A timeline of BloomReach’s history
In 2008, former Google scientist Ashutosh Garg and Raj De Datta, a successful Silicon Valley entrepreneur, had an idea: Why not help businesses better benefit from their web content by making sure each visitor was greeted with relevant content based on that particular visitor’s unique intent?
Not only would the businesses be more effective, but consumers would have better digital experiences on every site. Garg and De Datta believed that if they could bring massive amounts of data, world-class algorithms and continuous learning to every website, they would create the relevant web.
Their vision was a personalization platform that would bridge the gap between a visitor’s intent and a site’s content across devices and channels. Together, Garg and De Datta built the BloomReach Web Relevance Engine, a powerful machine-learning system that made the right products and services more visible to the right customers by surfacing relevant products and information that were once lost in the deep web.
The result is a suite of marketing and merchandising applications that benefit the entire digital ecosystem. BloomReach’s tools expose high-quality content that provides a more relevant and personalized experience for consumers and more profit for the businesses serving them.
The results are big data marketing applications that benefit the whole ecosystem. They expose high-quality content delivering a more relevant experience for consumers and more profit for businesses.