Quantium Retail Analytics Project

🎯 Problem Statement

Analyze retail transaction and customer purchasing behavior data to uncover business insights, identify sales trends, and evaluate store performance for better retail decision-making.

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📌 Project Overview

This project focuses on retail analytics using transaction and customer data provided by Quantium.

The analysis includes:

• Customer purchasing behavior
• Brand performance
• Pack size analysis
• Monthly sales trends
• Store performance evaluation
• Correlation analysis

The project aims to generate actionable business insights through data cleaning, exploratory data analysis, and visualization techniques.

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🛠️ Tools & Technologies

• Python
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Jupyter Notebook
• Excel

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📊 Analysis Performed

✅ Data Cleaning

• Checked missing values
• Removed duplicate records
• Converted date columns
• Merged transaction and customer datasets

✅ Feature Engineering

• Created Total Sales column
• Extracted product brands
• Extracted pack sizes

✅ Exploratory Data Analysis

• Customer segment analysis
• Top brand analysis
• Monthly sales trends
• Store performance analysis
• Correlation heatmap

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📈 Key Insights

• Young singles and couples contribute significantly to sales revenue.
• Premium chip brands generate strong customer engagement.
• Medium and large pack sizes dominate customer purchases.
• Some stores consistently outperform others in sales.
• Sales trends indicate seasonal demand variations.

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💡 Business Recommendations

• Increase inventory for high-performing pack sizes.
• Target premium product campaigns toward young professionals.
• Replicate successful strategies from top-performing stores.
• Optimize inventory planning based on monthly demand trends.

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🖼️ Visualizations

Top Brands by Sales

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Customer Segment Sales

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Monthly Sales Trend

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Correlation Heatmap

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Top Stores

📂 Project Structure

Quantium-Retail-Analytics/
│
├── data/
├── notebooks/
├── images/
├── README.md
├── requirements.txt

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⚙️ How to Run

1️⃣ Clone Repository

git clone https://github.com/harshithaadicherla10/quantium-retail-analytics.git

2️⃣ Install Dependencies

pip install pandas numpy matplotlib seaborn

3️⃣ Open Jupyter Notebook

jupyter notebook

4️⃣ Run Notebook

Open:

notebooks/quantium_analysis.ipynb

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🚀 Project Highlights

• Retail customer analytics
• Business-focused insights
• Data visualization
• Exploratory data analysis
• Store performance evaluation
• Correlation analysis