Summary:

Last summer, Yahoo’s investments in big data brought us Hadoop startup Hortonworks, and now those same investments brought us predictive-marketing startup InsightsOne. The company, founded by the team responsible for building Yahoo’s consumer analytics platform, launched on Thursday with $4.3 million in Series A funding.

Architecture

Last summer, Yahoo’s investments in big data brought us Hadoop startup Hortonworks, and now those same investments have brought us predictive-marketing startup InsightsOne. The company, which was founded by the team responsible for building Yahoo’s consumer analytics platform, launched on Thursday along with $4.3 million in Series A funding from Norwest Venture Partners and, according to InsightsOne’s press release, “Gaurav Garg, private investor and Special Limited Partner, Sequoia Capital; Zod Nazem, Former CTO of Yahoo!, and Peter Wagner, Founder/Partner at Alpha Venturi and former general partner at Accel Partners.”

Essentially, the InsightsOne platform processes lots of web data in real time, analyzes it against structured data sets, and figures out which consumers really want to see which offers and when. And it does it as a cloud service, so customers don’t have to build their own big data systems for marketing workloads.

Here’s how InsightsOne describes its technological underpinnings:

InsightsOne has built a unique predictive analytics infrastructure on top of a massively scalable distributed processing foundation based on open-source Hadoop and an in-memory real-time processor.

Our predictive analytics infrastructure enables precision targeting through micro-segmentation and fine-grained marketing analytics that are beyond the capability of traditional technologies based on RDBMSs and statistical tools. It brings together capabilities for machine learning, real-time processing, handling semi-structured data such as tweets, searches and reviews, as well as new structured data types such as graphs and sequences.

 

Targeted advertising and marketing, of course, is already a huge use for big data techniques. Ad-placement companies are building out their own systems to analyze consumer data for better ad targeting, while other cloud-based startups, such as BloomReach, are trying to take the guesswork out of figuring out what content consumers really want to see on commercial web sites with pure SaaS offerings. Sure, ad targeting is getting a bad name as the spotlight shines on web privacy, but until something major changes, it is how web companies pay the bills.

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