
Behavioral Targeting
Analyze user activity and behavior changes over time and create Segments for targeted messaging.
Behavioral Targeting analyzes user behaviors using the Recency, Frequency, Monetary model and and groups users’ recent app session behaviors over time into tiers based on:

- how recently they opened the app,
- how frequently they opened the app, and
- how much time they spent in the app.
Two reports display the tier data:
The Distribution report visually organizes the relative size of each tier and also displays its user count and audience percentage.
The Transitions report shows the flow of users between tiers over time.
Understanding the distribution can help you get a pulse on user activity in your app. Seeing the transitions between tiers can give you insight on how well you are retaining users or how effective your marketing campaigns are.
You can turn this analysis into actionable information by generating audience SegmentsA grouping of audience members selected by unique or shared identifiers. Multiple identifiers can be combined within a Segment. based on selected tiers or transitions.
Use cases:
Personalization — Different tiers can represent users at different stages of using your app or different levels of interest in your product. Use Segments based on tiers to customize your messaging to each group more appropriately. For example, reward your top tiers and incentivize the lower ones.
Engagement — Transitions between tiers are opportunities to provide specific content based on engagement level. Create Segments based on transitions to message users based on which direction they are moving through tiers or which tiers they are moving between. For example, create a re-engagement campaign for users moving down tiers to help retain them, or send a message suggesting users share your app or write a review when they transition into the top tier.
When assigned a tier, TagsMetadata that you can associate with channels or Named Users for audience segmentation. Generally, they are descriptive terms indicating user preferences or other categorizations, e.g., wine_enthusiast
or weather_alerts_los_angeles
. Tags are case-sensitive. describing the tier and analysis window date are assigned to users. Tags are added at the Contact level.
Documentation
Get all the details in Behavioral Targeting.
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