The Tag Transform allows you to categorize data based on criteria you select from the data you've imported. The Tag Transform will create a new column with the tag names you've created.
This article shows you how to use the Tagging Transform.
We also have an article about using Saved Tags and how that can save a lot of time.
How to Use
Find the Tag Transform by selecting the Add Transform button in Edit Metric.
You can then name the column you want your tags to fall under and add your tags.
Let's say I'm in E-commerce and I have a list of transactions from my online store that I want to categorize by purchase type. I've defined these types as
1 . Large Purchase (over $200)
2. Regular Purchase (over $75 up to and including $200)
3. Small Purchase ($75 or less)
Starting with my raw data table, I know that I need to categorize my Purchase column.
So I open the Tag Transform and name my column Purchase Type. I add my tags and create the logic. Below is an example of my tag Small Purchase.
I can also have combinations of AND/OR logic. In this example, my Regular Purchase tag needs a combination of logic to ensure I capture purchases over $75 AND purchases of $200 or less.
Once I have all my tags in place. I can use other transforms on the new column I have created. For this example, I want to know how much is being sold by category in terms of total purchase amount. So, I group my data by my new column Purchase Type and Sum the Purchase amount:
I can now chart off of the summarized data:
Success! In just a short amount of time, I was able to define categories and their criteria, group off of them, and get the insight I needed.
For those familiar with SQL Case Statements, this transform is essentially a way to accomplish the basic functionality without actually writing SQL!
If you need to make many metrics with the same tags using the same logic, you can use Saved Tags to save a lot of time.