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Diwali Sales Analysis

Table of Contents

  1. Project Overview
  2. Objective
  3. Data Source
  4. Dashboard Report
  5. Tools and Technologies Used
  6. Project workflow
  7. Key Findings

Project Overview

This project focuses on analyzing the Diwali Sales Dataset to uncover actionable insights about customer demographics, sales trends, and regional revenue distribution. Using Tableau for interactive data visualization, this project highlights the sales performance across various categories, age groups, occupations, and regions.

Objective

The main goal of this project is to visualize and analyze the Diwali sales data to:

  • Identify high-performing regions and categories.
  • Understand customer behavior based on demographics like age, occupation, and marital status.
  • Provide insights into product performance to optimize sales strategies.

Data Source

The dataset used in this project is available on Kaggle:
Diwali Sales Dataset

Dashboard

Explore the interactive Diwali sales dashboard on Tableau: Diwali Sales Dashboard

Tools and Technologies Used

  • Data Cleaning & Preparation: Python (pandas)
  • Data Visualization: Tableau
  • Dashboard Creation: Tableau Public

Workflow

  1. Data Exploration and Preparation:

    • Monitoring missing and inconsistent data values using Python(pandas).
    • Processed the dataset for compatibility with Tableau.

  2. Dashboard Development:

    • Created interactive dashboards to explore data trends and patterns visually.
    • Focused on aspects like regional sales performance, category-wise analysis, and demographic breakdowns.

Key Findings

  1. Revenue Insights:

    • Total revenue generated during the Diwali season: $106M.
    • Central Region contributed the highest revenue ($41.6M, ~39.15%).

  2. Customer Behavior:

    • High-frequency customers: 3,755.
    • Median order value: $3,824.

  3. Demographic Trends:

    • Age group 26-35 dominates purchases, contributing to a significant share of the revenue.
    • Married individuals account for 42% of total sales, while singles contribute 58%.

  4. Category Analysis:

    • Food category generated the highest revenue ($33.9M, ~31.94%).
    • Other top-performing categories include Clothing & Apparel and Electronics.

  5. Regional Performance:

    • Central and Southern regions collectively contribute more than 60% of total revenue.
    • States like Maharashtra and Karnataka are key drivers of revenue in these regions.

  6. Occupation Trends:

    • IT sector leads in revenue generation, followed by Healthcare and Aviation.

  7. Product Performance:

    • Auto products recorded the highest average order value (~$23.95K).
    • Clothing & Apparel topped in terms of order volume with 6,634 orders.

Acknowledgments

Special thanks to Kaggle for providing the dataset and the open-source tools that made this project possible.