📊 E-commerce Sales Analysis

📕Table of Contents

• Problem Statement
• Objective
• Tools Used
• Dataset Overview
• Key Findings
• Recommendations
• Project Presentation
• Project Learnings
• Installation and Usage
• Dashboard

❓ Problem Statement

While the e-commerce platform shows strong revenue growth and a positive average customer rating, there are disparities in performance across product categories, regions, and order statuses. The high average order value of cancelled orders suggests potential issues with order fulfillment or customer expectations. Additionally, the imbalance between the number of sellers and customers indicates a need for marketplace expansion and diversification.

🎯 Objective

The primary objective is to capitalize on the platform's revenue growth while addressing key areas for improvement. This includes optimizing product category performance, enhancing order fulfillment processes, expanding the seller base, and leveraging regional insights to drive growth. The goal is to increase overall revenue, reduce cancellations, improve seller-to-customer ratio, and maintain high customer satisfaction across all regions and product categories.

🛠️ Tools Used

• Analytical & Visual: Microsoft Power BI
  
• Presentation: Microsoft Power Point
  

📅 Dataset Overview

• Data source: Internet
• Time period: 2016-2018
• Data size: CUSTOMERS(99442,5),GEO_LOCATION(99952,5),ORDER_ITEMS(112651,7),ORDER_PAYMENTS(103887,5),ORDER_REVIEW_RATINGS(100001,5),ORDERS(99442,8),PRODUCTS(32952,9),SELLERS(3096,4)
• Key metrics: Total revenue, Freight cost, Average customer rating, Average order value, Number of sellers and customers
• Dataset Link
• Data Model

🔎 Key Findings

• Total revenue: $13.59M
• Freight cost: $2.25M
• Average customer rating: 4.07
• Average order value: $136.48
• Seller to customer ratio: 3,095 sellers to 58,798 customers
• Top performing categories: Health & Beauty, Watches
• Dominant payment method: Credit card
• Yearly revenue increase trend
• Highest revenue: Delivered products
• Highest average order value: Cancelled orders
• Top performing regions: Rajasthan (highest average order), Andhra Pradesh (highest revenue)

💡 Recommendations

1. Focus on promoting and expanding the Health & Beauty and Watches categories
2. Diversify payment methods
3. Improve order fulfillment to reduce cancellations
4. Replicate Rajasthan's high average order value strategies in other regions
5. Adapt Andhra Pradesh's revenue-generating strategies for other states
6. Reduce freight costs and increase customer ratings
7. Implement seasonal and yearly planning strategies
8. Develop tactics to increase overall Average Order Value (AOV)

📌 Project Presentation

Slides

The detailed presentation slides for this project can be found here

🧠 Project Learnings

1. Data Loading and Transformations.
2. Power Query and DAX.
3. Data modeling.
4. Conditional and calculated column.
5. KPI Development.
6. Data visualization.
7. Dynamically switch metrics and title in visuals.
8. Data storytelling.
9. Sharpened analytical and problem-solving abilities.
10. Strengthened strategic planning and presentation skill.
11. Enhanced communication skills.

💻 Installation and Usage

• Microsoft Power BI Desktop

📈 Dashboard

• Live Dasboard