Comprehensive analysis of customer purchase behavior, with a specific focus on purchase amounts, in relation to customer gender during the Black Friday sales event at Walmart Inc. This study aims to provide valuable insights that can assist the management team at Walmart Inc. in making data-driven decisions.
The company collected the transactional data of customers who purchased products from the Walmart Stores during Black Friday. The dataset has the following features:
| Feature | Description |
|---|---|
| User_ID | User ID |
| Product_ID | Product ID |
| Gender | Sex of User |
| Age | Age in bins |
| Occupation | Occupation (Masked) |
| City_Category | Category of the City (A, B, C) |
| StayInCurrentCityYears | Number of years stay in current city |
| Marital_Status | Marital Status |
| ProductCategory | Product Category (Masked) |
| Purchase | Purchase Amount |
- Data Collection - Source and format of the dataset.
- Data Cleaning & Preprocessing - Handling missing values, feature engineering.
- Exploratory Data Analysis (EDA) - Visualizations and insights.
- Compared customer spending patterns across gender, marital status, and age groups.
- Applied Central Limit Theorem & Confidence Intervals to validate results.
- Insights/ Recommendations
- Segment Smarter with Multivariable Insights: Use Age × Gender × Marital Status combinations, not single variables, for effective targeting. E.g., Unmarried Males 51–55 are top spenders → prioritize with premium lifestyle bundles Married Females 26–35 lean into concentrated category interest → design value-centric curated kits.
- Optimize Product Category Promotions Category 1 is the MVP across all demographics → make it the anchor for bundles or cross-sells Category 7 (females) and Category 1 (males) are gender hotspots → highlight these in gendered campaigns Unmarried buyers explore more → recommend new or trending items in Categories 5, 7, 8 Older users (46+) prefer Category 10 → position it as a legacy, wellness, or home utility line
- Tailor Offers to Age-Based Behavioral Trends Ages 51–55 spend the most → offer premium upgrades, loyalty perks, and early access sales 18–25 are digital natives but moderate spenders → boost cart size via flash deals, gamified incentives 0–17 and 55+ show low volume → target with gifting ideas, essentials, and assistive UI experiences
- Let Data Shape Inventory and Merchandising City C shows narrow product variety → reassess offerings, local preferences, or distribution gaps Categories 13–20 are niche → either rebrand, bundle, or rotate them out for better movers Boost stock and visibility of Category 1 and 7 in urban centers (City A & B)
- Precision Marketing & Communication Build micro-segmented email campaigns: "For Her: Trending in Category 7" "Upgrade Your Game: Offers for Males 51–55" "Bundles for New Households: Age 26–35 Married" For lower-engagement groups, run awareness and discovery campaigns—inform, inspire, and onboard them toward higher involvement.