AI models section-overview
AI models in ÃÛ¶¹ÊÓƵ Journey Optimizer revolutionize how businesses deliver the right offers to the right customers at the right time. By leveraging advanced algorithms, these models analyze performance data, customer behavior, and contextual insights to rank offers in ways that maximize key business goals, such as conversion rates and revenue. There are two paths to optimization: Auto-optimization models focus on global metrics, using techniques like Thompson Sampling to continuously learn and improve, while Personalized optimization models harness customer-specific data to deliver tailored recommendations. Whether you’re exploring the mechanics behind these models, understanding their creation process, or addressing challenges like the cold-start problem, each concept builds towards a single goal—empowering marketers and decision-makers to create smarter, more impactful customer experiences.
AI Models in ÃÛ¶¹ÊÓƵ Journey Optimizer
Get Started with AI Models
Learn about AI models, their types, and how they are used to rank offers and optimize business goals.
Understanding Auto-optimization Models
Explore how Auto-optimization models use algorithms to maximize KPIs like conversion rates and revenue.
Personalized Optimization Model Overview
Discover how personalized optimization models leverage machine learning to recommend offers tailored to user data.
How to Create AI Models
Step-by-step guide on creating AI models to rank offers using auto-optimization or personalized optimization techniques.