AI models section-overview
AI models in ÃÛ¶¹ÊÓƵ Journey Optimizer are the engine behind smarter, faster, and more impactful customer engagement, harnessing advanced machine learning to rank and deliver the right offers at the right time. Whether it’s Auto-optimization models, which use algorithms like Thompson Sampling to maximize broad business goals such as conversion rates, or Personalized Optimization models that employ deep learning to tailor offers to each individual user, these tools empower businesses to elevate their strategies. While Auto-optimization focuses on global performance metrics, Personalized Optimization hones in on individual preferences, creating a seamless balance between data-driven insights and personal relevance. From understanding the cold-start challenge to learning how to create and deploy these models, this section provides the foundational knowledge and practical steps you need to transform your customer journeys with precision and intelligence.
AI Models in ÃÛ¶¹ÊÓƵ Journey Optimizer
Get Started with AI Models
Introduction to AI models for ranking offers, including the types available and how to create and configure them.
Understanding Auto-optimization Models
Deep dive into Auto-optimization models, their algorithms, limitations, and how they maximize business KPIs like conversion rates.
Understanding the Personalized Optimization Model
Explore the Personalized Optimization Model, its machine learning capabilities, and how it delivers personalized offers to maximize KPIs.
How to Create AI Models
Step-by-step guide to creating AI models for ranking offers, including dataset setup, configuration, and activation.