A recommendation engine guides your users to highly relevant products, videos, music, movies, or even other users. Thousands of companies use personalized recommendations to boost revenue and better serve their users:
50% of new connections come from "People You May Know"
75% of movies and shows are viewed because of a recommendation
35% of sales are driven by recommendations: "Frequently Bought Together" and "Customers Who Bought This"
Your company needs a recommendation engine but doesn’t want the technical challenges that come with building and running one in-house. Mortar can help—we have built recommenders for Fortune 100 companies and startups alike. Why choose Mortar? We're fast, we're flexible, and we scale.
With our open-source frameworks, we can build an initial implementation of a custom recommendation engine in as little as one day.
Unlike many rigid off-the-shelf products, our recommendation engines are highly customizable. We fine-tune the recommendations to suit your business and your users.
Mortar runs on Hadoop, which powers data for virtually every Fortune 1000 company. Whatever the size of your data set, we manage the infrastructure so that you can focus on serving your customers.
Your company has the technical capacity to build out a custom recommendation engine—provided that you don’t have to start from scratch. Mortar’s build-it-yourself kit provides all the materials you’ll need to get your recommendation engine up and running fast. Apply now to join our build-it-yourself program.
We're now selecting an initial cohort of companies to build recommendation engines for free using our open-source code and tools.
No previous experience with data science or big data is required—we will provide all of the tools, tutorials, and code that you and your engineering team need to build a recommendation engine tailored to your business.
Each of the companies selected will also receive free support, guidance, and data strategy from Mortar to ensure success.
Mortar is a general-purpose platform for high-scale data science. Recommender systems are one great use of Mortar's award-winning platform. Other common uses include predictive analytics, natural language processing, and ETL.
Our mission is to enable you, the data scientist, to focus on doing your job rather than spending time on infrastructure and rebuilding the plumbing. Mortar jobs are written in open technologies—Hadoop, Pig, Java, Python—so you can build on the work created by your coworkers, your community, or even by your prior self.
We love data science. Time sinks and surprises, not so much. That's why we built Mortar.