📊 Ecommerce Funnel Analysis Project

Overview

In this project, I analyzed real world ecommerce user behavior data from Kaggle (https://www.kaggle.com/datasets/mkechinov/ecommerce-behavior-data-from-multi-category-store) to understand the customer journey through a traditional online sales funnel, from product views, to cart additions, to final purchases.
The project simulates a real company analysis pipeline by connecting SQL Server and Power BI without manual exports.

I used SQL views to organize the data transformation and Power BI to build a clean, insightful dashboard ready for presentation.

---

Project Objectives

• Analyze user drop-off at each funnel stage (view → cart → purchase)
• Calculate funnel conversion rates and drop-off percentages
• Segment purchasing patterns by product category and brand
• Visualize key revenue drivers clearly and interactively

---

Tools & Technologies

• Kaggle — sourced the ecommerce behavioral dataset (raw CSV files)

• Excel — used for initial exploratory data inspection and basic cleaning (checked for missing values, corrected datatypes)

• SQL Server Management Studio (SSMS) —

  • Imported the cleaned data into a SQL Server database
  • Wrote complex SQL queries using:
    • SELECT, FROM, WHERE clauses for filtering
    • GROUP BY and ORDER BY for aggregations and sorting
    • COUNT(DISTINCT ...), SUM(...) for metrics like users, revenue, and conversions
    • Common Table Expressions (CTEs) to structure funnel logic and simplify multi-step queries
    • Scalar subqueries for dynamic calculations like conversion/drop-off rates
  • Created SQL views for each major metric (funnel stages, conversion %, category/brand summaries) for seamless Power BI integration

• Power BI Desktop

  • Connected directly to SQL Server using a live connection
  • Imported SQL views without exporting CSVs
  • Built an interactive dashboard showcasing funnel analysis, conversion percentages, brand/category performance
  • Designed slicers, cards, pie charts, funnel charts, bar charts, and cards for dynamic reporting

---

Insights Uncovered

• Only 2.83% of total users completed the full funnel (view → cart → purchase)
• The largest user drop-off occurred between viewing a product and adding to cart
• Electronics represented the most purchased general category (74%+ of purchases)
• Apple and Samsung dominated the total revenue by brand
• Smartphones were the top individual product category purchased

---

📈 Dashboard Preview