Meet Us at RecSys 2024 · 14–18 October 2024 · Bari, Italy · Read More
Content Recommendations

Improve User Engagement and Retention with Content Recommendations

Personalize the user experience through real-time recommendation engine. Organize your content in the most relevant way for individual users based on their behavior and preferences.

Your Personalized Content

01

Personalized for a User

After receiving all the user’s data including his historical behavior, organize content in a unique, personalized way.

Personalized for a User
02

Recently Interacted With

Display the content the user recently interacted with.

Recently Interacted With
03

Similar Content

Show content similar to one the user had already interest in, based on common content attributes.

Similar Content
04

Liked This, Try That

Recommend the content to users with similar tastes and habits based on their previous behavior.

Liked This, Try That
05

Most Popular Content

Show your most engagement and trending content.

Most Popular Content
06

Latest Content

Display the newest, recently added or released content.

Latest Content
07

Personalized Search

Enhance your online experiences with tailored search results.

Personalized Search

Core Technology

Adapting to your Data

Adapting to your Data

Personalization based on the Collaborative and Content-based filtering algorithms.

Dynamically Retrained Models

Dynamically Retrained Models

Real-time Personalization for your individual user at every point.

Accelerated Integration

Accelerated Integration

Quick Integration through our well documented and easy to use APIs, SDKs.

AI-powered A/B Testing

AI-powered A/B Testing

To keep maximal KPIs at any time, AutoML AI is applied to optimize the algorithm ensambles.

Advanced Business Rules

Advanced Business Rules

Our solutions enables quick and easy addition of any Business Rules through boosters or filters.

Real AI Inside

Real AI Inside

Formation of Deep Neural Networks helps to predict the next action based on the historical behavior.

How Recombee Works

How Recombee Works Schema

Success Stories

50%
Increase in Click Through Rate

"Prior to Recombee, we used a general recommendation algorithm based on popularity and date published. Since moving our recommendation system to Recombee, we’ve seen a 50% increase in click-through across our 5 media brands (millions of readers per month). Recombee was easy to integrate, test, and deploy within just a couple of hours."

Haydn StraussHaydn StraussCOO at Unfiltered Media Group
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Higher Engagement

"Recombee is capable of scaling the service and keeps pace with our rapid growth. Constant innovation and proactive development of new features makes our collaboration smooth and pleasant."

Meindert van der MeulenMeindert van der MeulenHead of Strategy at Showmax
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40% higher
CTR of suggested articles

"We conducted A/B testings of multiple recommendation engines to find the best content personalization solution. Out of all solutions, only Recombee outperformed our internal read-next recommendations of news articles. After long-lasting A/B testing, Recombee achieved 40% higher CTR of suggested articles, which ultimately led to deployment of the solution to most of our news sites (iDNES, Lidovky, Expres)."

Petr KelinPetr KelinManager at MAFRA, a.s.
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34%
Increase in Video views on VOD platform

"Recombee allows us to modify how we want the recommendations to behave across our platforms in very specific use cases. The implementation of Recombee on the VOD platform prima+ helped us to increase video views by 34% and ad views by 73%, resulting in a significant rise in advertising revenue. Another major success has been the growth of recirculation, which is our top priority on online magazine platforms. We are currently discussing extending their recommendations also to our emails. Highly valued partnership!"

Jan LajkaJan LajkaChief Data Officer at FTV Prima
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Our Customers

9GAGAudiomackUnfiltered Media GroupStingraymafraprimaPathé ThuisShowmax

and 1000+ other sites and apps.