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Presentation to BIG conference from May 2012
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Big Dataopportunities forMarket Research
Q. How big
is Big Data ?
Byte B 100 1Kilobyte KB 103 1,000Megabyte MB 106 1,000,000Gigabyte GB 109 1,000,000,000Terabyte TB 1012 1,000,000,000,000Petabyte PB 1015 1,000,000,000,000,000Exabyte EB 1018 1,000,000,000,000,000,000
Computer Science 101
A. Bigger than Shakespeare?
t1B
x 1000 =
1 KB
x 1000 =
1 MB
x 5 =
5 MB
A. Bigger than your pocket?
x 100 =
500 MB
x 2 =
1 GB
x 60 =
60 GB
5 MB
A. Bigger than the known universe?
60GB
1 TB
x 140 =
140TB
x 20 =
A. Bigger than a day at Google?
2.5PB
x 5-10 =
140TB
x 11 =
13PB/year
1.5PB
x 1.5 =
20PB/day
or
A. Bigger than the sum of human knowledge?
x 250 =
All words ever uttered by the human race since the beginning of time
5EB
20PB/day
A. Bigger than the Internet?
x 100 =
All words ever uttered by the human race since the beginning of time
5EB
500EB
All data to flow across the Internet this year
Pause to think…
These were the biggest data sets I could find statistics for
and both would be good raw material for Market Research
if we could find a big enough table to put them in
There is a simpler answer
Q. How big is Big Data?
A. Bigger than we can easily handle
(and usually unstructured)
Why now?
More activities are digital, creating “data exhaust”
More sensor devices creating digital data: “chips with everything”
More connectivity: data can be networked
Storage is cheap and getting cheaper
Big Data means different things
Scientists: new frontiers of knowledge
IT industry: projects > 1 PB
Investors: opportunity for growth
Commerce: efficiency, decision-making
Google: business as usual
Market leaders in commercial Big Data
Data ownership
Data Analytics
Data Storage
Commercial applications for Big Data
Micro-segmentation / mass customisation
Predictive propensity modelling
Digital marketingPricing optimisation
Operational performance improvement
Forecasting
Product improvement / development
The Big Data hypothesis for Market Research
“The availability of large quantities of consumer data
will allow us to generate new and/or lower cost
consumer insights through analysis of that data”
Big Data sets for Consumer Insight
Social media
Web traffic
Transactional
Geodemographic& geolocation
And let’s not forget qual and ethnography
Social media
Blogs
A change in research process and mindset
Controllable sample
Extendable conclusions
Data on real world outcomes
Statistics
Analytics
Actionable insights
Hypothesis-led / inductive
Fact-led /Deductive
Transferable Research skills
Understanding client needs
Asking/framing the right questions
Knowing what to look for
Interpretation
Synthesising insights
And researchers have a grasp of statistical techniques used in data analysis
Pattern recognition
Trend analysis
Classification
Cluster analysis
Regression analysis
Big Data firms want a piece of our action
Google Consumer Surveys
Facebook research
Dunnhumby entered the Honomichl 100
Nectar are launching an online panel
Big Data tells us what, but
not why
How can Researchers respond?
1) Find a friendly data scientist
2) Get involved: understand available data sets
3) Talk to clients: what data? what needs?
4) Get creative: how could the data meet client needs?
5) Experiment (with your friendly data scientist)
6) Complement data with traditional research
Success for Market Research in Big Data =
ResearcherData
scientistTechnology
+ x
No-one is doing this well yet:
there is an open goal for whoever gets it right