Artificial Intelligence Powered Recommender as a Service
Reach the next level of personalization with Product, Content, and Search recommendations using intuitive RESTful API and SDKs tailored by data scientists.
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and 1000+ other sites and apps.Personalize User Experiences with Highly Versatile and Scalable Solution
Increase your customer satisfaction and spending with AI powered recommendations. Applicable to your home page, product detail, emailing campaigns and much more.
Recommender Engine
That Drives You Forward
Increase your customer satisfaction and spending with AI powered recommendations. Applicable to your home page, product detail, emailing campaigns and much more.
AI boosted real time machine learning
Best-in-class integration and versatility
Excellent scalability, big data infrastructure
Real Time Analytics and Seamless Configuration
Explore performance metrics and configure recommendations to reflect your personalization needs. Use simple and user-friendly interface designed for all your team members.
Explore Admin UIWatch DemoQuick and Easy Integration
into Your Environment
The recommendation engine is provided by RESTful API, HTML Widgets and SDKs for multiple programming languages.
var client = new recombee.ApiClient('database-id', dbPublicToken);
// Send a view of item 'item_x' by user 'user_42'
client.send( new recombee.AddDetailView('user_42', 'item_x'));
// Get 5 recommended items for user 'user_42'. Recommend only items which haven't expired yet.
client.send( new recombee.RecommendItemsToUser('user_42', 5, {filter: " 'expires' > now()"}),
(err, resp) => {
// Show recommendations
}
);
See Recombee API Client for JavaScript on Githubclient = RecombeeClient.new('database-id', secret_token)
# Send a view of item 'item_x' by user 'user_42'. Create user and/or item if it doesn't exist yet.
client.send( AddDetailView.new('user_42', 'item_x', 'cascadeCreate' => true) )
# Get 5 recommended items for user 'user_42'. Recommend only items which haven't expired yet.
recommended = client.send( RecommendItemsToUser.new('user_42', 5, 'filter' => " 'expires' > now()") )RecombeeClient client = new RecombeeClient("database-id", secretToken);
// Send a view of item "item_x" by user "user_42". Create user and/or item if it doesn't exist yet.
client.send(new AddDetailView("user_42", "item_x").setCascadeCreate(true));
// Get 5 recommended items for user "user_42". Recommend only items which haven't expired yet.
RecommendationResponse recommended = client.send(new RecommendItemsToUser("user_42", 5)
.setFilter("'expires' > now()"));client = RecombeeClient('database-id', secret_token)
# Send a view of item 'item_x' by user 'user_42'. Create user and/or item if it doesn't exist yet.
client.send( AddDetailView('user_42', 'item_x', cascade_create=True ) )
# Get 5 recommended items for user 'user_42'. Recommend only items which haven't expired yet.
recommended = client.send( RecommendItemsToUser('user_42', 5, filter=" 'expires' > now()") )var client = new recombee.ApiClient('database-id', secretToken);
// Send a view of item 'item_x' by user 'user_42'. Create user and/or item if it doesn't exist yet.
client.send( new rqs.AddDetailView('user_42', 'item_x', {cascadeCreate: true}), callback);
// Get 5 recommended items for user 'user_42'. Recommend only items which haven't expired yet.
client.send( new rqs.RecommendItemsToUser('user_42', 5, {filter: " 'expires' > now()"}) )
.then((recommended) => { ... }) //Supports both Promises and callbacks$client = new Client('database-id', $secret_token);
// Send a view of item 'item_x' by user 'user_42'. Create user and/or item if it doesn't exist yet.
$client->send( new Reqs\AddDetailView('user_42', 'item_x', ['cascadeCreate' => true]) );
// Get 5 recommended items for user 'user_42'. Recommend only items which haven't expired yet.
$recommended = $client->send( new Reqs\RecommendItemsToUser('user_42', 5, ['filter' => " 'expires' > now()"]) );var client = new RecombeeClient("database_id", secretToken);
// Send a view of item "item_x" by user "user_42". Create user and/or item if it doesn't exist yet.
client.Send( new AddDetailView("user_42", "item_x", cascadeCreate: true) );
// Get 5 recommended items for user 'user_42'. Recommend only items which haven't expired yet.
var recommended = client.Send( new RecommendItemsToUser("user_42", 5, filter: " 'expires' > now()") );# Send a view of item 'item_x' by user 'user_id'. Create user and/or item if it doesn't exist yet.
POST http://rapi.recombee.com/database_id/detailviews/
Data: {'userId': 'user_42', 'itemId': 'item_x', 'cascadeCreate': true}
# Get 5 recommended items for user 'user_42'.
# Recommend only items which haven't expired yet (filter: 'expires' > now()).
GET http://rapi.recombee.com/database_id/recomms/users/user_42/items/?count=5&filter=expires%27%20%3E%20now()
Our Customers Say
Kristie ChenProduct Head at 9GAG
Daniel UhmProduct Manager at Slickdeals
Meindert van der MeulenHead of Strategy at Showmax
Dennis OstnerHead of E-commerce at Robert Kunzmann GmbH & Co.
Petr KelinManager at MAFRA, a.s.
Jan LajkaHead Of Data & Programmatic at FTV Prima
Vojtěch KosteleckýProduct Manager at Economia
Andrew MoriTech. Director at Konga.com
Haydn StraussCOO at Unfiltered Media Group
Nicholas Blicker LarsenCEO at Design Group
Giovanni BartoliCEO at Casa Cenina
Lucas ColettCEO at BUBB.Store
Mikael SetterbergCTO at Keyflow
Rodrigo BendiaCTO at ChicoRei
Vojtěch KnyttlCTO at GoOut
Sumedh ChaudhryCEO at NewsBytes
Arvind SarafFounder, CEO & CTO at Wishbook Infoservices
Christian MedinaData Scientist at Osigu "Daily traffic to the 9GAG site amounts to hundreds of millions of users worldwide. To provide a unique user experience for each and every one of them, we needed to implement a recommendation system that would allow for the most advanced, real-time personalization of their experience. So we chose Recombee. Thanks to their solution, we managed to increase, among other KPIs, post views by 37%, overall interactions by 22%, and users’ session duration by 7.5%. With Recombee, we've taken engagement with user-generated content to the next level."
Kristie ChenProduct Head at 9GAG"Recombee was able to handle our very specific use case around providing recommendations with a highly volatile inventory of user-generated content. 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."
Daniel UhmProduct Manager at Slickdeals"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 MeulenHead of Strategy at Showmax"Recombee is an amazing recommendation engine which we use for personalizing different parts on our website, including homepage, product detail page, and search. With their solution, we managed to increase our conversion rate by 14% and shopping cart volume by 8%. A great partnership and looking forward to improving our customer journey even more."
Dennis OstnerHead of E-commerce at Robert Kunzmann GmbH & Co."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 KelinManager at MAFRA, a.s."Our cooperation with Recombee is very fruitful. We are having periodic calls where we are discussing possibilities for adjusting and improving current models to perform better for our use-case and also looking for new places for the deployment of personalized recommendations. So far, Recombee helped us to increase our CTR on the homepage by 15% and boost video views by 3.5 %. At the moment we discuss recommendations from linear TV to video on demand archive, which can bring our cooperation to even higher level. Highly valued partnership!"
Jan LajkaHead Of Data & Programmatic at FTV Prima"Thanks to Recombee’s recommendation service and Geneea’s NLP, we were able to personalize news and articles for visitors of our major portals (aktualne.cz, volny.cz, atlas.cz), increasing the number of pageviews by 64 percent. We expand recommendations to other scenarios such as video recommendations or personalized galleries."
Vojtěch KosteleckýProduct Manager at Economia"As a huge e-commerce site with millions of users we were looking for a stable and reliable partner that would back up our robust item catalogue and high traffic. The integration was simple and quick with incredible support assistance from Recombee when we needed it. Recombee, with its impressive real-time product recommendations, provides us with a perfect personalization solution to accomplish our KPIs and improve our customer satisfaction. Recombee solution currently drives an impressive 24% of Konga’s revenues."
Andrew MoriTech. Director at Konga.com"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 StraussCOO at Unfiltered Media Group"It has been really difficult to find a solution that could integrate many different data sources and be 100% customizable, but with Recombee we get this. Recombee has fundamentally changed how we are serving recommendations and has really helped us grow. In addition to this, they have great customer support and are always ready to help."
Nicholas Blicker LarsenCEO at Design Group"Recombee is easy to use, the support is fantastic and costs are affordable. We changed our previous recommendation engine with good improvements without efforts."
Giovanni BartoliCEO at Casa Cenina"Recombee's recommendation solution is incredible. Our e-commerce platform can recommend products with much more intelligence for our customers. The support is also fantastic!"
Lucas ColettCEO at BUBB.Store"Surprisingly easy to integrate yet powerful."
Mikael SetterbergCTO at Keyflow"If you are looking for a flexible, well documented and powerful recommendation engine, Recombee is definitely the best option in the market. Based on our tests, Recombee provided up to 19% lift in recommendation revenue and increased the conversion rate by 12%"
Rodrigo BendiaCTO at ChicoRei"Recombee opened us many new possibilities in recommending relevant events, places, and artists, to our customers. It works great."
Vojtěch KnyttlCTO at GoOut"As a founder of a new age media platform, increasing customer engagement is our number one goal and Recombee helped us in the same with their fantastic recommendation engine. NewsBytes has been working with Recombee for more than 6 months now and we are extremely happy with Recombee’s product."
Sumedh ChaudhryCEO at NewsBytes"We had seen significantly better conversions of users to paying customers on Wishbook app, a part of which was due to the similar product recommendations & relevant products for the user being served on the app by Recombee."
Arvind SarafFounder, CEO & CTO at Wishbook Infoservices"Recombee will bring your sales platform to life. It's easy to integrate, customizable and provides timely recommendations. All this combined with a great support team."
Christian MedinaData Scientist at OsiguRead more on
