Funnel & Conversion Analysis

E-Commerce Funnel Diagnostics

Aarya Bhivsanee analysed 1,761,675 e-commerce sessions in PostgreSQL to find where the purchase funnel leaks. 97.8% of viewing sessions never reach cart, while 72.8% cart abandonment sits near the roughly 70% industry average, which pointed to the product page rather than checkout.

Overview

The instinct going in was that checkout would be the leak — it usually is. Working from the RetailRocket eCommerce events dataset (views, add-to-cart, transactions), I built a session-level clickstream mart in PostgreSQL from scratch: sessionization, timestamp cleaning, and stage-by-stage conversion tracking across the full funnel.

Approach

The data told a different story. 97.8% of viewing sessions never reached cart, while 72.8% cart abandonment sat near the roughly 70% industry average. Aggregate, top-line metrics would have hidden this entirely; only session-level tracking surfaced exactly where the funnel actually breaks.

Results

• Located the real leak: 97.8% of viewing sessions never reach cart, while 72.8% cart abandonment sits near the roughly 70% industry average, so the fix is the product page and add-to-cart step, not a checkout redesign.
• Found returning visitors converting at about 3x new visitors from 3 to 9 pm and several high-traffic categories below average, shaping 3 proposed A/B tests (product page, category UX, cart recovery).
• Built a PostgreSQL session mart (1,761,675 sessions; 30-minute sessionization, window functions) feeding 4 Tableau dashboards on funnel health, segmentation, category performance and time to convert, because aggregate metrics alone would have hidden the leak.

That reframed the fix: not a checkout redesign, but product-page clarity. I also found returning visitors converting at about 3x the rate of new visitors from 3 to 9 pm, pointing at the first-visit experience as much as the funnel itself. The output was 3 proposed A/B tests (PDP clarity, category UX, cart recovery) and 4 Tableau dashboards, packaged into a stakeholder memo — not just a chart, a specific, arguable recommendation.

Tools

• PostgreSQL
• Tableau
• Sessionization
• Window functions
• A/B test design