Recommendations & Search
Real-Time Recommendations
Recombee functions as a dynamic real-time recommender, instantly adapting to new interactions—whether it's a content view, product purchase, like, or dislike—and any content changes, such as adding new items or modifying attributes.
This capability is particularly advantageous for platforms with fast-moving content, including News Sites, Deal Aggregators, and P2P Marketplaces.
Additionally, the real-time responsiveness of Recombee effectively addresses the cold-start challenge for new users. From their very first interaction, users receive personalized recommendations, which only become more refined as additional data is collected.
Segmentations: Recommending Categories, Brands, Tags, Artists, and More
While traditional recommender systems focus on suggesting individual pieces of content or products, Recombee goes further by offering recommendations for groups of related items, known as Item Segments.
Segmentation Examples
Categories/Genres
Actors
Brands
Tags
Artists or albumsbased on songs
Individual homepage rowsThis comprehensive approach enhances personalization across a wider array of use cases than conventional systems allow.
You can create dedicated sections like "Your Favorite Brands" or "Similar Artists," and even rearrange UI elements to highlight the most relevant options for each user. This optimization significantly enhances their experience, exemplified by features like the Fully Personalized Homepage.
Item Segmentations are easily defined in the Admin UI using your existing catalog data. Segmentation can be based on a single attribute, such as category, or a combination of multiple attributes, leveraging our innovative ReQL query language for added flexibility.
Read more about Item Segmentations
Read the Item Segmentations Documentation
Fully Personalized Homepage
Deliver the ultimate personalized experience with the Fully Personalized Homepage.
This innovative solution enables complete personalization of both the content within each section and the order in which they appear.
For example, a user who loves thrillers will see a homepage that is uniquely tailored to their interests, showcasing different rows and videos compared to someone who prefers comedies. This bespoke approach ensures that each user enjoys a distinct experience that reflects their individual tastes.
Recombee provides the essential tools to achieve this level of personalization:
- Item Segmentations: Customize the order of rows and sections based on user preferences.
- Advanced Filtering: Cater to diverse use cases, including the personalized reordering of content curated by your editors or product team.
- Batch Requesting: Obtain recommendations for all rows simultaneously, complete with automatic deduplication to avoid content overlap.
Explore the Fully Personalized Homepage Documentation to learn more about creating tailored experiences for your users.
Personalized Infinite Feed
Engage your audience with a captivating Personalized Infinite Feed that dynamically adapts to their unique tastes.
With Recombee, you can seamlessly integrate an infinite scrolling experience, allowing a continuous stream of content that loads new results as users scroll.
Powered by advanced ensembles that process data in real-time, Recombee is perfectly designed for platforms with user-generated content (UGC). This ensures that even the most dynamic and rapidly changing environments remain fresh and relevant for users, enhancing their overall experience.
Discover how this works in practice by checking out the 9GAG Case Study.
Personalized Semantic Search
Deliver intent-driven, context-aware search results even when search terms don’t directly match the content.
Recombee’s search combines full-text query matching with machine learning on user interaction data to deliver precise, highly personalized results.
For enhanced accuracy, our Premium feature, Semantic Search, uses a large language model (LLM) to interpret the intent and context of user queries. This approach goes beyond keyword matching by capturing the deeper semantic meaning of each query, allowing the system to retrieve results that align with the user’s true intentions.
With Semantic Search, users receive more accurate, context-aware results—even if their query terms don’t directly match the content in the database. For example, they can search for "movies about racing" or "eco-friendly jackets for extreme cold," and discover precisely relevant recommendations.
