📊 Customer Intelligence Platform
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Executive Summary
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RFM Analysis & Segmentation
3D RFM Distribution
Interactive 3D visualization of Recency (days), Frequency (orders), and Monetary (total spend)
RFM Score Distribution
Distribution of calculated RFM scores across customer base
RFM Segment Overview
Customer counts and key metrics by RFM segment
K-Means Clustering Analysis
PCA Projection (2D)
Principal Component Analysis of customer features, colored by cluster
Elbow Method & Silhouette Analysis
Determining optimal number of clusters using WCSS and silhouette scores
Cluster Profiles (Radar Chart)
Feature means for each cluster, normalized for comparison
Clustering Metrics
Customer Lifetime Value & Cohort Analysis
Cohort Retention Heatmap
Month-over-month retention rates by cohort of signup
Revenue by Segment (Box Plots)
CLV distribution across RFM segments
Cohort Revenue Evolution
Total revenue per cohort over time
Churn Prediction Model
Feature Importance
Logistic regression coefficients indicating churn predictors
Confusion Matrix
Model accuracy across classes (threshold: 0.5)
ROC Curve
Receiver Operating Characteristic curve; AUC shows model discrimination ability
Churn Probability Distribution
Histogram of predicted churn probabilities from logistic regression
Customer Journey & Flow
Customer Lifecycle Sankey Diagram
Flow of customers through lifecycle stages: acquisition, engagement, retention, churn
Geographic Revenue Analysis
Revenue by UK Region
Bubble map showing revenue concentration and customer density by region