To analyze and compare customer purchase amounts during Walmart's Black Friday sales based on gender, marital status, and age groups. Using statistical methods like confidence intervals and the Central Limit Theorem, the project aims to uncover spending patterns and provide Walmart with actionable recommendations to optimize marketing and sales strategies.
Walmart is a global retail giant operating a vast network of supercenters, discount department stores, and grocery stores. Serving millions of customers worldwide, Walmart continually seeks data-driven insights to enhance customer experience and business decisions.
The dataset includes transaction data of Walmart customers during Black Friday with the following key columns:
| Column Name | Description |
|---|---|
| User_ID | Unique identifier for each customer |
| Product_ID | Unique identifier for each product |
| Gender | Gender of the customer (M/F) |
| Age | Age group (binned) |
| Occupation | Masked occupation category |
| City_Category | City category (A, B, C) |
| StayInCurrentCityYears | Years lived in current city |
| Marital_Status | Married or Unmarried |
| ProductCategory | Masked product category |
| Purchase | Purchase amount in currency units |
Dataset link: Walmart_data.csv
- Data Import and Cleaning
- Exploratory Data Analysis (EDA) with visualizations
- Detect and handle missing values and outliers
- Calculate average purchase amounts by gender, marital status, and age
- Use Central Limit Theorem to build confidence intervals for population means
- Compare confidence intervals to check for significant differences
- Provide business insights and recommendations
- Confidence Interval Calculation
- Central Limit Theorem (CLT)
- Exploratory Data Analysis (EDA)
- Data Visualization (Boxplots, Histograms, Heatmaps)
- Statistical Inference
- Insights into whether women spend more than men on Black Friday
- Confidence intervals showing spending behavior by gender, marital status, and age
- Recommendations on how Walmart can tailor marketing and inventory decisions
- Observations on overlap of confidence intervals and their business implications
| File Type | Description |
|---|---|
| Jupyter Notebook | Walmart_Purchase_Analysis.ipynb - Full code, analysis, and visualizations |
| PDF Report | Walmart_Purchase_Analysis.pdf - PDF export of the notebook with detailed explanations |
| Dataset | Walmart_data.csv - Dataset used for the analysis |
Feel free to reach out for questions and suggestions !
💻Compiled by Samarth