The objective of this project is to analyze customer purchase behavior by applying exploratory data analysis and visualization techniques. The project aims to identify buying patterns, frequent products, seasonal trends, and insights that can support data-driven business decision-making.
Identify and collect a suitable retail or e-commerce dataset from open data sources.
Perform data cleaning by handling missing values, removing duplicates, and correcting inconsistent entries.
Conduct exploratory data analysis using descriptive statistics such as mean, median, frequency, and distribution.
Analyze customer demographics, purchase frequency, product categories, and transaction values.
Apply feature engineering to derive new variables such as customer lifetime value and purchase intervals.
Create meaningful visualizations using bar charts, line graphs, heatmaps, and pie charts.
Identify trends related to time, location, and customer segments.
Interpret visual findings to understand customer preferences and behavior patterns.
Document analytical observations and insights clearly.
Prepare a structured report explaining methodology, tools used, results, and business implications.
Optionally build a simple dashboard using Power BI or Tableau for summary presentation.
