Understanding Return Rate Calculation in Ecommerce Analytics

Return rate is one of the most important metrics in ecommerce. It impacts profitability, forecasting, customer experience, product development, and operational strategy. Yet many brands are surprised when Shopify and Redo show completely different return rates for the same store.

The orders are the same.
The returns are the same.
The math is different.

Understanding how return rate is calculated is essential if you want to make informed decisions about your returns strategy. This article explains the difference between Shopify’s return rate calculation and Redo’s methodology, why the numbers diverge, and which metric to use depending on the question you are trying to answer.

What Is Return Rate in Ecommerce?

Return rate measures the percentage of orders that are returned by customers. It is typically calculated as:

Number of returns ÷ Number of orders

Return rate is a critical KPI for ecommerce brands because it influences:

• Gross margin and profitability
• Reverse logistics costs
• Inventory planning
• Product quality insights
• Customer experience strategy

However, the definition of “number of returns” and how those returns are assigned to time periods can dramatically change the reported rate.

That is exactly where Shopify and Redo differ.

The Core Difference: Cash Basis vs Accrual Basis Return Reporting

The difference between Shopify and Redo return rates comes down to accounting methodology.

Shopify uses a cash basis method

Redo uses an accrual basis method

Both platforms analyze the same underlying orders and returns. They simply assign those returns to different time periods.

That one decision creates significantly different return rate trends.

How Shopify Calculates Return Rate

Cash Basis Method

Shopify calculates return rate using the following formula:

Returns processed this month ÷ Orders placed this month

Shopify counts a return when it is processed, regardless of when the original order was placed. A December order returned in February is counted against February’s orders.

What Shopify’s Return Rate Is Good For

Shopify’s method is helpful for:

• Tracking refund volume in a specific month
• Understanding cash flow impact
• Accounting and financial reconciliation
• Monitoring month end refund totals

If your goal is to understand how many refunds hit your books in a given month, Shopify’s return reporting is useful.

Where Shopify’s Method Falls Short

Shopify’s return rate is not reliable for measuring whether customer return behavior is actually changing over time.

There are two major issues:

1. Timing distortion caused by return lag
2. Denominator noise from canceled orders and discounts

The timing distortion is the most significant.

The Lag Effect: Why Shopify Return Rates Spike or Drop

There is typically a 20 day delay between when an order is placed and when a return is processed.

When order volume changes, that lag creates a statistical illusion.

Consider this scenario:

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Orders dropped in January from 10,000 to 5,000. However, returns from December orders were still being processed.

Shopify reports January’s return rate as 20 percent. It appears that return behavior doubled.

But customer behavior did not change.

The business did not change.

The math changed.

This is the lag effect. When order volume fluctuates seasonally or during promotional periods, Shopify’s cash basis method can create false spikes or artificial drops in return rate.

If teams react to these signals without understanding the methodology, they risk misdiagnosing product or operational problems that do not exist.

How Redo Calculates Return Rate

Accrual Basis Method

Redo calculates return rate using this formula:

Returns from orders placed this month ÷ Orders placed this month

Returns are matched back to the original order cohort that generated them. A December return is always counted against December orders, even if the customer ships it back in February.

This eliminates timing distortion entirely.

Why Redo’s Accrual Method Matters for Returns Analytics

Using the same example as above, Redo’s methodology produces a completely different result:

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Return rate is consistent at 10 percent across all five months.

Redo surfaces the true signal. Customer return behavior did not change.

By tying returns to the order cohort that generated them, Redo enables brands to measure real return rate trends rather than artifacts of volume timing.

When to Use Shopify vs When to Use Redo

Neither method is universally better. Each answers a different operational question.

Use Shopify Return Rate For:

• Tracking refund cash flow
• Month end reconciliation
• Accounting and financial reporting
• Monitoring refund transactions in a given period

Use Redo Return Rate For:

• Measuring true return rate trends
• Identifying product level return issues
• Evaluating operational improvements
• Comparing cohorts over time
• Understanding whether return behavior is improving or worsening

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The key is knowing which question you are asking before pulling the metric.

Common Mistakes Ecommerce Teams Make

Understanding the difference between cash basis and accrual basis reporting is critical. These are the most common operational mistakes brands make.

Reacting to Shopify Return Rate Spikes

If Shopify shows a sudden increase in return rate, check whether order volume declined in the prior month. The 20 day lag effect often explains the spike.

Escalating product investigations without this context leads to wasted resources.

Using One Return Rate Metric for Every Decision

Shopify and Redo serve different purposes. Using Shopify to evaluate product quality trends introduces systematic error. Using Redo for cash reconciliation creates accounting confusion.

Analyzing Incomplete Cohorts in Redo

Because Redo matches returns to order cohorts, the most recent 30 to 45 days may show artificially low return rates. Returns for those orders are still arriving.

Allow time for cohorts to mature before drawing conclusions.

Why Accurate Return Rate Measurement Matters

Return rate is not just a reporting metric. It drives strategic decisions including:

• Supplier negotiations
• Product development changes
• Size chart updates
• Operational staffing decisions
• Return policy adjustments
• Margin forecasting

If the underlying metric is distorted, the decisions built on top of it will be flawed.

In ecommerce, acting on a false signal can cost hundreds of thousands of dollars in unnecessary product revisions, operational overhauls, or supplier disputes.

Return analytics must reflect real customer behavior, not accounting timing artifacts.

The Takeaway: Right Metric, Right Question

Shopify is not wrong.

Its return rate metric is useful for tracking refund cash flow and financial reporting. It answers an accounting question.

Redo answers a behavioral question.

If you want to understand whether your return rate is truly improving or deteriorating, you need accrual based reporting that ties returns to the orders that generated them.

Using the wrong return rate metric leads to misdiagnosis. Using the right one creates clarity.

For ecommerce brands serious about reducing returns, improving operations, and protecting margin, methodology matters.

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