Managing Context Keys
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Context keys are user-specific attributes that enable advanced targeting and segmentation in your AB Tasty feature experiments. They act as the data points passed from your application to AB Tasty to determine how features should behave for different audiences.
This guide shows how to view, create, and organize context keys using the AB Tasty FE&R interface.
From the left-hand sidebar, navigate to: Feature Experimentation
→ Context keys
This opens the Your context keys screen, listing all configured context keys.
Each context key entry includes the following columns:
Name
Identifier for the context key (e.g., user_type
, browser
)
Type
Data type: STRING
, BOOLEAN
, or NUMBER
Description
Explanation of what the context key represents
Actions
Pencil icon to edit, trash icon to delete
You can also filter the list by type or use the search bar to find specific keys by name or description.
To create a new key:
Click the “Create key” button at the top right.
Fill in the following fields:
Name: Unique identifier for the key (e.g., user_is_premium
)
Type: Select from STRING
, BOOLEAN
, or NUMBER
Description: Add a short explanation to help others understand the key’s purpose
Save the key.
It will now appear in the list and can be used in targeting rules for flags.
To edit a context key:
Click the pencil icon next to the key you want to update.
Modify the name, type, or description as needed.
Save your changes.
Note: Changing the type of a context key used in active targeting may affect live campaigns.
To delete a context key:
Click the trash icon beside the key.
Confirm the deletion.
You should only delete keys that are no longer used in production environments or test configurations.
You can use the filters above the list to view only:
Boolean
String
Number
You may also use the search bar to quickly locate a specific key by name or description.
Use clear, descriptive names for keys to ensure consistency across teams.
Add descriptions for documentation and easier maintenance.
Avoid deleting keys that are actively used in live feature flags or experiments.
Filter by type when troubleshooting or auditing targeting logic.