360i Releases Big Data Road Map
- by Laurie Sullivan @lauriesullivan, December 3, 2012
Ad agencies, brands and technology platform companies have begun to appoint chief data scientists or chief marketing scientists, building out teams with knowledgeable employees in studies related to anthropology and sociology.
Supporting the transition, digital agency 360i will release guidelines Tuesday that offers a road map to guide companies in need of a chief data scientist or principal data lead.
Data helps marketers address a range of marketing opportunities and challenges. For years, Amazon.com tapped into customer data to power its recommendation engine.
Believing that data can transform businesses, companies are spending about $50 billion on advanced big data analytics platforms, according to BMO Capital Markets. But companies need to simplify and know how to use the collected data.
Wayfair's Dave Drollette, who sifts through the data and manages Web research traffic and recent commercial TV tests, says his team builds models and analyzes clickstream data to understand consumer behavior.
The goal to reach potential new customers drives data from inbound links, average order, conversion rates and viewed pages, says Trisha Mack Antonsen, the company's senior manager of social media. "It's an interesting way to see data generated by products, and how our products are merchandised alongside others."
Machine-generated Internet data continues to change digital marketing by identifying new customers, revealing new market opportunities, driving more profitable advertising and measuring the impact of campaigns.
The agency's white paper details the steps brands can follow to put data to work by appointing a chief marketing scientist.
Big data cannot provide the uptick alone, but it does allow marketers to create informed marketing decisions that can outrank competitors and make the company's products more relevant to consumers. Marketing data will continue to expand as more media gets measured through impressions, clicks, visits and social actions.
I've seen some commentators on the net regard BI (business intelligence) as analytic as somehow it is in par with predictive analytics. There's overlap but they are different. BI is mainly deductive (ie, the user makes the intelligent interpretation of the data), but predictive analytics is inductive. The system itself induces knowledge from the data. Also, I see that the term big data is a fashion term now, but methods of analysing big data has been available in the last 15 years or so. The only difference is that we need more computing power to crunch the data faster.
For those interested in big data training to start with, EMC offers an open course on DVD in Big Data Analytics. It might be a good place to start if you're looking just to start understanding what Big Data is and how you can use it.
http://amzn.to/P4DjX7
I generally agree with Sione's comments with one difference. BI is a retrospective view and predictive analytics is a prospective view.
Second, marketers need to remember that many online campaigns are much more successful in conjunction with traditional offline advertising. As a chief data scientist myself, I know that being able to understand cross-media consumption is far more valuable to an organization than knowing how to drill down or model online only.
where can we access the white paper?
White Paper: http://www.360i.com/reports/big-data/