Presentation to BIG conference from May 2012

1. Big Data
opportunities for
Market Research

2. Q. How big
is Big Data ?

3. Computer Science 101
Byte B 100 1
Kilobyte KB103 1,000
Megabyte MB 106 1,000,000
Gigabyte GB 109 1,000,000,000
Terabyte TB 1012 1,000,000,000,000
Petabyte PB 1015 1,000,000,000,000,000
Exabyte EB 1018 1,000,000,000,000,000,000

4. A. Bigger than Shakespeare?
t x 1000 = x 1000 = x5=
1B 1 KB 1 MB 5 MB

5. A. Bigger than your pocket?
5 MB
x 100 = x2= x 60 =
500 MB 1 GB 60 GB

6. A. Bigger than the known universe?
60GB
x 20 = x 140 =
1 TB 140TB

7. A. Bigger than a day at Google?
x 11 = x 1.5 =
140TB 1.5PB 2.5PB
x 5-10 = or
13PB/year 20PB/day

8. A. Bigger than the sum of human
knowledge?
20PB/day
x 250 =
All words ever uttered by the human
race since the beginning of time
5EB

9. A. Bigger than the Internet?
All words ever uttered by the human
race since the beginning of time
5EB
x 100 =
All data to flow across the
Internet this year
500EB

10. 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

11. There is a simpler answer
Q. How big is
Big Data?
A. Bigger than
we can easily
handle
(and usually
unstructured)

12. 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

13. 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

14. Market leaders in commercial Big Data
Data ownership
Data Analytics
Data Storage

15. Commercial applications for Big Data
Micro-segmentation / mass customisation
Predictive propensity modelling
Digital marketing
Pricing optimisation
Operational performance improvement
Forecasting
Product improvement / development

16. 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”

17. Big Data sets for Consumer Insight
Social media
Web traffic
Transactional
Geodemographic
&geolocation

18. And let’s not forget qual and ethnography
Social media
Blogs

19. A change in research process and mindset
Data on real world outcomes
Controllable
sample
Analytics
Statistics
Actionable
insights
Extendable conclusions
Hypothesis-led / Fact-led /
inductive Deductive

20. Transferable Research skills
Understanding client needs
Asking/framing the right questions
Knowing what to look for
Interpretation
Synthesising insights

21. And researchers have a grasp of statistical
techniques used in data analysis
Pattern recognition
Trend analysis
Classification
Cluster analysis
Regression analysis

22. Big Data firms want a piece of our action
Google Consumer
Surveys
Facebook research Big Data tells
us what, but
Dunnhumby entered
the Honomichl 100 not why
Nectar are launching
an online panel

23. 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

24. Success for Market Research in Big Data =
+ x
Data Technology
Researcher scientist

25. No-one is doing this well yet:
there is an open goal for whoever gets it right