The Tag Transform allows you to categorize data based on criteria you select from your data. It will create a new column with the tag names you've created.
For those familiar with SQL Case Statements, this transform is essentially a way to accomplish the basic functionality without actually writing SQL.
How to Use
From the Data tab, click on "Add Transform" at the left and select the Tag transform.
First, give the new column a name.
Then enter in the value you want to use for your first tag (under "Value").
Now specify what conditions need to be met for a row to receive that label (under "Condition"). You can add multiple conditions with any combination of AND/OR logic. Note that the query is not case sensitive.
You can add several tags, and when you are done you can add a "Default" tag that will be applied for any rows that do not meet the criteria of any of the other tags.
Note that the logic will be applied from top to bottom, so if a row meets the criteria of multiple tags, only the first one will be applied.
When you are done, click "Run" to add the new column.
Using Default Tags
You can either give a specific value to be applied to each row that doesn't fit any of the other tag criteria, or you can select a specific column to use as the default values for those rows.
If you want to label all other rows that aren't affected by the criteria you added for each tag with something like "Other" or "Unknown" then select "Assign the value" and enter in a value in the field. You could also not add any default field and those rows will be blank.
If you have another column that has data you want to use in the new tagged column, you can select "Assign value from column" and choose the column from the dropdown menu.
In this example, I have a list of lead sources, but including specific pages from our website. I can create a tag to label all those web pages as "Website" and then choose the current "Lead Source_detailed" column to fill in the rest of the rows that didn't come from the website.
In this example, I categorized daily ecommerce purchases with Large, Regular, and Small tags based on the number in the "total_price" column. Since the logic should cover every purchase, I didn't add a default tag.
In this example I created a tag based on the "referring_site" column to clean up the data and categorize the sites better. I used a default tag to catch any that I missed with the other tags. Later, I could filter to see only the "other" sites and see if there are other tags I'd want to add.
Using Saved Tags
If you need to use the same or similar logic to add tags to other reports, you can use Saved Tags to save time.
Add a Tag Transform and look to the bottom of the window and click 'Saved Tag Library'. You can then search for other tags that have been used by your company.
There are two options for using a saved tag. "Select" lets you use that same tag the way it is set up. Note that any changes made to the tag will also affect any other metrics using it. If you want to adapt a current saved tag, click on "Use as Template" to make a copy of it that you can change without affecting any other metrics.