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© GfK 2013 | April 2013 | How can we make Big Data Smart? 1
FROM BIG DATA TO SMART DATA: LEVERAGING THE VALUE OF BIG DATA THROUGH CONSUMER INSIGHT
Colin Strong, GfK
Internet World23rd April 2013
© GfK 2013 | April 2013 | How can we make Big Data Smart? 2
Big Data vs. Market Research
Commercial Big Data Market research
What consumers do What consumers think (and do)
Census Sample
Real time Fixed point(s)
Facilitates customer experience / prediction Wide breadth of consumer issues addressed
A-theoretical deductive analysis Analysis built around explicit and implicit consumer frameworks
Unstructured, noisy data Structured, clean data
What Why (plus what)
Breadth Depth
INTRODUCTION
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Agenda:
► Understanding data► Provenance► Providing context► Reading data
► Market research as data aggregators
► Integrating Big Data and Market Research
► Application of MR techniques to Big Data
► Small data
► A new model
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Data [do] not just exist, they have to be generated”
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Lev Manovitch
UNDERSTANDING DATA
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Data ProvenanceTwitter: Analysis of Twitter data from Hurricane Sandy
UNDERSTANDING DATA
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Data Provenance:Twitter: StreetBump
UNDERSTANDING DATA
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Data context:The pitfalls of false positives
Most published research findings are falseJohn Ioannidis
Our predictions may be more prone to failure in the era of Big DataNate Silver
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UNDERSTANDING DATA
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Data context:The need to think Bayesian
► Take into account the context through prior probability
► Consider for level of false positives
► Probabilistic outcomes
► Integrate multiple data sources
UNDERSTANDING DATA
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Reading data:Cognitive biases
UNDERSTANDING DATA
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What’s the opportunity?
The present time is a very special time in the history of social science
because we are witnessing a dramatic transformation in our ability to observe and understand human
behaviour.
Duncan Watts, Microsoft
Disciplines are revolutionized by the development of novel tools: the telescope
for astronomers, the microscope for biologists, the particle accelerator for
physicists, and brain imaging for cognitive psychologists. [Big Data is] a high-powered lens into the details of human behavior and
social interaction that may prove to be equally transformative.
Scott Golder
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MR – the new smart aggregators:Network Intelligence Solutions
Purchase
Media Exposure
Life Style
Socio-Demo
Users data are matched and enriched withGfK panel information
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And fused into the whole users database:BIG DATA ANALYSIS
3
Activity
ContextUser
Partner mobile operators transfer anonymised, real-time IP traffic to measure
activity across all mobile experiences
1
DATA AGGREGATION
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► Mobile customers leave a footprint of where they are and where they have been.
► Once anonymised and aggregated, it provides a new and powerful hour by hour insight into people’s movements and behaviour.
► Understand resident, worker and ad-hoc visitor profiles in any location
► Understand behaviour by hour, day, week, month
► Compare and contrast profiles of two or more areas
► Analyse people catchment areas and travel from/to zones to refine targeting
► Understand the loyalty factor of any given location
MR – the new smart aggregators Smart Steps: Geolocation data
DATA AGGREGATION
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Financial sector case study:Integrating survey data with Big Data
INTEGRATING BIG DATA & MR
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Telecoms sector case study:Integrating survey data with Big Data
INTEGRATING BIG DATA & MR
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Using consumer insights on Big DataUnderstanding patterns of online behaviour
APPLICATION OF MR TECHNIQUES TO BIG DATA
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Current research: ‘Social networks’
Big Data allows us to start exploring relationships between individuals
Allows us to start exploring different types of real-life social networks that have proved elusive
Big Data provide us with tools that help us to understand the way in which these work
Understand impact of social effects on consumer behaviour
APPLICATION OF MR TECHNIQUES TO BIG DATA
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Exploring the potential for a fundamental shift
Quantified Self movement may be precursor of a shift to wider ‘intention economy’ The individual becomes the point which manages their own personal data Consumers use Personal Data Stores to interface with brands
SMALL DATA
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The emergence of Smart Data
Discipline Individual Segment Social Cultural
Category Psychology Social psychology
Sociology Anthropology
Relevant areas of study
PersonalityBehavioural economics
Social identity Network analytics
Visual /linguistic analytics
Emerging disciplines
Cyber-psychology
Computational sociology Culturomics
A NEW MODEL
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Numbers have no way of speaking for themselves. We speak for them. We
imbue them with meaning.
Nate Silver, The Signal and theNoise: the art & science of prediction
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A NEW MODEL
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THANK YOU
To read more on this topic, download GfK’s Smart Data Manifesto.
@Colinstrong