Data & Results
Recommendations are based on the provided data. The two most important types of data are the catalog & the interaction data.
- Catalog - information about the content or products you want to recommend (e.g. title, categories, description, images, etc.).
- Interaction Data - what a user has viewed, watched, purchased, etc.
Catalog
Item Properties
Describe the items that you want to recommend.
Categories
Text Description
Images
Labels
Genres
Expiration Date
Destination
Age Restrinction
Geo Location
and more
User Properties
Describe your users.
Gender
Language
Age
Subscription
Registration date- and more
Interactions
Live Interactions
Interactions between Users and Items are the most inportant data for the recommender system.
Various Interaction Types
Views
Purchases
Cart Additions
Ratings (Likes)
Bookmark
View Portions
Interaction History (Optional)
Data Processing
Recombee Processes the Ingested Data Instantly in Real-Time
Thanks to our innovative incremental training of the models, new interactions and new content are taken into consideration within milliseconds.
Machine Learning (ML)
To come with the best performing recommendations and search, Recombee uses a huge portfolio of the ML and AI techniques.
- Collaborative filtering algorithms
- Content-based algorithms
- Reinforcement learning algorithms
- and many more
Configuration
Recombee offers unprecented configurability of the resulting recommendations and search results.
For each place where you show the recommendations, you can specify:
- The behavior of the recommendation model
- What content/products can be recommended
- What content/products shall be boosted in the recommendations
... and more, to align the recommendations with your product vision.
Explore More About Scenario Settings
Showing Results
You can personalize the whole user experience.
Personalization is often applied to
- Homepage rows
- Full-text search
- Product/Content detail
- Watch/Read next
- Personal feed
- Email campaigns
Recombee empowers you to implement advanced use cases like
- Personalizing the order of rows or sections on the homepage
- Recommending specific categories or brands
- Suggesting artists or albums based on songs previously listened to
Sending data and requesting recommendations is made easy thanks to our
Analyzing Results
Insights provides targeted control over your unique KPIs, enabling informed, strategic decisions.
Insights analytics section in the Admin UI offers various predefined and fully customizable reports to track how users interact with recommendations and your platform.
Explore Insights
