Overview
When comparing data between Shopify and Polar, you may notice differences in metrics like revenue, orders, refunds, or taxes. While this can feel alarming at first, discrepancies are usually the result of different reporting logic, filters, or settings, not missing or incorrect data.
This article explains:
How Polar processes Shopify data
The most common reasons numbers don’t match
Which Shopify reports to use for accurate comparisons
How Polar Data Settings can impact your results
By the end, you’ll know exactly how to validate your data and confidently explain differences to stakeholders.
Section 1: How Polar Processes Shopify Data
Polar connects to Shopify via the Shopify API and imports raw transactional data, including:
Orders and line items
Discounts and taxes
Refunds (full and partial)
Cancellations
Polar then transforms this data using standardized analytics logic so metrics behave consistently across time, tools, and stores.
Key principles to understand:
Polar is analytics-first, not operational
Shopify dashboards apply implicit assumptions (filters, rounding, inclusions)
Polar metrics are designed for decision-making, forecasting, and reporting
Section 2: Shopify Reports You Should Use for Comparisons
Comparing Polar to the wrong Shopify view is the #1 cause of confusion. Avoid Shopify’s Home dashboard for validation.
Recommended Shopify Reports
Use these reports instead:
Sales → Total Sales by Date
Best for comparing high-level revenue trends
Ensure you select Net Sales if comparing to Polar revenue
Analytics → Reports → Finances Summary
Useful for understanding payouts, refunds, and fees
Often closer to Polar’s net revenue logic
Orders → Export Orders (CSV)
Best for order-level validation
Allows you to compare individual orders with Polar
Section 3: Common Causes of Discrepancies (and How to Check Them)
1. Date Range & Time Zone Differences
Shopify reports default to the store’s local time zone
Polar allows flexible time zone handling and standardized timestamps
2. Gross vs. Net Revenue Definitions
Shopify and Polar may both say “revenue,” but mean different things.
Shopify dashboards often show Gross Sales
Polar typically reports Net Revenue, which may:
Exclude refunds
Account for discounts
Handle cancellations consistently
3. Refund Timing
Refunds are one of the most common sources of mismatch.
Shopify reports may attribute refunds to:
The original order date, or
The refund date, depending on the report
Polar consistently records refunds based on the refund transaction date
This means:
A refund issued today for an order from last month may appear in different periods between tools.
4. Canceled, Voided, and Test Orders
Shopify reports may include or exclude these depending on filters
Polar:
Automatically excludes test orders
Applies consistent logic to canceled or voided orders
📍 Where to check in Polar:
Settings → Data Settings → Order Inclusion Rules
5. Multi-Currency & Exchange Rates
If your store sells in multiple currencies:
Shopify may display presentment currency
Polar standardizes values using consistent exchange rates
This can cause small but expected differences, especially over longer time ranges.
Section 4: Step-by-Step Checklist to Reconcile Numbers
Before escalating a discrepancy, walk through this checklist:
Confirm you’re comparing the same metric definition
Match date range and time zone in both tools
Use a detailed Shopify report, not the homepage dashboard
Review Polar Data Settings (revenue, refunds, orders, currency)
Drill down to order-level data in Polar
📩 If things still don’t line up, contact Polar Support and include:
Metric name
Date range
Shopify report used
Relevant screenshots
Section 5: Compare Custom Reports
If discrepancies still persist after reviewing settings and standard reports, the most reliable next step is to compare Polar and Shopify at the same level of detail using a custom report.
This approach allows you to validate data order by order, making it much easier to pinpoint exactly where a difference originates.
When building Shopify Sales Report in Polar:
Match the same metric used in Shopify
(e.g. Gross Sales, Discounts, Refunds)Use the same date range as your Sales over time Shopify report
Avoid adding extra filters initially
Select a small date range for easier comparison.
Break down the report by dimensions like Order ID and sort by highest values.
If a discrepancy appears, check the original order in Shopify under 'Orders.'
Conclusion
Discrepancies between Shopify and Polar are usually the result of expected differences in reporting logic, not missing data. Once you align report types, filters, and Polar Data Settings, the numbers almost always reconcile.
Key takeaways:
Shopify dashboards are operational; Polar is analytical
Refunds, time zones, and revenue definitions matter
Polar Data Settings directly impact reported metrics
Understanding these nuances will help you trust your data, move faster, and confidently explain numbers to your team.