Supermetrics Custom Fields let you transform the data you use in your reporting. How the data is transformed is up to you — once you've created a custom field, it's saved in the Query Manager and ready for use whenever you need it.
These fields are entirely customizable, and offer opportunities for deep analysis and modification. If there's a field missing from a data source, for example, you can create a custom field that provides it. Any bulk changes, like corrections or formatting adjustments, can be carried out quickly and efficiently.
Before you begin
Custom fields are available for teams that have:
- At least one paid API license
- Any Google Sheets, Data Studio, or Excel Super package
- At least one paid data warehouse license that has custom schemas enabled
Contact our team or your Supermetrics customer success manager if you'd like to add custom fields to your reporting.
Create custom fields
When you create a custom field, you'll carry out 3 basic steps: you'll choose its type, how it'll transform data, and then define the steps it'll take to carry out that transformation.
When you're ready, learn how to create a new custom field.
Custom metrics and dimensions
Every custom field has one of two field types: metric, or dimension.
- Custom dimensions allow you to make bulk modifications to your data, as well as combine or correct it.
- Custom metrics allow you to add entire new metrics to your data — including any that Supermetrics itself doesn't support — or make adjustments to existing metrics.
Functions, lookups, and conditions
Supermetrics custom fields transform data with functions, lookups, and conditions. Every time you create a custom field, you'll build a ruleset that defines that field using these 3 elements.
Functions allow you to transform one field or column with a custom rule.
You'll select your function after you define its source field. Learn more about what each function does.
A lookup allows you to match values across different tables before you transform them.
You'll select the rule that defines your lookup — an operator like EQUALS or DOES NOT EQUAL, for example — and then enter the key-value pair that defines the data you want to match. The key is the current value in the dataset, and the value is what will be returned after you run the query. For example, if you wanted to apply capitalization to "black friday", then "black friday" would be the key and "Black Friday" would be the value.
Enter these pairs in the text editor, or toggle the CSV button above the editor to enter your key-value pairs in columns.
A condition allows you to define data that you want to transform, and then apply a function or transformation to only that data.
First, use the IF fields to define the data you want the condition to transform. Use OR and AND to further refine this definition if you need to.
Use the THEN and ELSE fields to describe the transformation that should happen to the data you defined in the IF fields. Select Function from the Output dropdown in either field to create and apply a function to the data.