Customer eCommerce Journey

Objective: This project aimed to analyze user behavior and conversion metrics using the Google Analytics 4 (GA4) public dataset. The analysis provides insights into how users progress through key eCommerce stages, highlighting areas for improvement in the customer journey and identifying revenue-driving media channels.

Tools & Techniques Used:

• SQL (Google BigQuery): Data extraction and transformation, applying filters and logic to categorize events and sessions.
• Tableau: Data visualization and dashboard creation with interactive filtering and multi-layered data presentation.
• Funnel Analysis: Visualized user progression from initial session start through purchase stages to understand drop-off points in the sales process.

Key Visualizations and Dashboard Features:

1. Funnel Analysis:
   • The primary visualization is a funnel chart illustrating each step from session start through item view, add to cart, begin checkout, add shipping info, add payment info, to final purchase. This analysis reveals a significant drop-off at the "add to cart" stage, while users who initiate checkout generally complete shipping information. However, the conversion rate drops at the payment stage, indicating potential user friction.
2. Global Revenue and Traffic Map:
   • An interactive world map tracks traffic and revenue sources by country, with the largest contributions from the United States. The map enables exploration of how different mediums impact regional traffic and revenue.
3. New Users by Week & Medium:
   • A line chart shows new users on a weekly basis, segmented by medium, providing insights into which channels are most effective for attracting new users.
4. Revenue Drivers (Pareto Chart):
   • A Pareto analysis of session start conversions identifies the top three media sources driving 73.37% of total conversions. Organic and direct traffic contribute the highest revenue, supporting strategic focus on these channels.
5. Session Counts & Weekly Change:
   • A calendar view and bar chart display session counts by day and week, respectively, with percentage changes to identify growth patterns and trends. Sessions show a post-holiday drop in early January and reduced activity on Mondays and weekends.
6. Peak Hour Traffic:
   • An hourly bar chart displays global session peaks, indicating evenly distributed traffic across time zones, likely due to the international user base.

Interactivity: The dashboard includes filtering options by country, device language, device type, medium, and conversion type, allowing for granular exploration of user behavior across different segments.

Conclusions:

• Global Traffic Patterns: Traffic is evenly distributed across 24 hours, suggesting a global presence spanning multiple time zones.
• Top Traffic & Revenue Sources: The United States dominates in both traffic and revenue across all mediums.
• Funnel Insights: The most substantial drop-off occurs at the "add to cart" stage. However, users who begin the checkout process tend to proceed to shipping information, with drop-offs re-emerging at payment.
• Seasonal & Weekly Variations: Conversion rates dip in early January, likely due to post-holiday fatigue, and tend to be lower on Mondays and weekends.

This dashboard provides a comprehensive view of the customer journey, identifying critical drop-off points and top-performing media channels. It’s a powerful tool for understanding user behavior, optimizing the sales funnel, and informing data-driven marketing strategies.