Overview
This article explains common reasons why the totals displayed in Custom Reports might not match the sum of rows or the totals in exported reports. These discrepancies often occur when using average metrics, breakdowns, or when exporting data that includes foreigner dimensions.
Using Average Metrics in Your Report
When your Custom Report includes average metrics (e.g., Average Order Value), the bottom row total doesn’t represent the sum of the rows. Instead, it is calculated using the metric’s formula.
How does it work?
For metrics like Average Order Value (AOV), the total in the bottom row is calculated as:
Total Sales ÷ Total Orders
For example, if your report displays multiple rows for AOV:
Bottom Row Total = Sum of Total Orders ÷ Sum of Total Sales
This ensures the total reflects the true average, not the sum of individual rows.
Using Breakdowns in Your Report
When you add a breakdown dimension (e.g., Order Tag or Discount Code) to your report, it creates a separate row for each unique combination of metrics and breakdown values. This can lead to totals that don’t match the sum of rows.As an example, the "Tracked Orders" report automatically applies specific breakdowns or filters when opened, which may result in totals that differ from dashboard summaries. You can adjust this by reviewing the report settings, removing filters, and ensuring consistency.
Example:
If you use the Order Tag breakdown with the Total Orders metric, an order with multiple tags will appear in multiple rows. This can make the sum of rows exceed the actual total number of orders because the same order is counted multiple times across rows.
Exported Report Totals vs. App Totals
When exporting a Custom Report into a .csv or Google Sheets file, the total for some metrics (e.g., Net Sales) may differ from what is displayed in Polar. This happens when the report includes foreigner dimensions, which can introduce duplicated rows.
What Are Foreigner Dimensions?
A foreigner dimension is a data attribute linked to a record but not unique to it. Examples include:
Discount Code
Product Tags
Customer Tags
Order Tags
These dimensions can create multiple rows for the same record in your export.
Example Scenario:
If an order has two discount codes and you use the Discount Code dimension, the export will include two rows for that order, each showing the full Net Sales value. This duplication inflates the column’s sum in the exported file compared to the total calculated in Polar, which accounts for these duplications.
How to Reconcile Differences
Understanding the "Tracked Orders" Report Discrepancies
To address discrepancies in the "Tracked Orders" report, follow these steps:
Open the Report in Custom Report Mode: Access the "Tracked Orders" report via the custom report settings.
Remove Applied Filters and Breakdowns: Check the report settings and disable any automatically applied filters or breakdowns.
Verify Data Alignment: Ensure the filtered report aligns with your intended data view while recognizing that the underlying data remains accurate.
For Discrepancies in the App:
Average Metrics: Trust the bottom row total, as it uses the correct formula.
Breakdowns: Understand that rows may represent overlapping data, especially when using dimensions like Order Tags.
For Discrepancies in Exported Files:
Remove Duplicates: Use tools like pivot tables or unique identifiers to consolidate rows representing the same record.
Sum Unique Records: Identify unique orders using an Order ID column and sum only those rows.
Rely on App Totals: Use the totals displayed in Polar for accurate reporting.4. Monitor Filters and Breakdowns: Regularly review applied report filters and breakdowns to ensure they align with your reporting needs.
Leverage Custom Report Settings: Use the custom report mode to verify, edit, or cross-check any applied metrics or filters.
Need Help?
If you have further questions about how your data is calculated or why totals differ, our Care Team is here to assist. Reach out via the in-app live chat for personalized support.