E- Commerce Cart Abandonment Analysis

Dashboard
Semantic Layer
Concierge

Inspiration

We wanted to solve one of the biggest pain points in e-commerce: customers leaving carts without purchasing. Our goal was to uncover insights that directly translate into recovered revenue.

What it does

The dashboard tracks cart and checkout abandonment, lost revenue, and conversion rates. It highlights where customers drop off and provides guidance for improving checkout flows.

How we built it

We combined transactional data, user behavior logs, and traffic sources into a unified semantic model on Data Cloud. Then, we built an interactive Tableau Next dashboard with funnel views, trends, and device-level analysis. We also Enabled Concierge for users to get quick AI based analysis by just asking questions.

Challenges we ran into

Standardizing data definitions across multiple sources was time-consuming. Another challenge was designing the dashboard to surface deep insights while keeping it simple enough for business users to act on quickly.

Accomplishments that we're proud of

We created a semantic model that ensures consistent, reliable metrics across dashboards. The dashboard empowers both analysts and business users with clear, actionable insights.

What we learned

Small UX issues, like unclear shipping costs, can have a huge impact on abandonment. We also learned how we can use effective semantic layers and AI-driven insights can accelerate decision-making.