The document discusses Nielsen's use of location-based analytics for marketing research. It describes Nielsen's global presence and services. Several case studies are presented, including using satellite imagery to classify rural vs urban areas in Indonesia for survey sampling. Nielsen applied machine learning techniques like k-means clustering to satellite images of Bali, Indonesia to develop an objective rural-urban classifier with high accuracy. This allows them to better stratify and manage large-scale survey fieldwork.

1. SMU
-­‐
SCHOOL
OF
BUSINESS
(SR
2.2)
20
APRIL
2015
Singapore
Data
Science
InnovaEon
Lab/InsEtute
The
Nielsen
Company
(Singapore)
47
ScoQs
Road
#13-­‐00
Goldbell
Towers
Singapore
228233
DATASCIENCE.SG
MEETUP
LOCATION-­‐BASED
ANALYTICS
FOR
MARKETING
RESEARCH
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

2. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
2
OUTLINE
• Brief
overview
of
Nielsen
• Selected
case
studies:
• Eye
in
the
sky
• Large-­‐scale
survey
fieldwork
design
&
management
• Store-­‐matching
using
locaEon
informaEon
• Measuring
exposure
to
outdoor
adverEsing
• Q
&
A
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

3. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
3
Help
our
clients
have
the
most
complete
understanding
of
consumers
worldwide
Our
Mission
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

4. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
4
Nielsen
–
A
Truly
Global
Company
• Founded
in
1923
• Global
footprint
in
>100
countries
around
the
world
• Employs
>34,000
employees
globally
Our
2012
revenue
was
USD$5.4
B
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

5. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
5
THE
LATEST
INDUSTRY
BENCHMARK...
Source:
Global
Market
Research
2014
Report
by
ESOMAR
(European
Society
for
Opinion
&
MarkeEng
Research)
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

6. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
6
Our
clients…
Buy
Watch
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

7. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
7
foresight
on
the
Asian
consumer.
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

8. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
8
Eye
in
the
Sky
Rural-­‐Urban
ClassificaHon
Using
Satellite
Images
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

9. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
9
RES
–
RETAIL
ESTABLISHMENT
SURVEY
Number
of
sales
outlets,
types
of
outlets
(market
size
&
composiEon)
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

10. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
10
SAMPLING
CENSUS
IN
LARGE
COUNTRIES
E.g.
Indonesia
(1.9
million
square
kilometers)
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

11. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
11
• In
RES,
a
target
country
is
‘carved’
up
into
small
manageable
survey
areas
• StraEfied
sampling
used
to
ensure
representaEveness
of
data
collected
• E.g.:
Indonesia
Rural-­‐urban
status
is
an
important
factor
in
the
straEficaEon
process
Problem
Official
info
from
Indonesian
govt
is
not
current,
and
important
info
may
be
missing/unavailable
STRATIFIED
RANDOM
SAMPLING
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

12. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
12
Step
1
Turning
to
remote
sensing
(satellite
imagery
–
DigitalGlobe/RapidEye)
to
provide:
scien-fic,
objec-ve
and
con-nuous
monitoring
of
survey
regions
Pilot
area:
Bali
Land
use
report
Step
2
Step
3
Computa-onal
Intelligence
Machine
Learning
Step
4
Rural-­‐Urban
classifier
PROPOSED
METHODOLOGY:
SCIENTIFIC,
OBJECTIVE,
TRACTABLE
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

13. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
13
PILOT
REGION:
BALI,
INDONESIA
• Bali
(smallest
of
34
provinces)
• Organized
into:
Ø Regencies
(Kapubaten)
Ø Districts
(Kecamatan)
Ø Towns/Villages
(645
DESAs
=
Nielsen
survey
areas)
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

14. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
14
RAPIDEYE
IMAGES
OF
BALI,
INDONESIA
Bali
land
use
paQern
dataset:
383
DESAs
used
in
this
study
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

15. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
15
GETTING
THE
GROUND
TRUTH
(RURAL
OR
URBAN)
Crowd
sourcing
approach
• Group
of
human
volunteers
used
• Image
order
randomized
• Majority
voEng
strategy
adopted
to
derive
final
class
label
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

16. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
16
RESULTS
FROM
TWO-­‐CLASS
APPROACH
• Results
from
1000
groupings
of
training
and
hold-­‐out
subsets
at
90%:10%
parEEon
raEo
Results
are
saHsfactory
but
error
rates
sHll
too
high
to
meet
Nielsen’s
standard
for
data
quality
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

17. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
17
APPLYING
K-­‐MEANS
CLUSTERING
TO
BALI
DATASET
Bali
land
use
paQern
dataset:
383
DESAs
used
in
this
study
K-­‐Means
result
concurs
with
visual
observaUons!
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

18. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
18
Sub
sub
urban/Sub-­‐
rural
areas:
-­‐ Region
with
large
open
areas
-­‐ Undeveloped
land/
farmlands
-­‐ Low
building
density
Core
urban
areas:
-­‐ High
building
density
-­‐ LiQle/no
vegetaEon
cover
-­‐ LiQle/no
farmlands
Core
rural
areas:
-­‐ Dense
vegetaEon
-­‐ Natural
lands
Sub
urban
areas:
-­‐ Mix
of
buildings
&
farmlands
-­‐ LiQle/no
dense
vegetaEon
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

19. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
19
RESULTS
FROM
FOUR-­‐CLASS
APPROACH
• Results
from
1000
groupings
of
training
and
hold-­‐out
subsets
at
90%:10%
parEEon
raEo
We
need
to
ascertain
that
the
new
set
of
results
is
significantly
beNer
than
the
one
from
the
two-­‐class
approach
At
1%
test
level,
the
results
from
four-­‐class
approach
are
beQer!
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

20. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
20
CONFIRMATION
OF
RESULTS
USING
NIGHT
IMAGERY
Earth-­‐at-­‐Night
imagery
from
NASA-­‐Earth
observatory
&
NOAA
satellites
Good
fit
between
our
classificaEon
results
and
the
EaN
images
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

21. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
21
TO
RECAP
What
is
urban?
AnalyEcs:
rigour
and
sustainable
SoluEon
must
be
pracEcal
(cost)
?
!
!
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

22. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
22
Large-­‐scale
Survey
Fieldwork
Design
&
Management
Nielsen
Singapore
Data
Science
InnovaUon
Lab/InsUtute
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

23. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
23
WHAT
IS
REQUIRED...
Survey:
LisEng
of
32k
respondents
over
a
period
of
12
months
(Jul14
–
May15)
LisEng
released
by
Client:
Phase
1
Phase
2
Phase
3
Phase
4
~32K
(lisEng)
10,500
10,500
7,000
3,500
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

24. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
24
CHALLENGES
(1) Client’s
requirement:
Similar
distribuEon
of
lisEngs
across
phases
Nielsen:
Task
allocaEon
(Field
work
efficiencies
+
ProducEvity)
=>
reduced
cost
(2) Client
provided
address
&
postal
code
for
lisEngs
(with
name,
age,
race,
gender)
Nielsen:
Manual
sorEng
and
grouping
of
addresses
(32k
respondents)
require
weeks
• Time
consuming
to
check
addresses
manually
• Even
more
Eme
to
group
addresses
to
ensure
even
distribuEon
• No
classificaEon
of
dwelling
type
(public
vs.
private)
• Private
housing
has
restricted
access
(condo
names
not
provided
by
client)
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

25. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
25
OBTAINING
THE
LOCATION
INFORMATION
TranslaUng
postal
codes
to
geocodes
(geo-­‐coordinates)
Changi
Airport
Paya
Lebar
Airbase,
Industrial
land
Nature
reserve,
Central
Catchment
Area
Jurong
Industrial
Estate
Tengah
Airbase,
Agricultural
land
Seletar
Airport
Black:
Public
housing
Blue:
Private
housing
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

26. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
26
EVEN
DISTRIBUTION
(GROUPING
BY
POSTAL
REGIONS)
Singapore
is
organized
into
postal
regions
• SG
postal
code
has
6
digits
• First
2
digits
denote
postal
region
• Each
building
in
postal
region
is
assigned
a
number
(last
4
digits)
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

27. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
27
LOCAL
CLUSTERING
WITHIN
EACH
POSTAL
REGION
Clustering
is
applied
to
group
locaUons
by
proximity
• Same
methodology
applied
for
both
public
and
private
dwellings
Yishun
(76)
Woodlands/Sembawang
(73)
Marsiling/Admiralty
(75)
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

28. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
28
FINAL
SAMPLE
DISTRIBUTION
BY
PHASES
Local
grouping
strategy
ensures:
• LocaEons
closed
to
one
another
are
visited
in
the
same
phase
• Methodology
is
fast
(clustering
<
5
mins)
• Manual
adjustment
can
be
used
to
fine-­‐tune
results
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

29. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
29
MAP
OF
INTERVIEWER
AND
RESPONDENT
LOCATIONS
FOR
SELECTED
SUBGROUP
–
PSO
RESULT
ILLUSTRATION
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

30. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
30
MAP
OF
INTERVIEWER
AND
RESPONDENT
LOCATIONS
FOR
SELECTED
SUBGROUP
–
PSO
RESULT
ILLUSTRATION
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

31. USING
GEOCODING
TO
MATCH
TWO
LISTS
OF
STORES
31
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

32. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
32
Name
of
Store
Store
Address
Name
of
Store
Store
Address
Key
observaEons:
• May
have
similar
names
among
store
list
• Address
formats
are
non-­‐standardised
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

33. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
33
• Geocode
List
A
and
B
addresses
using
Google
API
• Plot
standardized
Geo-­‐coordinates
for
visual
view
of
overlaps
• Perform
matching
based
on
pairwise
distance
and
store
name
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

34. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
34
USEFUL
PYTHON
PACKAGES
• geopy:
easy
to
geocode/reverse
geocode
through
various
geocoder
APIs,
and
to
compute
geographical
distances
• python-­‐levenshtein:
Levenshtein
funcEon
produces
a
metric
for
fuzzy
string
matching
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

35. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
35
Scale:
1
:
10e6
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

36. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
36
Scale:
1
:
50’000
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

37. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
37
QUESTION:
HOW
CAN
WE
OBJECTIVELY
MEASURE
EXPOSURE
TO
OUTDOOR
ADVERTISING?
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

38. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
38
IN
TODAY’S
MEDIA
ENVIRONMENT,
THE
EXPOSURES
TO
A
MESSAGE
PROVIDED
BY
OUTDOOR
ADVERTISING
ARE
MORE
VALUABLE
THAN
EVER.
BECAUSE
IT
IS
INCREASINGLY
DIFFICULT
TO
GET
MESSAGES
NOTICED
AND/OR
REMEMBERED,
THE
UNCLUTTERED
ENVIRONMENT
IN
WHICH
OUTDOOR
ADS
ARE
SEEN
(OFTEN
WITH
HIGH
FREQUENCY)
HELPS
TO
OVERCOME
PROBLEMS
OF
MEDIA
FRAGMENTATION
AND
SELECTIVE
PERCEPTION.
-­‐-­‐-­‐
C.R.
Taylor
(2006)
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

39. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
39
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

40. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
40
MEASURING
EXPOSURE
TO
OUTDOOR
ADVERTISING
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

41. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
41
WE’RE
USED
TO
THE
IDEA
OF
ROUTE
PLANNING…
…paths
possible
if
enough
digital
breadcrumbs
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

42. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
42
HOW
TO
FIND
WHEN
A
PERSON
GOES
PAST
A
BILLBOARD?
• Looking
into
Google
Maps
API
for
Work
and
Google
DirecEons
(23
waypoints
allowed)
• Inside
a
Python
program
pass
a
request
like:
hQps://maps.googleapis.com/maps/api/direcEons/json?origin=%221%20marnham
%20street,%20brisbane,%20australia%22&desEnaEon=%22116%20daw%20street,
%20brisbane,%20australia%22
• Returns
a
JSON
object,
with
the
(approximate)
paths
as
polylines:
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

43. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
43
HOW
TO
ENCODE/DECODE
THE
POLYLINE?
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

44. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
44
USE
A
GIS:
SEE
WHERE
TRAVEL
LINES
INTERCEPT
BUFFERS…
…automate
using
Python
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

45. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
45
WHAT
OTHER
POSSIBLE
DATA
SOURCES
COULD
THERE
BE?
N
ielsen
Singapore
D
ata
Science
Innovation
Lab

46. Copyright
©2013
The
Nielsen
Company.
ConfidenEal
and
proprietary.
46
QUESTIONS?
THANK
YOU!
Tim.Banks@nielsen.com
Xiaoyu.Lin@nielsen.com
WhyeLoon.Tung@nielsen.com
Chong.Lim@nielsen.com
N
ielsen
Singapore
D
ata
Science
Innovation
Lab