https://github.com/barkintopcu/powerbi_customer_analytics_with_cpa_data

An interactive Power BI dashboard that explores customer demographics, spending habits, and campaign responses. Built to uncover patterns, segment customers, and support smarter marketing decisions.
https://github.com/barkintopcu/powerbi_customer_analytics_with_cpa_data

dax powerbi sql

Last synced: 5 months ago
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An interactive Power BI dashboard that explores customer demographics, spending habits, and campaign responses. Built to uncover patterns, segment customers, and support smarter marketing decisions.

• Host: GitHub
• URL: https://github.com/barkintopcu/powerbi_customer_analytics_with_cpa_data
• Owner: BarkinTopcu
• Created: 2025-08-13T12:16:18.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2025-08-17T14:38:20.000Z (11 months ago)
• Last Synced: 2025-09-07T02:51:14.535Z (10 months ago)
• Topics: dax, powerbi, sql
• Homepage:
• Size: 313 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# 📊 Power BI – Customer Analytics Dashboard

This project is a **Power BI dashboard** designed to analyze customer data and provide valuable business insights.  

The dataset contains customer demographics, spending habits, campaign responses, and channel usage patterns.

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## Current Dashboard

![Description](Images/Dashboard_v1.png)

---

## 🎯 Objective

- Understand the overall customer profile

- Identify purchasing behavior and preferred product categories

- Analyze marketing campaign acceptance rates

- Compare performance of different purchasing channels

- Segment customers based on RFM (Recency, Frequency, Monetary) analysis

---

## 📂 Dataset

**Source:** [Customer Personality Analysis – Kaggle](https://www.kaggle.com/datasets/imakash3011/customer-personality-analysis)  

This dataset contains demographic, product preference, campaign response, and channel usage data for a set of customers.

| Category   | Fields |

|------------|--------|

| **People** | ID, Year_Birth, Education, Marital_Status, Income, Kidhome, Teenhome, Dt_Customer, Recency, Complain |

| **Products** | MntWines, MntFruits, MntMeatProducts, MntFishProducts, MntSweetProducts, MntGoldProds |

| **Promotion** | NumDealsPurchases, AcceptedCmp1–5, Response |

| **Place** | NumWebPurchases, NumCatalogPurchases, NumStorePurchases, NumWebVisitsMonth |

---

## ✅ Completed

- **Demographic Analysis** – Education level, marital status, age distribution  

- **Spending Analysis** – Total spend per product category  

- **Campaign Analysis** – Participation and acceptance rates

- **Customer Status** - Active/Inactive/Risk

## 📌 Planned Features

- **Channel Performance** – Web, catalog, and in-store purchases comparison

- **RFM Segmentation** – Customer classification based on Recency, Frequency, Monetary values

---

## 🛠 Tools & Technologies

- **Power BI Desktop**

- **Power Query**

- **DAX** – Measures, calculations, columns

- **MySQL** – Data source (localhost)