September - 2013 - issue > View Point
Big Data and Machine Learning based Marketing Analytics
Nisheeth Ranjan
Co-founder & CTO-BrightFunnel
Big Data analytics company which connects the dots between marketing data silos to generate predictive, actionable revenue insights.
The world generated 1.8 trillion gigabytes (approx. 1.8 x 1018 bytes) of data in 2011. Thats more bytes than the number of seconds since the universe started with the Big Bang (approx. 4.32 x 1017 seconds). Even more staggering, this data store is doubling every two years. New tools (Hadoop, HBase, to name a few.), skills (data science), and architectures (MapReduce, in-memory databases, etc.) are developing to store, manage, and analyze this ever expanding tidal wave of data.
Big data is "high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization" as defined by Gartner. Any company that has access to large amounts of data in a variety of formats growing quickly can use the Big Data toolset to generate actionable insights that increase revenue, cut costs and/or increase customer satisfaction. For example, AirBnB identifies its most valuable users by loading its social media data into a Hadoop cluster and figuring out which users have the most influence on their social networks for recommending AirBnB and generating revenue. It targets marketing initiatives at these influencers to maximize revenue.
Big Data applications often use Machine Learning techniques to create predictive models from analysis of past data.
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