Product Recommendations

Maximize your Revenue and Customer Satisfaction with Product Recommendations

Personalize the product offer for every individual customer. Utilize real-time personalization for a better user experience using our content and collaborative filtering based recommender system.

Your Personalized Product Offer

01
You May Also Like / Others Also Bought
Cross-sell / Up-Sell by showing products mainly based on collaborative filtering and onsite user behavior.
02
Frequently Bought Together
Show your users complementary products based on their buying behavior.
03
Recommended for You
Show your users new product offers based on individual user’s preferences and product similarities.
04
Personalized Search
Display the most relevant product offers for each individual user to satisfy its specific needs and save time.
05
Local Deals Trending Near You
Show personalised product offer to your user by using their geo-location.
06
Popular Right Now / Trending Now
Show the most trending products based on your user purchases and general trend.
07
Recently Interacted With
Display the products the user recently interacted with.

Core Technology

Adapting to your Data
Personalization based on the Collaborative and Content-based filtering algorithms.
Dynamically Retrained Models
Real-time Personalization for your individual user at every point.
Accelerated Integration
Quick Integration through our well documented and easy to use APIs, SDKs.
AI-powered A/B Testing
To keep maximal KPIs at any time, AutoML AI is applied to optimize the algorithm ensembles.
Advanced Business Rules
Our solutions enable quick and easy addition of any Business Rules through boosters or filters.
Real AI Inside
Formation of Deep Neural Networks helps to predict the next action based on the historical behavior.

How Recombee Works

Success Story

Daniel Uhm

Product Manager at Slickdeals

"Placing recommendations on our homepage was a huge success: 70%+ higher product detail page views and 30%+ higher clickthroughs.The Recombee team is a great partner in helping solve our unique use cases, and we look forward to continue working with them."