Target Personalization: Getting Started with Recommendations & Category Affinity
Learn how to build a strong foundation for getting started with Recommendations. Receive a better understanding of the algorithms that power Recs, and how to leverage Recs successfully.
Key takeaways
- Recommendations in Rex offer personalization at scale, allowing for intelligent recommendations of hundreds or thousands of items based on chosen algorithms like behavior-based, popularity-based, content similarity, and more.
- Rex provides customization options such as sequencing, weighting, exclusion rules, and more, making it a strong tool for personalized merchandising control.
- Rex is ideal for recommending a large number of products or content items across thousands or millions of items, providing personalized recommendations based on user profiles.
- Rex may not be suitable for scenarios with a small number of offers, rapidly changing catalog items, low interaction frequency, or when personalization is primarily based on user characteristics like loyalty segment or geography.
- Setting up recommendations in Rex involves teaching the system about products or content through catalog creation, capturing user behavior data, and providing context for recommendations to be shown.
- Category Affinity focuses on recommending categories or groupings of products or content rather than specific items, based on user interactions and points assigned to different categories.
- Category Affinity can be leveraged by setting up audiences based on user preferences, assigning points to categories, and using criteria like favorite or first to personalize recommendations.
- Criteria sequences in Rex allow for prioritizing recommendations based on visitor behavior and data depth, ensuring a full template of recommended items by layering criteria based on visitor value and behavior.
- The flexibility of Rex criteria sequences enables the prioritization of recommendations by assigning high-value criteria first and filling in the template with additional criteria as needed.
- Leveraging criteria sequences is crucial for ensuring depth in recommended items, especially when dealing with categories at different levels of granularity.
At a glance
Product: Target
Series: Adobe Customer Success Webinars
Role: Admin,Developer,Leader,User