Shopify Checkout Funnel Analysis: Find Where Shoppers Drop Off

Quick answer: Checkout funnel analysis splits your checkout conversion rate into steps — checkout started, contact and information, shipping, payment and purchase completed — and measures the share of shoppers lost between each one. The step with the biggest drop shows what to fix: a shipping-step drop points at delivery cost or speed, a payment-step drop at missing payment methods or trust. Segment by device, market and traffic source so a problem in one segment does not hide in the average.

"Our checkout conversion rate dropped" is a sentence that sends teams into guesswork. Was it shipping costs? A broken payment method? The new field someone added last week? A traffic source that brought in browsers instead of buyers?

You cannot answer that from a single number. Checkout is a sequence of steps, and shoppers leave at specific points for specific reasons. Once you can see which step is leaking, the fix usually becomes obvious.

This guide covers the checkout funnel steps, the metrics worth tracking, what Shopify Analytics gives you out of the box, how to build step-level tracking with customer events, how to diagnose each drop-off, and how to measure the impact of checkout changes.

Why the funnel view matters

An overall conversion rate mixes everything together: traffic quality, product pages, cart, and checkout. A checkout funnel isolates the part where the shopper has already decided to buy. Drop-off there is the most expensive kind, because you have already paid to acquire the visitor and convinced them to start.

It also tells you where to act. A drop at the shipping step points at delivery cost or speed. A drop at payment points at payment options or trust. Without the funnel, you would be guessing between the two.

The checkout funnel steps

On a one-page checkout layout these steps appear on one screen, but the underlying events still fire in sequence, so the funnel is still measurable.

The metrics that matter

• Checkout conversion rate: completed checkouts divided by started checkouts.
• Step drop-off: the share of shoppers who reach a step but not the next one.
• Revenue lost at checkout: the cart value of checkouts that were started but not completed. It is an upper bound, not recoverable revenue, but it shows the size of the problem.
• Average order value (AOV): important when you add upsells or minimums, since conversion and AOV can move in opposite directions.
• Time to complete: how long from checkout started to purchase. A sudden increase can signal a confusing new field or a slow payment method.

Segment each of these by device, market, traffic source and new versus returning customer. A problem that only affects mobile shoppers in one country disappears in the averages.

What Shopify Analytics offers natively

Shopify's built-in analytics include reports on sessions and a conversion funnel that shows how visitors move from sessions to add-to-cart, to reaching checkout, to completed purchase. You can break these down by dimensions such as device type, location and referrer, depending on your plan's reporting features.

That is enough to answer "is checkout the problem?" It is usually not enough to answer "which step inside checkout?" For that you need checkout-level events.

Custom tracking with Web Pixels and customer events

Shopify's customer events system lets you subscribe to standard events through a Web Pixel, either a custom pixel added in your admin or an app pixel. The standard checkout events include:

• checkout_started
• checkout_contact_info_submitted
• checkout_address_info_submitted
• checkout_shipping_info_submitted
• payment_info_submitted
• checkout_completed

Each event carries checkout data such as line items, totals and currency, which you can forward to your analytics tool. A minimal custom pixel looks like this:

const events = [
  'checkout_started',
  'checkout_contact_info_submitted',
  'checkout_address_info_submitted',
  'checkout_shipping_info_submitted',
  'payment_info_submitted',
  'checkout_completed',
];

events.forEach((name) => {
  analytics.subscribe(name, (event) => {
    // Forward to your analytics endpoint or tool
    console.log(name, event.data.checkout.totalPrice.amount);
  });
});

With these events, you can build the funnel in your analytics tool of choice and compute drop-off between each pair of steps.

Privacy and consent

Pixels run within Shopify's customer privacy framework. Depending on the pixel's settings and the shopper's region, events may only be sent after the shopper grants consent. That has two consequences:

• Your funnel numbers will be a consented sample, not every shopper. Compare trends, not absolute totals against Shopify's own reports.
• You must respect consent, especially in the EU and UK. Our guide to EU cookie consent on Shopify covers the setup.

Do not send unnecessary personal data such as full addresses or emails to third-party tools. Aggregate metrics rarely need them.

Diagnosing drop-off at each step

Contact and information

• Is account creation forced? Guest checkout usually converts better.
• Did someone add a required field recently? Every extra field adds friction.
• Are address validation rules rejecting legitimate addresses, for example a PO box restriction that is too broad?

Shipping

• Is the first shipping price shown much higher than the shopper expected?
• Are delivery times missing or vague?
• Are some regions getting no shipping options at all?
• For international shoppers, are unexpected duties a concern? A duties and tax notice can help.

Payment

• Is the shopper's preferred payment method missing in their market?
• Are payment method names clear, and is the most popular one easy to find?
• Is a fraud or payment rule hiding methods from legitimate customers?
• Are card declines high? Check your payment provider's reports.

Completion

• If payment_info_submitted fires but checkout_completed does not, look at declines, 3D Secure challenges and redirects to external payment providers.

Measuring the impact of rules, upsells and fields

Every checkout change, whether a validation rule, an upsell block, a new field or a hidden payment method, should be measured the same way:

1. Record the baseline funnel for at least two comparable weeks.
2. Make one change.
3. Compare the same funnel over an equal period afterwards.
4. Look at the step closest to the change first, then at overall conversion and AOV.
5. Keep, tune or roll back.

For upsells, conversion may dip slightly while AOV rises; judge on revenue per checkout started. For fraud-related rules, also watch chargebacks and refused deliveries, which our fraud KPIs dashboard guide covers.

Pitfalls

• Comparing periods with different promotions, seasons or traffic mixes.
• Reading too much into small sample sizes. A few dozen checkouts can swing wildly.
• Counting duplicate events when shoppers reload pages. Deduplicate by checkout token.
• Forgetting that express checkouts can skip steps, which distorts step-level drop-off.

Doing it with Blockly Checkout Customizer

Blockly Checkout Customizer, launching soon on the Shopify App Store, is designed to pair customizations with measurement: each rule, block or field you create can be reviewed against checkout performance before and after it went live, so you can see whether a change helped or hurt instead of guessing.

Frequently asked questions

What is checkout funnel analysis?

Measuring how many shoppers reach each checkout step and how many leave before the next one, so you can see exactly where checkout loses buyers instead of looking at one conversion number.

What are the steps of the Shopify checkout funnel?

Checkout started, contact and information, shipping, payment, and purchase completed.

Which checkout metrics should I track?

Checkout conversion rate, drop-off per step, revenue lost at checkout, average order value and time to complete, segmented by device, market, traffic source and new versus returning customers.

Why do shoppers drop off at the shipping step?

Usually because of shipping cost, slow delivery or no suitable delivery option.

The takeaway

Treat checkout as a funnel, not a single rate. Use Shopify's native reports to confirm whether checkout is the problem, use checkout customer events to find the exact step, respect consent while you do it, and measure every change against a clean baseline. Most checkout problems are obvious once you can see where shoppers leave.