📊 Customer Behavior Analytics & Retail Intelligence

🚀 Project Overview

This project simulates a real-world, end-to-end data analytics workflow for a retail business.
The objective is to transform raw customer data into actionable insights that improve customer engagement, increase sales, and optimize business strategies.

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💼 Business Problem

A leading retail company is experiencing changing customer purchasing patterns across:

• Demographics
• Product categories
• Sales channels (Online vs Offline)

How can customer data be leveraged to improve sales, customer satisfaction, and long-term loyalty?

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🎯 Objectives

• Identify high-value customer segments
• Analyze purchasing behavior across channels
• Discover key purchase drivers (discounts, reviews, seasonality)
• Improve customer retention and repeat purchases
• Enable data-driven decision-making

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🛠️ Tech Stack

• Python – Data cleaning, transformation, EDA
• SQL – Data analysis and querying
• Power BI – Dashboard and visualization
• GitHub – Version control and project documentation

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🔄 Project Workflow

🧹 1. Data Preparation & EDA (Python)

• Cleaned missing and inconsistent data
• Handled duplicates and outliers
• Performed exploratory data analysis
• Created features like:
  • Customer Lifetime Value (CLV)
  • Purchase Frequency
  • Average Order Value

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🗄️ 2. Data Analysis (SQL)

• Structured data into relational format
• Wrote SQL queries to:
  • Segment customers
  • Analyze repeat vs one-time buyers
  • Identify top-performing products
  • Track seasonal trends

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📊 3. Visualization (Power BI)

Developed an interactive dashboard including:

• Sales & revenue trends
• Customer segmentation
• Online vs offline performance
• Product category insights
• Discount and seasonal impact

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🧠 4. Insights & Recommendations

• High-value customers drive majority of revenue
• Discounts increase sales but impact profit margins
• Online channels show higher engagement
• Reviews significantly influence purchase decisions

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📈 Business Impact

• Improved marketing targeting
• Enhanced customer retention strategies
• Better inventory and demand planning
• Data-driven business decisions

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📦 Deliverables

• Python scripts (data cleaning & EDA)
• SQL queries (analysis)
• Power BI dashboard
• Final report & presentation

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🌟 Key Highlights

• End-to-end analytics project
• Business-focused insights
• Real-world problem simulation
• Strong combination of Python, SQL, and BI tools

Power BI Dashboard

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👨‍💻 About This Project

This project is designed for:

• Aspiring Data Analysts
• Students learning Python, SQL, and Power BI
• Professionals preparing for analytics interviews

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🔗 Connect With Me

If you're a recruiter or hiring manager, feel free to connect with me on diksharaut2511@gmail.com.

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