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📊 E-commerce Sales Analysis

📕 Table of Contents

❓ Problem Statement

In a competitive market, understanding the factors driving sales performance, profitability, and customer satisfaction is crucial for sustainable growth. Our organization faces challenges in identifying top performing products, optimizing inventory, optimizing sales and promotions strategies necessitating a deeper understanding of user behavior. Additionally, we need to understand the financial impact of discounts to enhance our profit margins.

🎯 Objective

Analyze sales and promotions data to identify key trends and insights, segmenting analysis by Overview, Product, Day/Time, Brand, and State for targeted insights. Aims include identifying best-selling brands, assessing financial health, understanding various factors' impact on sales, and providing actionable recommendations.

🛠️ Tools Used

  • Analytical & Visual: Microsoft Power BI
    power-bi-2021
  • Presentation: Microsoft Power Point
    microsoft-powerpoint-2019

📅 Dataset Overview

  • Data source: Internet
  • Time period: 2019
  • Data size:
    • Sales_Data_Ecommerce (160001,18)
    • Promotion (62,4)
  • Key columns: Day_of_week, channel, event_hour, event_type, category, sub_category1, sub_category2, brand, price, user_session, State, User_Score
  • Calculated/Dax columns: Active title, Average discount, Average user score, Purchase ratio, Set benchmark, Top brand by customer, Top reviewed brand, top sold category, etc.
  • Data Model

🔎 Key Findings

  • Total sales: $5.37M
  • Purchase ratio: 9.11%
  • Best-selling brand: Apple
  • Average rating: 2.51 (significantly low)
  • 78% of customers only visit without purchasing
  • Most sales occur between 5am-2pm
  • Mississippi leads in state-wise sales
  • Electronics lead in sales and discounts

💡 Recommendations

  1. Implement strategies to improve conversion rates
  2. Optimize for peak sales hours (5am-2pm)
  3. Develop special Friday promotions and Sunday deals
  4. Create state-specific strategies
  5. Focus on promoting electronics and improving other categories
  6. Strengthen partnership with Apple and convert Samsung browsers
  7. Improve overall customer satisfaction
  8. Enhance mobile app experience
  9. Review and optimize discount strategy

📌 Project Presentation

Video Presentation

E-commerce Sales Analysis 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. Sorting option.
  9. Parameter. Dynamically select how many data points to show.
  10. Tooltip.
  11. Data storytelling.
  12. Sharpened analytical and problem-solving abilities.
  13. Actionable Insights Generation.
  14. Strengthened strategic planning and presentation skill.
  15. Enhanced communication skills.

💻 Installation and Usage

  • Microsoft Power BI Desktop

📈 Dashboard