Payment Method Analysis

This project focused on three major cities in Myanmar: Yangon, Mandalay, and Naypyitaw.

The goal was to provide insights that help businesses optimize payment strategies and offer targeted promotions across departments and customer segments.

Project Highlights:

Data Cleaning & Preprocessing:

Utilized Python (Pandas, NumPy) to handle missing values, standardize formats, and prepare the dataset for visualization.

Data Visualization:

Built interactive dashboards in Power BI to present trends and comparisons across:

Cities

Customer Types (Member vs. Normal)

Genders

Market Departments (Electronics, Food & Beverages, Fashion, etc.)

Payment Methods (Cash, Wallet, Visa)

Key Findings:

Yangon showed a strong preference for Wallet payments, especially in tech-related departments.

Mandalay customers leaned more toward Cash, likely due to fewer digital infrastructure options.

Naypyitaw displayed a balanced use between Visa and Wallet, driven by younger customer segments.

Gender and customer type also had a noticeable impact on payment choices.

Certain departments showed higher digital payment usage, making them ideal for targeted offers and discounts.

Business Value:

Helped identify preferred payment methods per customer segment.

Suggested how environmental factors and purchase categories affect payment behavior.

Provided a base for designing payment development strategies and targeted marketing campaigns.

Tools Used:

Python for data cleaning and exploration

Power BI for visual storytelling and insights