Use Case Example
You noticed that two days in September reported too many conversions in your connected marketing platform data source. You want to override those values with the correct values instead. You can apply these same principles on different cases with the same core issue, just adjust the logic and rules accordingly.
Step 1: Prepare Your Corrected Data
Create a Google Sheet or a file import that includes only the data for the affected dates. Make sure to:
Include the corrected metric values (e.g. conversions).
Match the dimensions used in your original setup, especially the ones used in your custom field mapping (e.g. Campaign, Traffic Source). This is crucial so that Funnel can stitch the data correctly.
Make sure that all date values in the date column follow the same format.
Make sure the metric values are formatted as numbers, not text, otherwise they won’t be recognized as metrics in Funnel.
Learn more:
Step 2: Set the Incorrect Data to Zero using a Custom metric
You will need to use a custom metric to stitch the data from the source with the incorrect values together with your corrected uploaded data. To avoid double-counting, you'll need to adjust the rules in your custom metric (e.g. Conversions) so that the original data from the marketing platform data source returns 0 for the affected days.
Go to Organize > Metrics and create a new custom metric, or edit your existing one (e.g. Conversions).
Click Edit in the top right corner.
Add a new rule for the affected data source and date range, like below. Make sure you include all the needed conditions for the specific data source or any other dimensions. For example if it’s only a specific campaign that had incorrect tracking you would specify that campaign here.
Example of how the rule could look like to correct a couple of days in September:
WHEN: Data Source → exactly matches → Data Source to be corrected
AND: Campaign → exactly matches → Campaign to be correctedAND: Date → ≥ → enter the start date of the incorrect period (yyyy-mm-dd)
AND: Date → ≤ → enter the end date of the incorrect period (yyyy-mm-dd)
In the THEN field, choose:numeric value → 0
Place this rule above your existing rules if you have several so it takes priority for those dates. As the rules are executed in order from the top to bottom.Step 3: Map Your Corrected Data to the Custom Metric
Once your corrected data is uploaded:
Edit the custom metric again, this time for your corrected data. Use a similar rule structure, but this time specify the imported source and the corrected values you want Funnel to use for those same dates. If you only uploaded the corrected dates you may skip the date conditions in this rule.
WHEN: Data Source → exactly matches → Data Source with the corrected dataAND: Date → ≥ → enter the start date of the incorrect period (yyyy-mm-dd)
AND: Date → ≤ → enter the end date of the incorrect period (yyyy-mm-dd)
In the THEN field, choose:value of → the field with the corrected data
Step 4: Map the Dimensions in the Corrected Data to your Custom Dimensions
The Dimension data in your corrected data source also needs to be mapped to all the Custom Dimensions you are using when viewing the data. This is what makes the data from the separate data sources to be stitched together.
Example of how the rule could look like to map the Campaign field from the corrected data source to the Campaign Custom Dimension.
WHEN: Data Source → exactly matches → Data Source with the corrected data
In the THEN field, choose:value of → the field with the dimension to be mapped.
Once all your rules and mappings are in place, it's time to check if everything works as expected.Step 5: Verify the Setup
Check your dashboard or Data Explorer to confirm the correct values are now showing.
If you’re using filters (e.g. Segment or Traffic Source) in your reporting, make sure your imported data is mapped into those dimensions (Step 4).
Common Pitfalls
Not including all required dimensions in the file (this breaks the mapping).
Forgetting to set the original source to return 0.
Data imported as text instead of number (this prevents metrics from calculating properly).