Funnel Drop-Off Analysis for E-commerce by Chaya ChaipitakpornFunnel Drop-Off Analysis for E-commerce by Chaya Chaipitakporn

🔎 Funnel Drop-Off Analysis (GA4 + BigQuery)

Understand where users drop off—and how long they hesitate—across your customer journey.

🧩 Project Summary

A funnel analysis using GA4 and BigQuery to uncover conversion bottlenecks and time delays across devices. Delivered segmented insights to prioritize UX and CRO improvements.

📌 Business Problem

The client wanted to identify why users were not completing purchases, despite high product views and cart activity. Existing GA4 dashboards showed totals but didn’t break down drop-offs or time delays at each funnel stage.

⚙️ My Approach

Queried GA4’s raw event logs in BigQuery to reconstruct the user funnel: view_item → add_to_cart → begin_checkout → purchase

Calculated drop-off rates and average time-to-convert between each step

Segmented the funnel by device type (desktop, mobile, tablet) for better UX targeting

Filtered out extreme outliers to focus on realistic, same-session user journeys

Delivered a clean summary with business insights and action recommendations

📊 Key Results: Funnel Conversion Rates

📌 Insights

Add-to-cart is the major drop-off point across all devices—only ~20% of users progress past product viewing.

Once users enter the checkout flow, conversion rates are strong, especially on mobile and tablet (over 50%).

Mobile leads in final purchase rate, indicating a relatively optimized experience.

Tablet users, while fewer in number, show the highest funnel completion rates, suggesting more deliberate or motivated shoppers.

⏱️ Key Results: Time to Convert (Average per Step)

📌 Insights

Users typically add to cart within 4–5 minutes of viewing an item, indicating fast decision-making.

Cart to checkout time averages around 13 minutes, suggesting minor hesitation or distraction, ideal for nudge campaigns or UX improvements.

Checkout to purchase average under 7 minutes, which is a healthy signal of payment process efficiency.

Tablet users complete the funnel faster overall, supporting the idea of more focused browsing behavior.

🔍 Summary Business Insights

Biggest Drop-Off: The most critical point is the transition from product view to add-to-cart; this is the key optimization target.

Conversion Strength: Once users are in checkout, more than half complete the purchase, indicating the checkout process itself is effective.

Fast Flow: Most conversions occur within a short time window, ideal for same-session marketing and real-time personalization.

Mobile & Tablet Strengths: Mobile has high volume and solid conversion, while tablet users convert at the highest rate—both should be prioritized in UX strategy.

✅ Strategic Recommendations

Improve product detail clarity and CTA placement to increase the Add-to-Cart rate

Consider triggering cart nudges or discount timers around the 10–15 minute mark

Run mobile A/B tests to fine-tune the high-performing funnel

Retarget high-intent users who stall between cart and checkout

Segment campaign audiences by device behavior to align with funnel tendencies

🛠️ Tools & Techniques

BigQuery • GA4 • SQL (Window Functions) • Funnel Analysis • Device Segmentation • Conversion Timing Metrics