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BloomReach Launches to Solve the Multi-Billion Dollar Big Data Problem of the Digital Discovery DivideMany Web Businesses Are Missing Out on 80% of Potential Demand Because Their Most Relevant Products and Services Don't Show Up in Search and Social Channels (February 22, 2012)
MOUNTAIN VIEW, CA -- (Marketwire) -- 02/22/12 -- BloomReach officially launched today after three years in stealth mode. BloomReach's cloud marketing platform bridges the growing digital discovery divide. The company developed a Web Relevance Engine that continuously analyzes over one billion consumer interactions and one billion web pages daily to surface relevant products and services on any consumer platform and web site, creating a more relevant user experience and driving increases in traffic, customer loyalty and online revenues for BloomReach customers. Founded in 2009 in Mountain View, the company is led by Raj De Datta, CEO and Co-Founder, and Ashutosh (Ashu) Garg, CTO and Co-Founder, with a team made up of some of the brightest minds in machine learning, large scale systems science and search from companies like Google, Cisco and Facebook.
Big data represents a massive challenge for web businesses, as consumers miss out on up to 80%(1) of relevant products and services, which remain unfound due to the volume and volatility of web content, as well as the structure of websites.
According to Forrester Research, Inc.'s August 2010 report, The Future of Search Marketing, authored by Shar Van Boskirk, "The difficulty navigating splintered access to burgeoning content will push consumers to seek in a more direct way. This will force marketers to think about 'search marketing' outside of SEM and SEO. In fact, we think 'search marketing' will become an umbrella term that applies to using any targeted media to help an advertiser get found."
BloomReach reports that only 25% of URLs for all products and services are being visited by consumers, who are increasingly savvy and specific on the details of what they seek. BloomReach is innovating ways for brands to better close the gap between products and consumers, driving 80% incremental traffic to their sites and improving paid search profitability by up to 50%.
"In an ideal world, consumers could go online, and quickly discover exactly what they want, but the reality is, brands have an amazing array of products and services that are almost impossible to find because of the widening gap between content and discovery," said Raj De Datta, CEO and Co-Founder of BloomReach.
At the core of BloomReach's technology is the Web Relevance Engine (WRE), which gathers data on content and anonymous user behavior and interprets this using a machine learning language model. The WRE then adapts websites to capture maximum consumer demand by presenting the most relevant and compelling content and user experience to consumers and platforms. The company also announced today its initial suite of products, including Bloom Search, BloomLift and BloomSocial, all built upon the Web Relevance Engine.
"If you're a large web site trying to sell one thousand items and you place ten products on every page of your site, that's ten octillion possible pages that can be generated to serve the customer. If each product can be described in multiple ways, that becomes ten nonillion possible ways future customers might describe the product," said De Datta. "It is a massive problem and, at this scale, it takes innovative big data technology to connect these products with consumers looking for them."
(1) Ratzan, L. (2006, December 11). Mining the Deep Web: Search strategies that work. Computer World. http://www.computerworld.com/s/article/9005757/Mining_the_Deep_Web_Search_strategies_that_work
BloomReach's cloud marketing platform maximizes our customers' revenues -- attracting unmet demand and creating better user experiences by making the most relevant products and services easier to find.
BloomReach created the Web Relevance Engine (WRE), which analyzes one billion consumer interactions and semantically interprets the products and services on over one billion web pages daily. The WRE dynamically adapts websites to capture existing consumer demand across search, social and advertising channels, driving an average 80% increase in non-branded natural search traffic and significant incremental revenues across their large customer base from the retail, travel and listings industries.
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