Sunnyvale, CA (PRWEB) May 09, 2014
Flipora, the popular online discovery company that suggests websites to users based on their personalized interests, is growing in popularity among global adopters. The company announces that it has now has 25 million users, and is rapidly approaching 30 million.
“Every day, Flipora is helping people all over the world discover new and interesting websites,” says Jonathan Siddharth, Flipora Co-CEO. “It’s very rewarding to us on a personal level, to see the technology we developed helping people in a very real way. When someone signs up for Flipora, our recommendation engine uses machine learning to intelligently infer a person’s interests based on their web browsing history as well as their Facebook activity. The web is the world's largest knowledge base, and Flipora’s goal is to categorize the world's knowledge and recommend it to users based on their interests.”
“We are really excited by the growth potential for Flipora,” says Vijay Krishnan, Flipora Co-CEO. “Flipora’s user base has been almost doubling every year. We have also recorded an all-time high in new user registrations, with over 100,000 new registrations in a single day. This is a huge milestone for us. This is also the year we made the Top 10 list of social media sites for sharing, alongside Facebook, Twitter, and LinkedIn.”
Flipora’s personalization and recommendation engine analyzes 100 million websites each day, roughly 25 times the size of Wikipedia. The service monetizes through the inclusion of ads, and Flipora has been profitable since late last year with revenues growing at a rapid pace.
Flipora Co-CEO Vijay Krishnan says, “We take a long-term view to building our company and product, which translates to a focus on having a scalable business model alongside a great product user experience. We expect to end the year with over 50 million users and to continue scaling our rapidly growing revenues. It’s exciting times ahead.”
Over the last year, Flipora has seen an astounding increase in its mobile user base. Today about 25% of Flipora’s new users worldwide sign in via mobile, and in the U.S., mobile accounts for 50% of new users. Flipora also expects to release a mobile app for iOS later this year.
Given Flipora’s strong international growth, the company is happy to announce translations in 11 new languages; German, Spanish, French, Hungarian, Indonesian, Italian, Portuguese, Vietnamese, Chinese, Japanese, and Korean. This will help Flipora gain a significant foothold in many new markets.
One of the unique aspects of Flipora’s recommendation engine is its ability to do intelligent personalization automatically with minimal input from the user. Flipora uses state-of-the-art machine learning algorithms to automatically infer what topics users like, based on a user’s web browsing history and Facebook data. This lets Flipora automatically figure out what a user is currently in the mood for and make recommendations based on that.
Additionally, users can choose to follow topics and other like minded users. This personalization module,called FlipCat, can analyze a user’s web browsing history data, data from Facebook, and from other sources, and categorize it to build a fine grained, customized profile of the user’s interests. This helps the recommendation engine suggest interesting websites on topics that users will love.
Flipora is announcing the launch of an API for FlipCat that developers can request access to by emailing support(at)flipora(dot)com. FlipCat is now avaliable at http://ai.flipora.com. Flipora is also planning significant updates to its core recommendation engine in the coming months. You can receive more updates from the official Flipora Blog.
Flipora’s mission is to categorize the world’s knowledge and recommend the best of the web to users based on their interests. Sign up at flipora.com to follow your interests and follow other interesting users. You can follow Flipora on the following social media sites to stay tuned for more updates.
Flipora on Facebook
Flipora on Twitter
About The Company
Flipora is a web-based recommendation engine that recommends websites to users personalized to their interests. Flipora uses machine learning to intelligently infer a users interests based on their Web browsing history and Facebook activity. The Web is the world's largest knowledge base and our goal is to categorize the world's knowledge and recommend it to users based on their interests. Try it out at Flipora.com
Starting out of Stanford University, Flipora.com now has nearly 30 million users and has raised Venture Capital from some of the best investors in Silicon Valley, with prior successes such as PayPal, Twitter, Skype, Tesla, Baidu, and Hotmail.
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