price sensitivity indicators

graph LR
    A[Data Collection] --> B[Feature Engineering]
    B --> C[Model Training]
    C --> D[Prediction Engine]
    D --> E[Automated Scoring]

4. Real-Time Behavioral Scoring

• Scoring Components

5. Purchase Propensity Modeling

Creating effective cross-sell recommendations:

• Product affinity mapping