Get started with AI models

Journey Optimizer allows you to use a trained model system that ranks offers to display for a given profile.

This feature enables you to create different AI models based on your business goals. Using these different goal-based strategies in a decision, the trained model system will help you understand how the different AI models are impacting your goals.

For example, you can select an AI model for the email channel and another one for the push channel. For each channel, the trained model system will leverage multiple data points to determine which offer should be presented first for a given placement, rather than taking into account the offers’ priority scores or a ranking formula.

AI model types

Two types of AI models are available in Journey Optimizer:

  • Auto-optimization models aim to serve offers that maximize the return (KPIs) set by business clients. These KPIs could be in the form of conversion rates, revenue, etc. At this point, Auto-optimization focuses on optimizing offer clicks with offer conversion as our target. Auto-optimization is non-personalized and optimizes based on “global” performance of the offers. Learn more

  • Personalization models allow you to define business goals and utilizes customer data to train business-oriented models to serve personalized offers and maximize KPIs. Learn more


The use of Personalized Optimization models is currently available in early access to select users only.

Creating an AI model

The main steps to create and use AI models are as follows:

  1. Create a dataset where conversion and impression events will be collected. Learn more
  2. Create an AI model that will leverage events from the dataset to rank offers. Learn more
  3. Configure your offer schema to automatically capture events. Learn more
  4. Assign the AI model to a placement in a decision to rank eligible offers. Learn more

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