By Steven Gittelman, Ph.D. and Elaine Trimarchi
Transcript of By Steven Gittelman, Ph.D. and Elaine Trimarchi
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Global Patterns in Panel Research
BySteven Gittelman, Ph.D.
and Elaine Trimarchi
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Objectives
Compare Global and American panel patterns.
Demonstrate trends in panel evolution.
Illuminate how various problem respondents, through their impact on purchasing data, drive evolutionary changes.
Clarify the issues that now confront the American Panels.
Arrive at workable solutions‐‐‐blending methodologies.
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I can see clearly now! Compared survey results from 12 US Consumer Panels, 1 panel in
each of twenty‐five global markets. 400 completes per source. June 2008 ‐ February 2009.
We are grateful to our research partners for providing sample for the following global (non US) markets.
‐ ‐ 17‐ global panels‐Argentina, Brazil, Czech Republic, Denmark, Finland, France, Germany, Italy, Norway, Poland, Portugal, Russia, Spain, Sweden, Switzerland, UK, Ukraine
Clear Voice Research‐Australia, Canada
‐China, Japan, South Korea, Singapore, Hong Kong, Taiwan
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Methods
Selected demographic quotas (age, income, gender, ethnicity) were used to simulate census.
Median length was 15 minutes.
Questions covered: Technology and the media, Participation in market research, Buyer Behavior, Values and lifestyle, Demographics, Questionnaire Satisfaction.
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Respondent Types Professional Respondents fall into four categories:
• (1) Self report taking on‐line Surveys “practically every day”.
• (2) Self report (open ended) taking over 30 online surveys “in the past month”.
• (3) Multiple panel membership > 5 panels.
• (4) Respondent panel tenure.
Inconsistency: Brand vs. Price, Price vs. Brand, Happy with standard of living vs. unhappy with standard of living.
Failure to follow instructions: Instructed to enter a predetermined answer.
Speeders: Lowest 10% of survey lengths.
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Percent Respondents Doing More than 30 Surveys/Month
Red = US Panels Green = International Panels
0%
5%
10%
15%
20%
25%
30%
35%
40%
Singap
ore
Portugal
Hong K
ong
Switzerl
and
Finlan
d
Czech
Rep
Ukraine
Russia
Brazil
Argen
tina
ChinaS. K
orea
Norway
Denmark
Poland
Taiw
anUS11US10
Sweden
Fran
ceSpainIta
lyGerm
any
Canad
aUS16 UK
Australi
aJa
pan
US12US9US6
US17US14US13US7US18US8
Perc
ent 3
0+ s
urve
ys p
er m
onth
US11=RiverUS10= Social Network
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Percent Respondents Doing Surveys Every Day
RED = US Panels Green = International Panels
0%
10%
20%
30%
40%
50%
60%
Singapore
Portugal
Hong K
ong
Switzerl
and
Finland
Czech
Rep
Ukraine
Russia
Brazil
Argen
tina
China
S. Korea
Norway
Denmar
kPola
ndTaiw
anUS11US10
Sweden
France
Spain Italy
German
yCan
ada
US16 UK Aus
tralia
Japan
US12 US9US6
US17US14US13 US7US18 US8
Perc
ent D
oing
Sur
veys
Dai
ly
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Percent Respondents Enrolled in > 4 Panels
0%
10%
20%
30%
40%
50%
60%
70%
Singap
ore
Portugal
Hong K
ong
Switzerl
and
Finlan
d
Czech
Rep
Ukraine
Russia
Brazil
Argen
tina
ChinaS. K
orea
Norway
Denmark
Poland
Taiw
anUS11US10
Sweden
Fran
ceSpainIta
lyGerm
any
Canad
aUS16 UK
Australi
aJa
pan
US12US9US6
US17US14US13US7US18US8
Enro
lled
in o
ver 5
Pan
els
or M
ore/
mon
th
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Percent Respondents Who had an Inconsistent Brand Over Price Response
0%
2%
4%
6%
8%
10%
12%
14%
16%
Singap
ore
Portugal
Hong K
ong
Switzerl
and
Finlan
d
Czech
Rep
Ukraine
Russia
Brazil
Argen
tina
ChinaS. K
orea
Norway
Denmark
Poland
Taiw
anUS11US10
Sweden
Fran
ceSpainIta
lyGerm
any
Canad
aUS16 UK
Australi
aJa
pan
US12US9US6
US17US14US13US7US18US8
Perc
ent I
ncon
sist
ent o
f Bra
nd o
ver P
rice
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Percent Respondents Who Failed to Follow Instructions by Panel
0%
5%
10%
15%
20%
25%
30%
35%
Singap
ore
Portugal
Hong K
ong
Switzerl
and
Finlan
d
Czech
Rep
Ukraine
Russia
Brazil
Argen
tina
ChinaS. K
orea
Norway
Denmark
Poland
Taiw
anUS11US10
Sweden
Fran
ceSpainIta
lyGerm
any
Canad
aUS16 UK
Australi
aJa
pan
US12US9US6
US17US14US13US7US18US8
Perc
ent W
ho F
aile
d to
Fol
low
Inst
ruct
ions
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Percent Respondents Who are Speeders by Panel
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
Singap
ore
Portugal
Hong K
ong
Switzerl
and
Finlan
d
Czech
Rep
Ukraine
Russia
Brazil
Argen
tina
ChinaS. K
orea
Norway
Denmark
Poland
Taiw
anUS11US10
Sweden
Fran
ceSpainIta
lyGerm
any
Canad
aUS16 UK
Australi
aJa
pan
US12US9US6
US17US14US13US7US18US8
Perc
ent S
peed
ers
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1.3
2.5
6.0 6.04.8
6.3
4.5
1.2 1.1
5.2 5.25.8
2.23.4
6.4
4.4
8.0
0123456789
M3 M4 M5 M6 M7 M8 M9M10M11M12M13M14M15M16M17M18
All Pan
els
Panels
Num
ber o
f Pan
els
Average Panel Membership by Panel in the U.S.
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Impact of Max Panel Age in the U.S. on Sociologic and Buyer Segmentations
0%
5%
10%
15%
20%
25%
30%
35%
40%
0 Months 6 Months 12 Months 18 Months 24 Months
Max Age on Panel
Dev
iatio
n (S
quar
e R
oot o
f the
Su
m o
f Squ
are
Dev
iatio
ns)
Socio Deviation Buyer Deviation
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Max Age on Panel by Panel in the U.S.
0%
20%
40%
60%
80%
100%
M6 M7 M8 M9 M10 M11 M12 M13 M14 M16 M17 M18 GrandTotal
Panel
% o
f Res
pond
ents
0 Months 6 Months 12 Months 18 Months 24 Months
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Social/Psychographic Variation Social opinions and behavior can be expected to drive
purchasing behavior or at least provide a basis for segmenting the market. Consistency of these measurement may likewise be critical.
Variables Groups• Internet Use• Taking Surveys• Having a Passport• Social Characteristics
Measures:• Driving Variables
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Global variation from grand mean of standardized sociographic segments.
-60
-40
-20
0
20
40
60
Social
Netw
ork
Contri
bute O
n Line
Instant
Messa
ging Blog
Share
Pictur
es
Downloa
d Vide
o
On-line C
alend
ar
Games
Onli
ne
Uncon
ventio
nal
Enjoy R
isks
Time o
ver M
oney Mag
Stay Info
rmed
Compu
ters m
akes
Easier
Radio
Speak
Mind
Read S
unday
Newsp
aper
Lower
Std to
Cons
erve
Happy
w/f S
td of L
iving
Good w
ork/l
ife B
alanc
e
Asked
for A
dvice
Resea
rchM
odes
Read N
ewpap
er
Enjoy P
olitic
s
Too M
uch C
once
rn on
Env.
Alcoho
l off T
V
Childr
en A
ds of
f TV TV
No Com
puter
Global
Warming
Passpo
rtSt
anda
rd E
rror
s
High Computer/Stays Informed (40%) Happy with Life/Not Computer (29%) Opinionated/Not Computer (31%)
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Global Average Sociographic Segmentation Distribution
0%
20%
40%
60%
80%
100%
USCan
adaFran
ceGerm
any
Italy
Spain UK Argen
tina
Australi
aBraz
ilChina
Czech
RepDen
markFinlan
dHong Kong
Japan
Norway
PolandPortu
galRuss
iaS. K
oreaSingap
oreSwed
enSwitz
erland
TaiwanUkra
ine
% o
f Res
pond
ents
in S
egm
ent
High Computer/Stays Informed Happy with Life/Not Computer Opinionated/Not Computer
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US Sociographic segment distribution by panel and phone.
0%
20%
40%
60%
80%
100%
US1*US2*US3*US4*US5* US6
US7US8US9US10US11US12US13US14US16US17US18
US Pho
ne*
% o
f Res
pond
ents
in S
egm
ent
High Computer/Stays Informed Happy with Life/Not Computer Opinionated/Not Computer
* EM Algorithm for Missing Data & Logit Model for Segmentation
Social Network
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Variation in Buyer Behavior
Measuring buyer behavior is the objective of most marketing research. And therefore, consistency of those measurement are critical.
Variables• Number of High Tech Items Purchased. • Internet Purchase behavior• Purchasing Opinions
Measures:• Clusters (Segments) • Driving Variables
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Buyer Behavior Segment Profiles
-50
-40
-30
-20
-10
0
10
20
30
40
50
High Tech Purch
ases
Download
Music
Lastes
t Elec
tronic
s
Interne
t Rad
io
Purcha
se O
nline
Techn
ology
Brand ov
er Pric
e
Video Gam
es
Online B
ankin
gTrav
elApp
roval
Quality
Takes
Trips
Impro
ve Home
Passp
ort
Price o
ver B
rand
Shop Around
EMailCred
it
Enviro
nment
Freque
nt Flie
rDom
estic
Use Coupon
sCou
ponsSmoke
Hrs. O
n-line
Informati
onSt
anda
rd E
rror
s
Broad Range/Credit (34%) Price Sensitive Shoppers (18%) Credit/Environment (27%) Domestic/Coupons (21%)
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Distribution of Buyer Behavior Segments by Countries.
0%
20%
40%
60%
80%
100%
USCanad
aFran
ceGerm
any
Italy
Spain UK Arg
entina
Australia
Brazil
ChinaCze
ch R
epDenmark
Finland
Hong Kong
Japa
nNorw
ayPolandPortu
galRussia
S. Kore
aSingap
oreSwed
enSwitz
erland
Taiwan
Ukraine
Perc
ent o
f Pan
el in
Seg
men
ts
Broad Range/Credit Price Sensitive Shoppers Credit/Environment Domestic/Coupons
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US and Global Distribution of Buyer Behavior among Panels
0%
20%
40%
60%
80%
100%
US6US7US8US9US10US11US12US13US14US16US17US18 UKSpain
Germany
FranceIta
lyJapan
Total US Panels
Perc
enta
ge o
f Res
pond
ents
Broad Range/Credit Price Sensitive Shoppers Credit/Environment Domestic/Coupons
Social Network
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-10-8-6-4-202468
10
M11 M3 M4 M10 M2 M16 M15 M1 M9 M12 M7 M13 M5 M14 M6 M17 M8 M18
Stan
dard
Err
ors
Conventional Purlchasers On-liners Low Card OL Banking
97%99%
River SocialNetwork
PointSystem
UK Access Panels
Statistical Panel Profiles Against Buyer Segments
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+/-14.8%
+/-10.8%
+/-12.9% +/-14.9%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
Broad Range/ Credit Price SensitiveShoppers
Credit/ Environment Domestic/ Coupons
Perc
ent o
f Res
pond
ents
Buyer Behavior Segments
Expected Range of Values for a Random 3 Panel Sample Showing 1.281 Standard Errors (20% of being beyond this range) in the
U.S.
+/- Coefficient of variation
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+/-20.8%+/-15% +/-17.1%
0%
10%
20%
30%
40%
50%
60%
High Computer/ StaysInformed
Happy with Life/ NotComputer
Opinionated/ Not Computer
Perc
ent o
f Res
pond
ents
Sociographic Segments
Expected Range of Values for a Random 3 Panel Sample Showing 1.281 Standard Errors (20% of being beyond this range) in the
U.S.
+/- Coefficient of Variation
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+/- 22.1%
+/- 18.6% +/- 15.8% +/- 16.4%
0%
10%
20%
30%
40%
50%
60%
Internet Stay Informed Enjoys Politics Concerned
Perc
ent o
f Res
pond
ents
Media Segments
Expected Range of Values for a Random 3 Panel Sample Showing 1.281 Standard Errors (20% of being beyond this range) in the
U.S.
+/- Coefficient of Variation
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Optimization Profile
0.00
0.01
0.02
0.03
0.04
0.050.06
0.07
RM
S Er
ror
0%20%
40%60%
80%100%0% 20% 40% 60% 80% 100%
Percent of M8
Percent of M17
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OptimizationsPanels Optimum Average
Expected (1 SE) Inherent (1 SE)
M8 24% 33%M17 26% 33%M12 50% 34%
Root Mean Square Error 0.40% 2.36% 8.31% 2.45%
Panels Optimum AverageExpected (1 SE) Inherent (1 SE)
M8 0% 33%M13 91% 33%M16 9% 34%
Root Mean Square Error 3.6% 7.8% 8.3% 2.4%
Panels Optimum AverageExpected (1 SE) Inherent (1 SE)
M10 8% 33%M13 66% 33%M16 27% 34%
Root Mean Square Error 1.6% 12.3% 8.3% 2.4%
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Summary Panel ageing in the U.S. has led to degradation.
Professional Respondents and other problem respondent types appear to greatly affect the reliability of panel research results.
Sample sources around the world are beginning an ageing cycle. There is still time to document and stabilize the situation.
Reliability and consistency of samples can be improved by combinations of panels (Blending Methodologies).
Optimization models improve blending methods, data is needed within each market to create the baselines so that these models can be employed.
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Thank youSteven Gittelman, Ph.D.
and Elaine Trimarchi 200 Carleton Avenue
East Islip, New York 117301‐631‐277‐7000