improving data insights and user experience with mobile devices

© GfK 2016

Beyond the Survey: Improving Data Insights and User Experience with

Mobile Devices

Patricia Graham and Gavin Lew GfK Custom Research

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Introduction

• Reliance on surveys to find ‘why’ • Finding ‘what’ without asking • Linkages to behavior and attitudes passive and active • Enter the role of the mobile device to obtain holistic info • Two case studies that advance understanding

– Survey + Passive digital metering in the FL Presidential primary – Multi-media data capture

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Method Case Study #1

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Method Case Study # 1: Overview • Associated Press and GfK are testing

online administration of surveys to predict election outcomes, using probability-based sample from GfK’s online KnowledgePanel®

• Most recent test was in Florida during the Presidential Primary among N=1,860 KnowledgePanel members.

• Of the respondents surveyed, we also had 64 people’s passively captured digital behavior beginning January 2016 and an array of profile data including party ID.

• Merge the two data sets; illustrate digital consumption by party ID by attitudes.

• KnowledgePanel English speaking adult members, with mobile devices, used to go to the Internet, give permission for digital tracking.

• Sample frame with Active Member definition applied.

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A: Smartphone B: Tablet C: Windows PC

or Laptop

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Method: Mobile Passive Metering An App must be downloaded for Android and iOS. Exact installation and uninstallation process depends on the operating system.

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Method: Android – Installation 2

Download of the App via Google Play Store

Download link and PIN code via text message.

Download our app via Google Play Store

Accept permissions and download.

Open the App.

Typically incent for consent, app install and some period of

initial participation and monthly

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How? Where & when? What? Who?

Method: Data from Passive Measurement

Time • Local Time • UTC time • Durations for App

and URL usage

Structural Information • Socio demographics

from the respective panel

• Profiling Info

Attitudinal Insights • Possibility to survey

people on the mobile device triggered by time

Apps & Browser • Application Usage • Browser URL Request • Browser Search

Request • Website category/ Search

topics • Time spent • Website visit frequency • Website / search visit

sequence/navigation • Web page topics (within

same site)

Device • Distinguishing

Smartphones and Tablets

• Model • Manufacturer • Operating System • Divide Identifier to

match with external data sources

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Results Case Study #1

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Viewing of political URLs did not increase as Election Day neared and a sliver of all activity

Comparing URL Views Not Political vs. Political

1,659 Likely Political URLs Viewed

136,466

Not Likely Political URLs Viewed 5,683

16,718 15,069

17,942 19,617

8,315

13,119

10,346

20,625

9,032

17 204 165 125 157 102 280 121 340 148 0

5000

10000

15000

20000

25000

1/1 - 1/3 1/4 -1/10

1/11 -1/17

1/18 -1/24

1/25 -1/31

2/1 - 2/7 2/8 -2/14

2/15 -2/21

2/22 -2/28

2/29 -3/6

Not Likely PoliticalLikely Political

URL Views Week by Week

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Spikes in political URL views propelled more by registered Republican likely voters than their Democratic counterparts

17

204

165

125

157

102

280

121

340

148

4

91

19 29

31

58

209

78

216

84

2

34

67

20

42

17

49

22

48

20

0

50

100

150

200

250

300

350

1/1 - 1/3 1/4 - 1/10 1/11 - 1/17 1/18 - 1/24 1/25 - 1/31 2/1 - 2/7 2/8 - 2/14 2/15 - 2/21 2/22 - 2/28 2/29 - 3/6

Likely Political

Likely Political Among Registered GOP LVs

Likely Political Among Registered Democratic LVs

URL Views Over Time by Party Registration and Vote Likelihood

Ability to survey by behavior

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Political URL views by party registration

Likely Voters who are Registered Republicans Likely Voters who are Registered Democrats

819 or 4% of 22,162 URLs

Viewed Contain Political Content

81 or 10% out of 819 Political URLs Contain Republican

Keywords (48 of 819 contain Democratic keywords)

51% 2%

Of the 81 URLs with Republican Keywords

contain Trump contain Cruz contain Rubio

12%

321 or 1% of 50,658 URLs

Viewed Contain Political Content

Democrats Viewed More

URLs Containing GOP Keywords than Democratic (110 versus 69 out of 321)

Of the 69 URLs with Democratic Keywords

29%

contain Clinton contain Sanders

25%

21%

34%

45%

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Results: Generally speaking, would you say things in this country are heading in the right or wrong direction

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N of URLs % Avg.Seconds N of URLs % Avg. Seconds

Republican 2,851 5.9 29.87 23 7.1 18.39Democrat 38,211 79.7 60.75 260 80.0 71.71Not affiliated/Not sure/Other 6,883 14.4 43.99 42 12.9 76.34Total 47,945 100.0 57.13 325 100.0 70.84Republican 24,978 34.4 37.84 828 75.3 30.06Democrat 33,932 46.7 56.01 227 20.7 102.64Not affiliated/Not sure/Other 13,690 18.9 62.38 44 4.0 60.79Total 72,600 100.0 51.03 1,099 100.0 46.45

Wrong Track

Country is on Party ID

Total Internet Usage Political Content

Right Track

Illustrative small N

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Conclusions / Discussions Case Study #1

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Data Integration is now adding holistic views while lessening research participant burden

REFERENCE LAYER A core panel or sample source and integration platform that serves as a standalone and /or a calibration tool, as link between various data sources and for data enrichment of external and internal data sources

DATA SOURCES Proprietary, government and other third party data

HOLISTIC DATA AND INSIGHTS Defined by the research needs

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Method Case Study #2

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Method Case #2: Multi-platform Video Capture Record experiences. Imagine the value to HealthCare.gov!

iPhone, iPad, Android, Kindle, OSX, Windows

Ask a selection

of interview questions, conduct video surveys or

present tasks

Record screen, front-

facing camera, mic & all touches/

clicks

Gather

reactions to web pages, videos, prototypes, concept

sketches, ads

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Opportunity: Measure real excitement and interpret response using neuroscience coding.

Showcasing spontaneity

Reflecting authentic, real-time reactions

Capturing verbal and

facial reactions

Method: Because Conversations Matter

Moving from the traditional world of multi-point scales to two-way, unstructured conversation with emotion & authenticity

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Results: Applying In-store mobile shop-a- long techniques to Academic Research

In the moment, unmoderated insights into digital and in-store path to purchase

Using a unique mobile platform which captures the genuine in-store shopper experience through: Video of what they see Voice over of what they are thinking In-the-moment decision drivers Digital behavior and influences

Core Benefits Lower costs Captures multi-platform usage Faster start-up & reporting Less intrusive, more authentic Analysis of video responses Executive highlight reel

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Conclusion: Human coding & sentiment analysis add value and increase positive user experience

Sentiment analysis by the moment

Human coding ‘sound bites’

allows for quant analysis &

focused highlight reels

Skip to specific video

segments

improving data insights and user experience with mobile devices

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