Examining how technology-driven data applications have become viable options for ascertaining consumer feedback. Determining the implications for mobile applications for delivering data quality to brands. How to motivate consumers to respond quickly to branded information through channel novelty

1. Towards an Understanding of Smartphones as a Survey Platform Elaine B. Coleman, Ph. D, Resolve Market Research & Dean Wiltse, Thumbspeak

2. Lead Biographies Elaine Is Chief Research Officer and Co-Founder of Resolve Market Research, a leading global research consultancy with unique insight into how technologies and digital media transform consumers and audiences alike. Elaine holds a Ph.D. in Cognitive Science from the University of Toronto and was awarded a McDonnell Post-Doctoral Fellowship which was held at UC Berkeley. Coleman has been an executive of consumer research and product design for over 15 years. Her expertise in designing actionable research has attracted clients from wireless, games, technology, sports marketing and home entertainment. Dean Wiltse is a market visionary who has pioneered multiple game-changing products and services including Mobile Relationship Marketing and Online Communities. Dean is the founder and President of Thumbspeak LLC and was the former CEO of Greenfield Online. ThumbspeakLLC focuses exclusively on leveraging smart phone technology to create a disruptive approach to gathering data for customer feedback and marketing research while encouraging advocacy and building loyalty. After being hired as CEO of Greenfield Online in 2001, he immediately recognized an opportunity to transform the business model. Under Dean’s leadership, Greenfield completed a successful IPO in 2004, a secondary offering later that same year and the purchase of Ciao in 2005, which led to the eventual sale of the company to Microsoft in 2008. In 2005, he was nominated for Ernst & Young’s ‘Entrepreneur of the Year’ award and Research Magazine’s ‘Marketing Industry CEO of the Year’ honor. Dean is the author of – ‘Weapons of Mass Collaboration: How to Use Online Communities to Drive Competitive Advantage’.

3. How does mobile compare?

4. Panel 1 Panel 2 Survey Topic

5. The study was executed via an online and mobile survey from (April 13 – April 28, 2011) among a national US sample of 866 iPhone and Tablet Owners Controlled for: Identical questions and stubs, fieldwork period, gender breakout, median age and age groups, business and personal tablet usage, base sizes with the mobile sample were randomly selected. The margin of error for the full sample is +/- 4%, higher for subgroups.

6. Comparing the Experiences Mobile Online

7. Mode Comparisons…

8. Are you downloading more or fewer apps on your smartphone now that you are using your tablet device? N=366 N=500 Q9: Are you downloading more or fewer apps on your smartphone now that you are using your tablet device? BASE: N=866

9. For the next tablet device you purchase, what size tablet would you most prefer? 348 500 Q5: For the next tablet device you purchase, what size tablet would you most prefer? BASE: N=866

10. Content is now accessible across multiple devices (smartphone, tablet, PC, laptop, TV set, etc.). Which devices do you use to watch your favorite TV and movie programming? 348 500 Q16: Content is now accessible across multiple devices (smartphone, tablet, PC, laptop, TV set, etc.). Which devices do you use to watch your favorite TV and movie programming? Base: N=848

11. Have you noticed any advertising while you are using applications? Do you pay attention to advertisements while using your tablet device? Mobile Platform 366 Online Platform 500 Q14: Do you pay attention to advertisements while using your tablet device? Base: N=866

12. Where do you use your tablet device at work? 348 500 Q7: Where do you use your tablet device at work? Base: N=866

13. Research Operations Comparisons

14. Completion Rates Full Point Full Point

15. Response Rates

16. How can we make the mobile survey platform experience actionable for our clients?

17. Mobile Surveys or Polls But who wants to answer a 40 question survey on their phone? Polls work Great! How can we extract valid and reliable samples from mobile?

18. Innovate on the Sampling Structures That require “Big Data” Managing and analyzing large volumes of data in real-time

19. Close Approximate Match This is John…. This is Jon…. This is Johnny…. Age: 21 Ethnicity: Caucasian Environment: Lives at home Occupation: University Student on a scholarship Online Interests: Avid Pandora User Activity: Sends 50 texts per day Hobbies: Plays video games 2 hours per day Entertainment: Cord Cutter who watches HULU plus on a laptopat least 8+ hours per week Commonalities across all of our Johns

20. I have a survey that is 40 questions long that we plan to distribute via mobile. John 1 City, State Age, Gender, Ethnicity John 2 -Next Approximate Match Online Behaviors Media Consumption Marital Status Occupation John 3 – Next Approximate Match Answers the first module of 10 questions then stops. Answers the second 10 question module then stops. Matching Variables And so forth until the John Group has completed 4 modules of 10 questions

21. Expect all Johns to answer in the same approximate way Aggregated as a cohort group –with little variance. Each individual’s responses are aggregated with others in their cohort and represent a more robust set of opinions of one type respondent.

22. Aggregate Responses John This enables clients to distribute a 25 minute mobile questionnaire with the contextual benefits of a mobile experience. Kari Victor

23. Historically, with every new technology or research method comes an “effect” that needs to be understood separately from its novelty

24. Historical Effects

25. Historical Effects

26. Historical Effects

27. 4 Calls to Action Online Mobile Face to Face Conduct more studies to “cognitively unpack” the Mobile Effect Develop new types of sampling methodologies make mobile actionable for business and product Develop elegant, easy mobile UI’s for end user experiences Think about “Big Data” and develop real-time data processing applications for research

28. Questions Elaine.Coleman@Resolvemr.com Dean@Thumbspeak.com