Filters are a powerful tool used throughout the dashboard in various tools that allow you to fine-tune how data is displayed and analysed. No matter which tool you’re using filters help you zero in on the exact slice of data you need. Here's how to use them correctly.
What Are Filters For?
Filters let you define conditions based on the data collected in your program. These conditions determine which contacts (or other entities) are included or excluded.
You’ll encounter filters in various parts of the dashboard, so understanding filters is essential to making your workflows efficient and your data accurate.
Structure of a Filter
Each filter is made up of four main components, top-down:
Filter ‘type’: This defines what you're filtering on—usually a contact, but it can vary depending on where you're applying the filter.
‘Option’: This determines the specific attribute or data point you're interested in (see the descriptions under the titles)
‘Operator’: The logic that connects the option and value. For example:
equals
contains
greater than, less than etc.
‘Value’: The specific data you want to filter by, such as a date, text, or numerical value.
Filter Operation
When applying filters, understanding how to combine them is key to building the right logic.
Adding Filters ‘+’
When you add multiple filters within the same group, they are treated as an AND condition. This means all the filter conditions must be true for a contact to match.
Example: (only a contact matching both criteria will be included)
Filter 1: Email subscription status equals subscribed
AND
Filter 2: Created at date is less than 90 days ago
Adding Filter Groups ‘filter group +’
When you create multiple filter groups, you're applying an OR condition. This means a contact only needs to meet the conditions in one of the groups to match.
Example: (a contact matching criteria from either filter group will be included)
Filter Group 1: Age is greater than 18
OR
Filter Group 2: Last transaction date is less than 30 days ago
Combining Filters and Filter Groups
This allows you to build more flexible logic by combining strict (AND) and broad (OR) conditions.
Example: (a contact will match if they meet either of the filter group criteria. Notice, to satisfy Filter Group 1, both filters within it must be true.
Filter Group 1: Age is greater than 18 AND Credit balance is greater than 29
OR
Filter Group 2: Last transaction date is less than 30 days ago
Limitations
Not based on specific form submissions (unless the form includes a hidden custom contract attribute that stores a value)
Not based on sign-up location
Must use existing data (Filters only work on attributes and events that have already been captured—there’s no filtering on data that doesn’t exist yet.)
Tips
Keep it simple
Overcomplicating your filter logic can create unexpected results. Start small and build up.
Think in terms of attributes
Always ask: “Do I have a specific data attribute I can filter on?” If not, consider updating your data collection strategy.
Test before launching
If you’re using filters for automations or campaigns, preview your audience to make sure it matches expectations.
Use custom attributes strategically
For special tracking or filtering needs, custom attributes can store extra data—like tagging someone who submitted a particular form.