Filters help ensure that only the data you want is used in your campaigns. For example, if you have an inventory feed containing both new and used items but only want to create a campaign for new products, data filters are your solution.
How to set up a data filter
Go to Blueprints in the top menu.
Select a Blueprint from the list, and then a Blueprint element for the filter (e.g., a campaign, ad group, ad).
Click the blue Data Filter button under the metrics row.
Copy the tag you want to filter and paste it into the Data Filter field. Move the content after the dot and below the text, ensuring you keep the brackets around the text. Example: [inventory.model]
Add an operator (see below for information about operators) and define a filter for the data value.
Example:Data Source → [inventory]
Data Path → model = New ← Filter for Data Value
In the example above, the equal sign (=) filters for “New” models within the “inventory” data source.
To apply additional filters, start a new line. Our platform interprets this as an AND statement, allowing you to apply multiple filters to a single tag.
Example:[inventory]
model = New
price < 10000
This filters for entries that are both “New” and have a price of less than $10,000.
Common operations for data filters
= equal to
!model= not equal to (leading with “!” e.g., !model = New)
>= greater than or equal to
<= less than or equal to
> greater than
< less than
CONTAINS
IN searches in a list
Data filter examples
Here are additional examples of data filters and how to format them:
[Fluency Facebook Promo]
Campaign Goal CONTAINS Reach
[Fluency Inventory]
Category=Apparel
[Fluency DAM Media - Photos]
!excluded = true
[BackpackMedia]
virtualFolder CONTAINS [BackpackData.Month]
[BackpackData]
!Placement = Static
!Placement = Video
[inventory]
Condition=New
[gdriveimages]
virtualFolder=/[account.formalName]/Meta Media
Advanced data filters
Now that you have the basics, let's look at more advanced ways to use data filters: data subsets and polling sources.
Using data filters to create data subsets
In certain scenarios, you might need to narrow a data source into a specific subset of data for customizing campaigns, ad groups/sets, and ads within Blueprints. Here's how:
Go to Blueprints in the top menu.
Select a Blueprint from the list, and then a Blueprint element for the filter (e.g., a campaign, ad group, ad).
Click the blue Data Filter button under the metrics row.
Copy the tag from the data source you want to filter and paste it into the Data Filter field. Example: [media-collection.tags]. Delete the dot and anything that follows, and then enclose it in brackets. Example: [media-collection]
Add an arrow (→) and assign a name for your subset. Example: [media-collection] → subset 1
Define the parameter for the subset. On the next line, copy and paste a tag from under the data source. Example: [media-collection.tags]. Delete everything except what follows the dot, including brackets. Example: tags
Add an operator (refer above for common operators) and the criteria to define the parameter.
Example:
[media-collection] → subset 1
tags CONTAINS people
You can define a subset with as many parameters as needed:
[media-collection] → subset 1
tags CONTAINS people
tags CONTAINS food
You can also create multiple subsets in a data filter:
[media-collection] → subset 1
tags CONTAINS people
[media-collection] → subset 2
tags CONTAINS food
Using data filters with polling sources
You can also use data filters with polling sources to narrow down output data and exclude unwanted results. When using a data filter on a polling source, you don't need to define the data source, only the data value, as the polling source is the data source.
Example:
Data Path → model = New ← Filter for Data Value
Additionally, you can create list data, similar to a Blueprint tag, in the polling source data filter using {}. Make sure to comma-separate each value in your list, excluding spaces.
Example:
Data Path → make = {Make1,Make2,Make2,etc}