Ecommerce Conversion Funnel Analysis

📊 Dashboard Preview

📌 Project Description

This project analyzes user behavior in an e-commerce funnel to identify drop-off points and optimize conversion performance.

The goal is to identify where users drop off and how conversion can be improved.

📂 Dataset

The dataset includes user session data with events such as:

• session_start

• view_item

• add_to_cart

• begin_checkout

• add_payment_info

• purchase

• 📈 Key Metrics

• Total Sessions: 354,856

• Purchases: 4,745

• Conversion Rate: 1.34%

• 🔍 Key Insights

• The biggest drop-off occurs between view_item and add_to_cart

• Conversion rate peaks around early December and then declines

• Desktop generates the most sessions, but conversion is similar across devices

• Google is the main traffic source, but not the highest in conversion

• 🛠 Tools Used

• SQL (data analysis)

• Tableau (dashboard & visualization)

• 📁 Project Structure

• sql_analysis.sql — SQL queries

• Dashboard Image — dashboard preview

• 🔗 Live Dashboard

View on Tableau Public