imagine the possibilities - assembling modular mobile surveys to create complete datasets - ssi...
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Presented by Edward Paul Johnson, Director of Analytics ,SSI Christi Walters, Principal, Gongos at Market Research in the Mobile World North America 17 - 18 July 2013, Minneapolis, USA This event is proudly organised by Merlien Institute Check out our upcoming events by visiting http://www.mrmw.netTRANSCRIPT
JULY 16 - 18, 2013, Minneapolis, USA
WWW.MRMW.NET
The original, premier event for the Mobile Marketing Research Industry
WWW.MRMW.NET
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Assembling Modular Mobile Surveys to Create Complete Datasets
Market Research in the Mobile World July 17, 2013
SSI Confiden*al © 2013 Survey Sampling Interna6onal
Edward Paul Johnson Director of Analy6cs SSI Chris1 Walters Principal Gongos Research
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Current Environment
Researcher to Respondent Rela1onship
VS.
respondents researchers
I want to know what you think about soH drinks
Great! Here’s a 30-‐minute survey…
Sure I have some 6me to help you out
Wait, what does my hair color have
to do with beverages?
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Problem
New Mobile World
Consumers want control
Where. When. How long?
How can we give them what they want?
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Ques6ons
Can we modularize? → Within-‐respondent
→ Between-‐respondent
Can we fuse the data?
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Key Hypotheses
Willingness to par1cipate in “long” surveys on mobile devices will be increased by offering incremental incen1ves 2 There are minimal data effects on modularizing surveys on smartphones
3 Data fusion techniques allow advanced analysis despite missing data
4 Bivariate analysis is possible with data fusion techniques
5 AStude and behavioral hooks will prove superior to demographic hooks
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Modularizing surveys will create a beVer, more enjoyable experience for the respondent 1
This is the correct image.
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Methods
Ques1onnaire Design
Full Ques1onnaire
Sec1on A
Sec1on B
Sec1on C
We started with a full ques1onnaire
with three sec1ons
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Methods
Ques1onnaire Design
Full Ques1onnaire
Hook
Que
s6on
s
Sec1on C
Sec1on B
Sec1on A
Pieces from
each sec1on were removed as
hook ques1ons
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Methods
Ques1onnaire Design
Full Ques1onnaire
Hook
Que
s6on
s
The rest of the ques1onnaire was
split into three modules
Mod
ule
Mod
ule
Mod
ule
Sec1on C
Sec1on B
Sec1on A
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Methods
Ques1onnaire Design
Respondents were randomly
assigned to a star1ng module.
Respondents always saw a specific set of
‘hook’ ques1ons within their first
module.
Respondent Survey
Hook Ques1ons
1st Module
2nd Module
3rd Module
Choice to con1nue
Choice to con1nue
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Need to Assemble the Pieces
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Assembly Method
Hot Decking Imputa1on
• Finds similar respondents • Based on similari6es to link
respondents together • Drops unlinked data
— Only actual responses
Respondent Matching
• Es6mates missing data • Based on the similari6es to
the remaining sample • Includes all respondents
— actual responses and — es6mated responses
SSI Confiden*al © 2013 Survey Sampling Interna6onal
Results
H1 – enjoyable experience
Average Difference in Sa6sfac6on Ra6ngs Sa6sfac6on -‐0.06 -‐0.03 -‐0.02 -‐0.14
Bad Data Checks No Straightlining 84.0% 81.7% 82.3% 87.0%
Failed Grid 1 Instruc6ons 17.6% 13.9% 12.8% 16.9%
Failed Grid 2 Instruc6ons 17.3% 18.1% 9.7% 12.7%
Failed Zip Code Match 2.2% 1.6% 3.4% 1.4%
Control [Online Complete]
Control [Mobile Complete]
Test [Mobile Modular]
Test [Online Modular]
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
11% 9% 25%
8% 9% 8%
4% 8%
80% 83% 71% 84%
Abandoned Removed Completes
Results
H2 – willingness to par1cipate
Control [Online Complete]
Control [Mobile Complete]
Test [Mobile Modular]
Test [Online Modular]
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Results
H2 – willingness to add modules
9% 19%
72%
1 Module 2 Modules 3 Modules 1 Module 2 Modules 3 Modules
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Results
H3 -‐ minimal sta1s1cal effects
Compared to Online Control
Online Modular Sta1s1cal:
No discernible differences
Mobile Modular Sta1s1cal:
25% of the ques6ons showed sta6s6cal
differences
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Results
H3 -‐ minimal prac1cal effects
Compared to Online Control
Online Modular Prac1cal:
Findings and resul6ng insights are the same
Mobile Modular Prac1cal:
Resul6ng insights were similar, however, some differences do exist
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Results
H4 – segmen1ng the data
Hot Deck Data Imputa1on
Data Matching Based on AStudes & Behaviors
Online Control
Segmenta1on analysis resulted in a three-‐segment solu1on.
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Results
H4 -‐ checking segment algorithms
When applying the online control algorithm to each data set…
When applying algorithms from each data set to the online control data…
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Results
H4 -‐ segment solu1on results
20% 26% 26%
53% 51% 50%
28% 23% 24%
Segment Sizing Across Techniques
Online Control
Mobile Hot Deck Data Imputa1on
Segment 1
Segment 2
Segment 3
Data Matching Based on AStudes
& Behaviors
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Results
H4 – accuracy of segment assignment
83% 86% 86% 86%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Imputed Matching
Missing Full
Data Matching Based on AStudes & Behaviors
Mobile Hot Deck Data Imputa1on
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Results
H5 – bivariate rela1onships
Hot Deck Imputa1on
Respondent Matching
501 424 17% 20% 0.29 0.22 .24 0.29 .19 0.19
Control Modular No Imputa1on
Sample Size 333 416* % Significant Differences 0.0% 15%
Average Reasons r 0.39 0.31 Average AVribute r 0.30 0.24
Average Reason x AVribute r 0.22 0.20
Distance Correla1on
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Results
H6 -‐ aStudinal vs. demographic s1tching
Online Control
Segment 1
Segment 2
Segment 3
Data Matching Based on AStudes
& Behaviors
20% 19% 26%
53% 55% 50%
28% 25% 24%
Data Matching Based on
Demographics
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Results
H6: aStudinal vs. demographic s1tching
92% 86% 87% 86%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Demos Aetudes
Missing Full
Data Matching Based on AStudes & Behaviors
Data Matching Based on Demographics
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SSI Confiden*al © 2013 Survey Sampling Interna6onal
Conclusions
Allow respondents to choose mode (online vs. mobile vs. mul1modal)
1 Within-‐respondent modulariza1on key to reducing holes in data 2 Advanced analy1cs feasible (i.e. segmenta1on)
3 Both fusion techniques work with unique advantages
4
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WWW.MRMW.NET
TITLE SPONSOR DIAMOND SPONSOR PLATINUM SPONSOR
GOLD SPONSORS
WORKSHOP HOST
SILVER SPONSORS
PREMIERE SPONSOR
NETWORKING EVENING SPONSOR BAG SPONSOR PREMIERE SPONSOR
JULY 16 - 18, 2013, Minneapolis, USA
WWW.MRMW.NET
The original, premier event for the Mobile Marketing Research Industry