What does the phrase "big data" mean to Marketing?

The phrase big data doesn't mean too much to most marketing departments and marketers. They are more likely to understand data mining or marketing analytics. It's still quite a new term in the marketing press and it seems to engage the more analytical marketers, not surprisingly, who are relatively scarce people. Here are a couple of blog articles that I wrote to help marketers understand the importance of big data (and data). ...this one was for ESCP, the business school... http://bit.ly/Ufgiic ...and these ones were for my company... http://bit.ly/PLg6KT http://bit.ly/S9TNi8

I run into this question a lot - not just for marketing - but for other disciplines like Actuarial science , quant trading etc also. Here is my summary. 1.From a perception standpoint for marketing- People use the term Big Data to refer to Marketing Analytics. This is different than from areas like Actuarial science where Math and Analytics have been part of the culture for ages.  Marketing Analytics and its quant focus is still not deeply rooted into most traditional Corporate's. Its history is maybe 10 yrs. Also - because of the pedigree of the new marketing analytics techniques from companies like google/facebook - big data resonates more here than say other terms like  - complex event processing or statistical sciences or grid computing. 2. From a real use case standpoint. "big data" in marketing means two things     a) Ability to microsegment  via the use of Machine Learning technologies. i.e creating 100,000 customer segments and applying a strategy for each segment in an automated fashion. refer to http://en.wikipedia.org/wiki/Next-best-action_marketing here . This is in contrast to the traditional http://en.wikipedia.org/wiki/RFM   techniques which  are point of time and their effectiveness decreases as time goes by. Machine Learning on the other hand keeps on learning via new data getting added on the field incrementally improving the model effectiveness.   b) Cycle time from insight to action. Traditionally , the process of any marketing analytic could take about 3-4 months. This was as a result of the technologies (SAS, SPSS ) and also as a result of the process. IT gives data to Marketing Analysts , Marketing Analysts create statistical models and then model gets integrated into the applications.  Now with Big Data Analytics and Machine Learning - you can startoff with a base clustering model but keep on adding data to the model from the field in realtime improving the model.

Lot of people confuse big data with just big volumes. Its not the case. Big data apart from that has to do with speed or rate/frequency at which data is coming, 700,000 Facebook updates per min; being heterogenous (text, image, video, audio), and coming from different platforms. So its quite unstructured. In fact, if you just have one variable, say, high volume, existing BI tools may suffice. It’s when several characteristics come together big data presents challenges and opportunities. In marketing and sales big data is being perceived as the most powerful insight generating opportunity. You could know so much about customers like the way Amazon and Netflix are doing. Lets also understand that doing big data analytics is not only about IT tools or tech gyan Rather a combination of Brainwork+consulting+stats/maths+IT. The application areas are endless and Knowledgefaber is happy to partner with customers on thing such as say you combine customer CRM data with social graph data, you may be able to identify the “key influencers” (say xxx blogger on smartphones) among your customers and use them for creating awareness about a new product being launched.