This project focuses on analyzing customer lifetime value using various data visualization techniques. By leveraging Python libraries such as Pandas, Seaborn, Plotly, and Matplotlib, the analysis provides insights into customer acquisition costs, revenue generation, conversion rates, and return on investment across different marketing channels.

Ten Retail Data Analytics Projects, Heavy Focus on ML. Emphasis on consumer behavior.