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The Realtime Commerce Revolution

Big data analytics goes realtime

Over the next few years, the "realtime commerce" space is set to experience phenomenal growth. Companies such as One Kings Lane, Groupon, LivingSocial, Ideeli and others are developing a whole set of new retail business models. Others such as Amazon and Netflix are developing ever more powerful recommendation engines, and a huge number of companies are looking to develop more accurate models for personalization and targeted advertising. A new "realtime commerce" revolution is underway that will be as profound a shift for the business world as the eCommerce revolution of the 1990s.

To be successful in realtime commerce, companies will have to put in place a whole raft of new capabilities, many or most of which will require, and be powered by, new realtime big data analytics platforms. The winners in data-driven realtime commerce will be those that can best handle some or all of the following challenges, continuously, in realtime:

  • track social, mobile and local data
  • support smart group buying, flash sales, auctions
  • generate smart personalized advertising, marketing and recommendation
  • track and manage brand and product sentiment
  • optimize dynamic pricing
  • handle payments and fraud detection at scale
  • monitor web analytics, customer support, fulfillment, distribution, IT

Just last week, speaking at the Web2.0 Summit, Doug Mack, CEO of One Kings Lane, pointed out that big data tools are essential, but they have to be realtime, and aimed at ordinary business users and other "big data consumers", rather than at experienced programmers. At Cloudscale we totally agree. Realtime commerce will be a major killer app for our next-gen realtime big data analytics platform.

More Stories By Bill McColl

Bill McColl left Oxford University to found Cloudscale. At Oxford he was Professor of Computer Science, Head of the Parallel Computing Research Center, and Chairman of the Computer Science Faculty. Along with Les Valiant of Harvard, he developed the BSP approach to parallel programming. He has led research, product, and business teams, in a number of areas: massively parallel algorithms and architectures, parallel programming languages and tools, datacenter virtualization, realtime stream processing, big data analytics, and cloud computing. He lives in Palo Alto, CA.

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