Dynamic Segmentation

User Property and Behavioral Targeting

Send the right message to the right customer by creating dynamic audience segments based on any combination of user properties and actions they’ve taken.

Automated Segmentation

Our automated segmentation machine learning model assigns each user to a segment and score based on their purchase activity that gives marketers the ability to deliver highly targeted messages to improve engagement, retention, and monetization of customers.

Propensity Score

Similar to our Segmentation Model, our Propensity Model assigns each user a score (from 0 to 100) based on multiple factors which is the likelihood that the user will convert to purchaser.

Predicted Lifetime Value Model (LTV)

Using your customers activity, our model automatically segments your entire customer records based on what the predicted values you can expect from each customer. This segmentation is dynamic and updates continually based on changes in the data as individual customers frequently change over time.

Predicted Gender

We use your customers’ first names to predict their gender, which can be used to segments users to activate with gender-specific campaigns.