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Shopping journey · CAR

Cart abandonment rate.
Find where baskets lose momentum.

Cart abandonment rate is the share of carts started that do not become completed orders within a defined observation window.

Start with your numbers.

CAR calculator

Use matching periods and populations. Monetary examples use EUR; enter one consistent currency. Starting values are illustrative.

Cart abandonment rate70%Based on the inputs above
01 / The definition

What is
cart abandonment rate?

Cart abandonment rate is the share of carts started that do not become completed orders within a defined observation window.

Do not divide all orders by add-to-cart event counts. A shopper may add many items to one cart or complete an order on another device.

02 / The measurement

A clear formula.
A useful comparison.

CAR =Abandoned carts ÷ Carts started × 100
01

Collect the matching inputs.

Assign stable cart IDs and connect each to a completed order. Choose an observation window, such as seven days after cart creation, and wait for every cart to mature before reporting.

02

Read the result in context.

Compare device, shipping region and basket value. Baymard provides broad context, but your cart definition and recovery window must remain consistent.

03

Document the comparison.

Keep the reporting dates, population, exclusions and calculation with every result. Show underlying counts as well as the average or rate, so a small sample does not look more conclusive than it is.

Illustrative example

From inputs to insight.

Abandoned carts
700
Carts started
1,000
CAR
70%

70% of carts were abandoned: 700 of 1,000 carts did not convert by the cutoff.

Try your numbers ↑
03 / Industry benchmarks

Context first.
Targets second.

Compare device, shipping region and basket value. Baymard provides broad context, but your cart definition and recovery window must remain consistent.

Use the source’s population and measurement rules to decide whether the comparison applies to your store.

Broad ecommerce context

External context
Source checked September 9, 2026
SegmentReported result
Average across 50 studies70.22%

Source: Baymard cart abandonment research ↗. The source list was updated September 22, 2025. It combines studies from different years and methods; this is not a fresh 2026 cohort or an industry-specific target.

04 / Clerk customer evidence

Real stories.
Clear measurement limits.

We have not verified a published Clerk customer case with a quantified cart abandonment rate result matching this page’s definition.

What would count as useful evidence?

A case reporting abandoned carts and carts started, with the time window and comparison method. General revenue growth or a related engagement metric does not establish this result.

Customer stories describe individual implementations. They are not industry benchmarks, guarantees or standardized causal tests.

05 / Put it into practice

Find where baskets lose momentum.

Show delivery costs and returns terms early. Keep useful add-on suggestions secondary to a clear route to checkout.

Explore the experience

Turn the insight into a useful next step.

See how relevant product discovery can support the shopping journey. Choose an intervention that addresses the issue your data reveals.

Explore product alternatives ↗
Keep the full result in view

Measure the commercial outcome.

Do not divide all orders by add-to-cart event counts. A shopper may add many items to one cart or complete an order on another device.

Explore Recommendations ↗
06 / Common questions

A little more
clarity.

How do I calculate cart abandonment rate?

Abandoned carts ÷ Carts started × 100. 70% of carts were abandoned: 700 of 1,000 carts did not convert by the cutoff.

What should I check before comparing results?

Do not divide all orders by add-to-cart event counts. A shopper may add many items to one cart or complete an order on another device.

What is a good cart abandonment rate?

Compare device, shipping region and basket value. Baymard provides broad context, but your cart definition and recovery window must remain consistent.

Does a higher attributed result prove incremental growth?

No. Attribution connects an interaction with an outcome under a reporting rule. To estimate what a change added, compare randomly assigned treatment and control groups using the same eligible population and a predefined measurement window.

Keep learning

Connect the numbers.

Your next opportunity

Make product discovery
work harder for your store.

Explore how Clerk helps shoppers find relevant products throughout their journey.