This repository uses statistical methods and data visualization to analyze customer data from a retail company. It identifies customer segments and provides insights to improve customer retention. Tools include Python, Pandas, NumPy, Matplotlib, Seaborn, and statistical analysis.
From the README
Customer Insights & Retail Analytics Overview This project analyzes customer data from a mid-sized retail company to understand customer behavior, spending patterns, and engagement levels. Using statistical analysis and data visualization, the project identifies key customer segments and provides business recommendations to improve customer retention. Business Objective • Understand customer demographics • Analyze spending behavior • Identify customer segments • Discover factors influencing engagement • Generate data-driven business insights Tools Used • Python • Pandas • NumPy • Matplotlib • Seaborn • Statistics Key Analysis Performed ✔ Customer Demographic Analysis ✔ Spending...
Skills
- Jupyter Notebook
- business-intelligence
- customer-analytics
- customer-segmentation
- data-analysis
- data-visualization
- hypothesis-testing
- python
- retail-analytics
- statistics
