This project performs an Exploratory Data Analysis (EDA) on Black Friday sales data to uncover key insights into customer purchasing behavior, demographic trends, and product preferences. The findings help businesses make informed decisions on marketing strategies, customer segmentation, and inventory management.
The dataset used for this analysis contains transaction records from Black Friday sales, including:
Customer Information: Age, Gender, City Category, Occupation, Marital Status.
Product Details: Product ID and Product Category.
Purchase Data: Purchase amount spent by customers.
Identify spending trends across different customer demographics.
Analyze purchase behavior based on age, gender, and city categories.
Discover popular product categories and high-revenue customer segments.
Provide business recommendations for targeted marketing and inventory planning.
Purchase Trends: Most transactions fall in the ₹5,000 - ₹15,000 range, with males making higher-value purchases.
Demographic Insights: Young consumers (18-35 years) are the primary spenders, and City B contributes the highest revenue.
Product Preferences: Product categories 1, 5, and 8 are the most popular, with males preferring high-category products.
Occupation & Marital Status: Occupations 4 and 10 show the highest spending, while single customers make larger purchases.
Customer Targeting: Focus marketing campaigns on high-spending age groups (18-35) and City B residents.
Personalized Promotions: Create gender-based and occupation-based offers to increase conversion rates.
Inventory Optimization: Stock more high-demand products (categories 1, 5, and 8) in high-revenue regions.
Pricing Strategies: Implement dynamic pricing based on demand fluctuations to maximize revenue.
Programming Language: Python
Libraries: Pandas, NumPy, Matplotlib, Seaborn
Visualization Tools: Data visualizations using Matplotlib and Seaborn for trend analysis
This analysis provides a data-driven approach to understanding Black Friday sales trends, helping businesses enhance customer engagement, optimize inventory, and increase revenue through strategic planning.**