"GA4 ecommerce events are firing — but I still can't tell where customers are dropping off." This is the most frequent question I hear from EC operators who finished setup but stalled before turning numbers into fixes. Setup is done; reading the numbers as fix-driving signals is not. This article walks through how to visualize drop-offs from view to purchase stage-by-stage in GA4, and how to pick the right action — in a three-layer structure of setup HOW, interpretation WHY, and improvement ACTION. Build the funnel in 5 stages: view → add-to-cart → checkout start → payment info → purchase. Stage-level drop-off makes the leaking step obvious Read numbers in two axes: industry comparison + stage comparison. Compare against industry-typical rates, not absolute values. The biggest stage-to-stage gap is where to focus Match the action to the stage: view→cart is a landing page issue, cart→checkout is shipping/stock, checkout→purchase is form length / payment options. Wrong stage targeting wastes campaign spend EC funnel analysis is a method to visualize the drop-off path to purchase. With GA4's standard e-commerce events, you can observe all five stages with zero additional implementation. The five stages are view_item → add_to_cart → begin_checkout → add_payment_info → purchase. Calculating the pass-through rate at each step decomposes site-wide CVR into stage-level drop-off. If your site CVR is 1.5% with a view→cart rate of 8% and a cart→purchase rate of 18%, the biggest leak is at the very first stage. Looking at CVR alone, you only see "low overall" and your fixes scatter — but splitting by stage tells you exactly where to focus. If your GA4 ecommerce setup is done, building the funnel takes about five minutes in the exploration report. Step 1 — Verify view_item, add_to_cart, begin_checkout, and purchase fire in the GA4 "Realtime" report. Shopify default integration fires automatically; custom themes sometimes miss events. Step 2-3 — Create a new exploration via "Explore" → "+" → "Funnel exploration." Build from a blank canvas. For each step, set "event name = view_item" etc. and choose "continue indirectly" so drop-off across multiple sessions is captured. EC behavior frequently spans sessions, so indirect continuation is the standard choice. Step 4-5 — Add segments for new/returning, device, and channel. The standard period is last 28 days vs. prior 28 days. Use the "Share" button to make the funnel visible to your team for weekly review cadence. Pass-through rates vary widely by industry. Read against industry-typical values, not against absolute thresholds. Apparel typically shows a view→cart rate of 5-8%, which is low but not abnormal — browsing behavior is high. Food EC, by contrast, is 12-18% because visits are driven by immediate need. Before deciding "our 6% view→cart rate means we need to fix the landing page," check the industry-typical value first. A 5-8% range may mean status quo is fine. Significant improvement potential exists only at stages clearly below typical. Once you've identified the abnormal stage, separate actions by stage. Wrong-stage targeting wastes campaign spend, so mapping cause to action sets the priority. view→cart drops point to product page appeal: photo quality, pricing visibility, review count, stock display. Landing-page changes move the numbers quickly here. cart→checkout drops point to shipping, stock-out, or forced signup. Adjusting free-shipping thresholds and adding guest checkout are standard fixes. checkout→purchase drops point to form length and payment options. Trimming form fields and adding Apple Pay / Amazon Pay are usually effective. Once you see "which stage is leaking," the next layer is which channel cohort is leaking at that stage. Compare channel-level (paid search / paid social / organic / direct) funnel pass-through in GA4 segments, identify the inefficient channel, and judge ad spend efficiency with ROAS. Funnel analysis answers "where is revenue leaking?" — it pairs with RPS (revenue per session) and channel-level ROAS to answer "where to invest budget?" What about you? Which stage of the funnel typically leaks most for your store? Do you read drop-off rates against industry typical, or against a target you set internally? Curious to hear how others approach the read.