Summary

You may notice that Shopify’s day-by-day “Total Sales” doesn’t align with Triple Whale’s “Total Sales” for certain orders. That’s because Shopify breaks out each transaction on the actual date it occurs—whether it’s the original sale or a subsequent change—whereas Triple Whale consolidates the entire final order amount under the original “processed date.” While this approach often causes only minor discrepancies over a full month or quarter, on daily or weekly views the numbers can appear mismatched.

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 changes (such as added items or refunds) on the actual day those changes occur.
Triple Whale Consolidates Revenue
Triple Whale records the final state of the order under the original “processed” date—regardless of later edits or refunds—resulting in all changes being folded into that first date.
3rd-Party Refund Handling (e.g. Loop)
When using 3rd-party apps like Loop for exchanges or refunds, the process becomes more complex. The 3rd party app first creates a refund (e.g., -$52 on June 17) and then, if an exchange occurs, generates a new order with a 100% discount (e.g., +$52 on June 21). Triple Whale’s calculation for refunds (Refund Order Adjustment - Refund Line Item) 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 final order total 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.

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:
  - Consolidates the refund information by calculating:
    - 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 exactly when they occur, whereas Triple Whale consolidates them under the original order’s date—leading to apparent discrepancies in daily reports.
Month/Quarter Totals May Align
Over broader timeframes, the net effect of all changes (refunds and edits) in Triple Whale tends to converge with Shopify’s totals, even though individual days may differ.
3rd-Party App Impact
For orders processed through apps like Loop, the 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

Check for Subsequent Changes
If Triple Whale’s revenue for an order seems higher on the original day, review whether there were returns, refunds, or order edits processed later.
Compare Longer Date Ranges
Aggregating data over a month or quarter often minimizes daily discrepancies since all offsets are eventually included.
Understand Your Workflow
Be aware that if your store frequently modifies orders or uses 3rd-party apps (like Loop) for returns/exchanges, Shopify will show each change on its actual date while Triple Whale will consolidate the final order state under the original processed date.
Review Refund Calculations for Loop Transactions
Recognize that 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.

By understanding that Shopify assigns revenue to the actual dates of each transaction while **Triple Whale consolidates revenue under the original processed date—and handles 3rd-party refund events (like those from Loop) with its own calculation logic—you can better reconcile daily discrepancies, even though long-term totals tend to align.