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Customer-behaviour

📊 Exploratory Data analysis on customer behaviour:

This repository focuses on exploratory data analysis (EDA) to understand customer behavior trends over the given year by examining patterns in purchasing, engagement, and usage data. The analysis aims to uncover meaningful insights about how customers interact with the business over time and how their behavior changes across different periods.

💡Tools & technologies used:

  1. Python IDE: Visual Studio Code, Libraries: Numpy, Seaborn, Pandas, Matplotlib
  2. Sql IDE: PostgreSql
  3. Visualising IDE: Power BI

🎯Key objectives:

To analyze customer behavior in a structured, data-driven way to identify trends, and potential areas for improvement that can support better decision-making.

🌟Conclusion:

This project demonstrates how combining statistical analysis, visualization and business intelligence tools can transform raw customer data into actionable insights.

About

Analyzed transactional and engagement data to understand customer purchasing patterns and revenue contribution. Performed segmentation, trend analysis, and repeat purchase evaluation using Python and Excel. Delivered actionable insights and built visual dashboards to support data-driven decision-making.

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