When you are creating new measures, it is a good idea to think about their names from the end user’s point of view. In this article, we have summarized a collection of best practices that always worked for us.
Make them user friendly
GoodData measure names may include any characters. Take advantage of that and name the metric in a way that is most natural to your users. Use plain English (or whatever is the language of your audience) rather than abbreviations, all lowercase with underscores or camel case.
Your users will find it easier to work with “Weekly Active Users” then “weekly_active_users” or “WeeklyActiveUsers”.
Note: If you are a developer, treat a measure name as a title, not as an identifier.
Keep them short
In many situations, long names may be trimmed: column names in a table, legends of charts, or the catalog of GoodData Analytical Designer.
This is why we recommend to keep the measure names short and put the key information at the beginning.
Example: Use “Weekly Active Users” and Monthly Active Users” rather than “Active Users (Weekly)” and “Active Users (Monthly)”.
If you have two measures showing a percentage and count of something, put the percentage indicator at the beginning rather than at the end.
Example: Use “Weekly Active Users” and “% of Weekly Active Users” rather than “Weekly Active Users (%)” or “Percentage of Weekly Active Users”.
However, try to avoid acronyms - always prefer readability and clarity over brevity.
Example: Use “Weekly Active Users” and “Monthly Active Users” instead of “WAU” and “MAU”.
Note: It’s possible to override the measure names in insights when the meaning is clear from the contest (see Use insight specific names below).
The Analytical Designer can organize the items in your catalog into folders. It is a good idea to group related measures under the same folder.
For example, if you followed our advice above, you may want to have measures such as “Weekly Active Users”, “% of Weekly Active Users”, or “Monthly Active Users” under a folder named “Active Users” or “Usage”.
Use insight specific names
In some contexts, the full measure name may look a little redundant or take too much space.
For example, consider a table named Weekly and Monthly Active Users with measure such as “Weekly Active Users”, “% Weekly Active Users”, “Monthly Active Users” and “% Monthly Active Users”.
In that case, you can use Analytical Designer to create insight specific aliases so your table columns will be simply “WAU”, “%WAU”, “MAU”, and “% MAU”. Just don’t forget to make sure that your abbreviations are easy to understand from the context!