Customer Shopping Behavior Analysis
Budget: ₹1,500 – ₹12,500 INR
Analyzed a dataset of 3,900 customer transactions to identify purchasing patterns, customer segments, and revenue drivers. Performed data cleaning and preprocessing using Python (Pandas), including handling missing values, standardizing columns, and feature engineering such as age groups and purchase frequency. Loaded the processed data into PostgreSQL for advanced querying and analysis.
Conducted exploratory data analysis to uncover key business insights, including revenue distribution by gender, age group, and subscription status. Identified high-value customer segments such as discount power users and loyal customers, and analyzed product performance based on ratings and sales volume.
Generated actionable insights and business recommendations, such as improving subscription conversion, optimizing discount strategies, and targeting high-revenue customer groups to enhance profitability and customer retention.
Conducted exploratory data analysis to uncover key business insights, including revenue distribution by gender, age group, and subscription status. Identified high-value customer segments such as discount power users and loyal customers, and analyzed product performance based on ratings and sales volume.
Generated actionable insights and business recommendations, such as improving subscription conversion, optimizing discount strategies, and targeting high-revenue customer groups to enhance profitability and customer retention.