Advanced configuration options for power users. Control data analysis parameters, optional features, and performance thresholds.
By default, the script analyzes rolling time periods (last 30 days, etc.). The fixed date range feature allows you to analyze specific time periods for comparison or historical analysis.
How to set: Double-click the date range cells to input specific start and end dates.
Use cases:
The six-bucket classification system uses cost and ROAS thresholds to categorize products as “high” or “low” performers. These thresholds can be customized in Advanced Settings.
Configurable parameters:
Adjusting these thresholds changes how products are distributed across the six performance buckets, allowing you to tailor the analysis to your specific business metrics and profitability requirements.
For accounts with large product catalogs, the standard script execution may timeout before completing data processing. The “lots of products” setting manages this limitation by filtering out low-signal products.
Configuration options:
This setting prevents script timeouts for large datasets while maintaining analysis of products that actually matter to your performance.
More information: Paid script timing out? Use the lotsproducts variable
The script can generate supplementary reports for deeper analysis. These reports are off by default because they increase script execution time, particularly when running through the MCC script across multiple accounts.
Available additional reports:
How to enable: Tick the checkboxes for the reports you want to generate.
Accessing reports: After the script runs, use the sheet hamburger menu to unhide the tabs. The reports appear as hidden tabs on the right-hand side of the tab list.
Data format: These reports provide raw data without the polished UI of the main tabs, designed for custom analysis.
Campaign name filters allow you to analyze specific subsets of your Performance Max campaigns rather than account-wide data.
Use cases:
Filter syntax: Use campaign name patterns to include only matching campaigns in the analysis.
Best practice: For complex filtering needs, consider creating separate scripts and sheets for different campaign groups rather than repeatedly changing filters.