End-to-end Customer 360 project applying SQL Azure, RFM modeling, VBA automation, and Power BI dashboards to analyze customer behavior and segmentation.
SQL Azure • VBA Automation • Power BI Dashboard
Link Power BI: https://drive.google.com/drive/folders/1kMQsT0sWNI8yeDNsUkafuIdG8JQpnjgK
🔍 1. Project Overview
This project implements an end-to-end Customer 360 analytical pipeline using the RFM model (Recency–Frequency–Monetary) to segment customers and uncover behavioral insights.
💡 2. Components of the Pipeline
2.1 SQL Azure (T-SQL)
Data cleaning & preprocessing
RFM metric calculation (Recency, Frequency, Monetary)
2.2 VBA Automation
Auto-assigns RFM segments
Final segmentation refined manually for accuracy
Outputs 5 customer groups: VIP, Loyal, Potential, At Risk, Lost
2.3 Power BI Dashboard
Includes:
Customer overview
RFM segmentation charts
Heatmaps (R×F, R×M, F×M)
Scatter plots exploring RFM relationships
Behavior & revenue insights
2.4 PDF Report
Full methodology
Heatmap interpretations
RFM insights
Marketing strategy recommendations
🧰 3. Tech Stack
SQL Azure (T-SQL) – RFM metric generation & preprocessing
VBA – Automated segmentation logic (little manual adjustment after that)
Power BI – Dashboard visualization
Excel/CSV – Raw data input
PDF – Final analytical report
📁 4. Folder Structure
customer-360-rfm-analysis/
│
├── data/
│ ├── customer_transaction.csv
│ ├── customer_registered.csv
│ └── segmentation_rfm.xlsx # distinct RFM codes + manual segmentation validation
│
├── code/
│ ├── rfm_calculation.sql # SQL Azure script for R/F/M metrics
│ └── rfm_segmentation.bas # VBA script for automated segmentation (pre-adjustment)
│
├── customer360_dashboard.pbix # Power BI Dashboard: https://drive.google.com/drive/folders/1kMQsT0sWNI8yeDNsUkafuIdG8JQpnjgK
├── Customer360_RFM_Report.pdf # Final project report
│
└── README.md
📊 5. Key Features
✔ 1. Data Consolidation
Customer data from registration & transactions is unified into a 360-degree analytical dataset.
✔ 2. RFM Calculation (SQL Azure)
Recency – days since last purchase
Frequency – normalized transaction count
Monetary – normalized GMV
Stored in segmentation_rfm.xlsx to validate distinct RFM codes.
✔ 3. Automated Segmentation (VBA)
VBA assigns customers to 5 groups based on the RFM score:
VIP, Loyal, Potential, At Risk, Lost
✔ 4. Power BI Dashboard
Includes:
Customer overview
RFM heatmaps
Segmentation breakdown
Scatter plots for R–F–M relationships
Revenue & behavior insights
✔ 5. Insights Summary
Potential & At Risk are the largest groups
Loyal customers produce the highest average spending
VIP group is small but high-value
Lost customers show strong win-back potential
Behavioral scatter plots highlight clear value tiers
🎯 Business Recommendations
At Risk: reminder notifications, 7-day comeback offers
Lost: low-cost "Come-back Pack" with curated titles
Potential: soft upsell, 10% off the second weekly purchase
Loyal/VIP: early access, personalized perks, tier-upgrade programs
Reduce wasted marketing budget using segmentation-based targeting
📎 Appendix
All SQL and VBA code is included inside the /code folder.
The segmentation_rfm.xlsx file stores distinct RFM key combinations used to generate segment assignments.
📁 Large Files (stored externally due to GitHub size limits)
Customer360 Power BI Dashboard (.pbix)
🔗 https://drive.google.com/file/d/xxxxx/view?usp=sharing
👤 Author
Nguyen Khanh Nhat
📍 Phu Thuan Ward, Ho Chi Minh City
📞 +84 707 701 783