Summary

You may notice that Shopify's day-by-day sales metrics do not align with Triple Whale's order-based sales metrics for certain orders. This can affect Gross Sales, Order Revenue, Total Sales, and calculated metrics that use those values.

This often happens when an order is edited after the original purchase. Shopify can show the original sale on one date and the later order edit on another date. Triple Whale stores the updated order values on the original order date, based on when the order was processed. While this approach often causes only minor discrepancies over a full month or quarter, on daily or weekly views the numbers can appear mismatched.

The affected metric depends on what changed. If an edit changes products, quantities, or prices, Gross Sales can change. If an edit changes shipping, taxes, or discounts, metrics such as Order Revenue, Total Sales, Net Sales, or other revenue-based calculations can also change.

Refund timing depends on the data source. In the Orders table, order-level refund values are tied to the original order date. In the Refunds table, refund values are tied to the refund processed date.

Why This Happens

Shopify Shows Multi-Day Transactions
When a customer adds or edits an order after the initial purchase, Shopify records the original sale on one day and the subsequent change on the actual day it occurs. This can include added items, removed items, shipping changes, tax changes, discounts, refunds, or exchanges.
Triple Whale Consolidates Order Values
Triple Whale records the current order values under the original processed date. If an order is edited later, the updated order amount is reflected on the original order date instead of being split out as separate revenue on the edit date.
Refund Timing Depends on the Source
In the Orders table, order-level refund values are keyed to the original order date. In the Refunds table, refund values are keyed to the refund processed date. Metrics or reports that use those sources can therefore place refund impact on different dates.
Third-Party Refund Handling (e.g. Loop)
When using third-party apps like Loop for exchanges or refunds, the process becomes more complex. The third-party app may first create a refund (e.g., -$52 on June 17) and then, if an exchange occurs, generate a new order with a 100% discount (e.g., +$52 on June 21). Triple Whale's refund calculation can result in a net refund of $0, obscuring the fact that there was significant transaction activity on those individual dates.

Example Scenario

Order Edit Example

January 1 - A $100 item is purchased. Both Shopify and Triple Whale list $100 for that day.
January 2 - The customer adds a new item for $50 to the same order.
- Shopify: Records $100 on January 1 and an additional $50 on January 2.
- Triple Whale: Shows the updated order value of $150 on January 1 and does not display any separate revenue for January 2.

Result:

On January 1, Triple Whale shows $150 for that order, while Shopify shows $100.
On January 2, Shopify displays $50 of additional revenue, but Triple Whale shows $0 for that day.

If the added item changes the product sales amount, this same order edit can affect Gross Sales. If the edit changes shipping, taxes, or discounts, it can also affect Order Revenue, Total Sales, and calculated metrics that use those values.

Loop Refund/Exchange Example

June 15 - A customer places an order for a product for $52.
June 17 - The customer initiates an exchange. Loop processes a refund of -$52 for the order.
June 21 - The exchange is completed. Loop creates a new sale with a 100% discount that appears as +$52.
- Shopify:
  - Shows the original order of $52 on June 15.
  - Records a refund of -$52 on June 17.
  - Displays a replacement sale of +$52 on June 21.
- Triple Whale:
  - Calculates the refund information by comparing:
    - refund.order_adjustment.amount + refund.order_adjustment.tax_amount = $52, and
    - refund.refund_line_item.subtotal + refund.refund_line_item.total_tax = $52.
  - It then subtracts these values (i.e., $52 - $52), resulting in a net refund of $0 for that specific order.

Result:

Shopify’s Sales Over Time Report shows:
- June 15: $52 (original order)
- June 17: -$52 (refund)
- June 21: +$52 (replacement sale)
Triple Whale shows:
- June 15: $52 (original order)
- June 17: $0 (refund, updated from -$52 to $0 once the replacement sale is processed on June 21)

How This Affects Reporting

Daily or Weekly Mismatches
Shopify's granular, day-by-day breakdown shows changes when they occur, whereas Triple Whale reflects updated order values under the original order date. This can create apparent discrepancies in daily or weekly reports.
Refund-related values depend on the source
If a report uses order-level refund values from the Orders table, the refund impact is tied to the original order date. If it uses refund-detail values from the Refunds table, the refund impact is tied to the refund processed date.
Month/Quarter Totals May Align
Over broader timeframes, the net effect of all changes in Triple Whale tends to converge with Shopify's totals, even though individual days may differ. Exact alignment still depends on the metric, the adjustment type, and the data source being compared.
The issue is not limited to Total Sales
Order edits can affect order-based metrics that use the edited order values. Gross Sales can be affected when products, quantities, or prices change. Order Revenue, Total Sales, Net Sales, AOV, ROAS, MER, profit metrics, and other calculated metrics can be affected when they use the changed order-based sales values.
Order Count Is Usually Not Affected in the Same Way
The order edit itself typically does not create another original order. That means order count is usually not affected in the same way, although some third-party exchange workflows may create separate replacement order records.
Third-Party App Impact
For orders processed through apps like Loop, separate refund and exchange events may cancel out in Triple Whale's calculations (resulting in a net $0 change), even though the daily activity in Shopify is clearly visible.

How to Interpret the Data Correctly

Confirm which metric you are comparing
Gross Sales, Order Revenue, and Total Sales are different metrics. Gross Sales is before shipping, taxes, discounts, and refunds. Order Revenue includes shipping and taxes and subtracts discounts, before refunds. Total Sales also accounts for refunds.
Confirm which data source the metric uses
For refund-related checks, confirm whether the metric or report uses order-level refund values from the Orders table or refund-detail values from the Refunds table.
Check for Subsequent Changes
If Triple Whale's revenue for an order seems higher on the original day, review whether there were returns, refunds, exchanges, or order edits processed later.
Compare Longer Date Ranges
Aggregating data over a month or quarter often minimizes daily discrepancies because the original order date and later edit, refund, or exchange date are more likely to be included in the same comparison window.
Understand Your Workflow
If your store frequently modifies orders or uses third-party apps like Loop for returns and exchanges, Shopify may show each change on its actual date while Triple Whale may report the order-level impact on the original processed date.
Review Refund Calculations for Loop Transactions
With Loop, even if refunds and exchanges occur on different days, Triple Whale's refund calculation may result in a net $0 for that order, so daily reporting might not reflect the activity even though the overall sales are accurate.

If the order was not edited, refunded, exchanged, or adjusted, then the mismatch may have a different cause and should be investigated separately.