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The Big Opportunity

The Big Opportunity. Audience Research Meets Big Data. What exactly is Big Data?. The Big Data Revolution. Big Data Strengths. Cost. Long tail. Speed. Passive. Granular. Data overlays. Single Source: Big Data a step closer to the Holy Grail. Why are we doing this?.

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The Big Opportunity

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  1. The Big Opportunity Audience Research Meets Big Data

  2. What exactly is Big Data?

  3. The Big Data Revolution

  4. Big Data Strengths Cost Long tail Speed Passive Granular Data overlays

  5. Single Source: Big Data a step closer to the Holy Grail Why are we doing this?

  6. Safety in (Big)Numbers? • Key variables: • Robust sample size • Balanced, representative sample of the universe • High response rate • Quality Control • A balanced, controlled sample of 1000 individuals with a high response rate will always be more representative than 1,000,000+ customers drawn from an imbalanced, self-selecting or partial sample.

  7. Industry Surveys Strengths Transparency Data availability Individual level demographics Balanced rep. samples Trading currency

  8. Industry Surveys Strengths Coverage of Whole market Transparency Data availability Individual level demographics Balanced rep. samples Trading currency

  9. What does Big Data represent? • Because a data set is representative of something does not mean it can be assumed to represent everything. • However just because it doesn’t cover everything does not mean a data set cannot be representative of something.

  10. Consumer-centric Print Radio Mobile Outdoor Online Social Media WOM

  11. Media-centric Source-centric

  12. Big Data & Industry Surveys

  13. The research department of the future?

  14. The Big Debate “Out with every theory of human behavior, from linguistics to sociology. Forget taxonomy, ontology, and psychology. Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves… There's no reason to cling to our old ways. It’s time to ask: What can science learn from Google? " Chris Anderson…wrote in 2008 that the sheer volume of data would obviate the need for theory, and even the scientific method….[T]heseviews are badly mistaken. The numbers have no way of speaking for themselves. We speak for them. We imbue them with meaning… Data-driven prediction can succeed— and they can fail. It is when we deny our role in the process that the odds of failure rise Nate Silver The Signal & The Noise 2012 Chris Anderson Wired 2008

  15. From creators to curators… OrfeoOrfei; The Cook William Sidney Mount: Long Island Farner ..from farmers to chefs?

  16. Askingthe right questions….

  17. The Big Opportunity Audience Research Meets Big Data

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