Web Survey Bibliography
In 2008, Swisscom developed a new brand positioning and appearance, which has been launched in March. Basis for the new identity was a model of generic emotions or motives, as used in Neuro-sciences nowadays. In order to capture implicit knowledge about brand values, which customers associate with Swisscom and other brands, we started to experiment with reaction time measurement (RTM). Instead of asking customers to use scaled judgements like “how strongly they agree to Swisscom being innovative”, respondents have to use two computer keys to accept or not accept the connection between the words Swisscom and Innovation. The times between displaying the words and the customers’ reaction by pressing the button, are recorded.
Basis for our trials was the Swisscom owned online panel Intervista, which allowed us testing different methods in a cost efficient way. In our first test of RTM, we worked together with a consultancy with good experience in Neuro-psychology. We simply applied their operationalization (a fix set of key words) of the model. In several quality and method checks, we found out, that:
- In general, the RTM provides relevant results.
- However: lengths and complexity of key words have influence on reaction times, and
- too many key words increase complexity of analysis and comprehensibility
Since we wanted to exploit the methods in other research studies, we asked our provider for online surveys to program our own RTM software. The goal behind this was to establish a standardized and fast method for pre testing advertisements especially regarding to brand compliance. This allows early adjustments and thus reduces the risks of lauching a campaign, which transports the wrong image.
In the meantime, the tool has been used many times for pre- and post-tests of ad campaigns, brochures and also after touch point visits of customers.
In the presentation, we will show, how the customers experience the interview, give examples of a pre-test and show, how the results of the study have been used to improve the communication measures according to our new brand values.
onference homepage (abstract)
Web survey bibliography (4086)
- Respondent Processing of Rating Scales and the Scale Direction Effect ; 2016; Caporaso, A.
- The Effects of Pictorial vs. Verbal Examples on Survey Responses ; 2016; Sun, H.; Bertling, J.; Almonte, D.
- Evaluating Grid Questions for 4th Graders; 2016; Maitland, A.
- Mixing Modes: Challenges (and Tradeoffs) of Adapting a Mailed Paper Survey to the Web ; 2016; Wilkinson-Flicker, S.; McPhee, C. B.; Medway, R.; Kaiser, A.; Cutts, K.
- An Examination of How Survey Mode Affect Eligibility, Response and Health Condition Reporting Rates...; 2016; Stern, M. J.; Ghandour, R.
- Investigating Measurement Error through Survey Question Placement ; 2016; Wilson, A.; Wine, J.; Janson, N.; Conzelmann, J.; Peytcheva, E.
- Instructions in Self-administered Survey Questions: Do They Improve Data Quality or Just Make the Questionnaire...; 2016; Redline, C. D.; Zukerberg, A.; Owens, C.; Ho, A.
- Usability Testing within Agile Process; 2016; Holland, T.
- Exploring Why Web Surveys Take Longer to Complete on Smartphones than PCs: Findings from a Within-subjects...; 2016; Antoun, C.; Cernat, A.
- Making Mobile Web Surveys Accessible; 2016; Malakhoff, L.
- Association of Eye Tracking with Other Usability Metrics ; 2016; Olmsted, E. L.
- Cognitive Probing Methods in Usability Testing – Pros and Cons; 2016; Nichols, E. M.
- Grids and Online Surveys: Do More Complex Grids Induce Survey Satisficing? Evidence from the Gallup...; 2016; Wang, Me.; McCutcheon, A. L.
- Assessing the Accuracy of 51 Nonprobability Online Panels and River Samples: A Study of the Advertising...; 2016; Yang,Y.;Callegaro,M.;Yang,Y.;Callegaro,M.;Chin,K.;Yang,Y.;Villar,A.;Callegaro, M.; Chin, K.; Krosnick...
- Calculating Standard Errors for Nonprobability Samples when Matching to Probability Samples ; 2016; Lee, Ad.; ZuWallack, R. S.
- Communicating Data Use and Privacy: In-person versus Web based methods for message testing ; 2016; Clark Fobia, A.; Hunter Childs, J. E.
- User Experience and Eye-tracking: Results to Optimize Completion of a Web Survey and Website Design ; 2016; Walton, L.; Ricci, K.; Libman Barry, A.; Eiginger, C.; Christian, L. M.
- Estimated-control Calibrated Estimates from Nonprobability Surveys; 2016; Dever, J. A.
- Decomposing Selection Effects in Non-probability Samples ; 2016; Mercer, A. W.; Keeter, S.; Kreuter, F.
- The Effect of Emphasizing the Web Option in a Mixed-mode Establishment Survey ; 2016; O'Brien, J.; Rajapaksa, S.; Schafer, B.; Langetieg, P.
- A Multi-phase Exploration Into Web-based Panel Respondents: Assessing Differences in Recruitment, Respondents...; 2016; Redlawsk, D.; Rogers, K.; Borie-Holtz, D.
- Effect of Clarifying Instructions on Response to Numerical Open-ended Questions in Self-administered...; 2016; Kumar Chaudhary, A.; Israel, G. D.
- Exploring the Feasibility of Using Facebook for Surveying Special Interest Populations ; 2016; Lee, C.; Jang, S.
- National Estimates of Sexual Minority Women Alcohol Use through Web Based Respondent Driven Sampling...; 2016; Farrell Middleton, D.; Iachan, R.; Freedner-Maguire, N.; Trocki, K.; Evans, C.
- Bringing Fair Market Rent Surveys into the 21st Century – Evaluating the Effectiveness of MSG...; 2016; Dayton, J.; Brassell, T.; Cooper, V.; Dion, R.; Williams, R.
- Measuring Survey Behavior of Smartphone Users; 2016; Luks, S.; Phillips, R.
- Practical Considerations for Using Vignettes to Evaluate Survey Items ; 2016; Steiger, D. M.; Williams, Do.; Edwards, W. S.; Cantor, D.; Truman, J.
- Using Web Panels to Quantify the Qualitative: The National Center for Health Statistics Research and...; 2016; Scanlon, P. J.
- Impact of Field Period Length in the Estimates of Sexual Victimization in a Web-based Survey of College...; 2016; Berzofsky, M.; Peterson, K.; Shook-Sa, B. E.; Lindquist, C.; Krebs, C.
- Longitudinal Online Ego-centric Social Network Data Collection with EgoWeb 2.0 ; 2016; Amin, A.; Kennedy, D.
- Influences on Item Response Times in a Multinational Web Survey ; 2016; Phillips, B. T.; Kolenikov, S.; Howard Ecklund, E.; Ackermann, A.; Brulia, A.
- QR Codes for Survey Access: Is It Worth It?; 2016; Allen, L.; Marlar, J.
- An Exploration of the Relationship between Usability Testing and Data Verification ; 2016; Langer Tesfaye, C.; Kurmlavage, V.
- Beyond the Survey: Improving Data Insights and User Experience with Mobile Devices ; 2016; Graham, P.; Lew, G.
- User Experience Considerations for Contextual Product Surveys on Smartphones ; 2016; Sedley, A.; Mueller, H.
- The Differential Effect of Mobile-friendly Surveys on Data Quality; 2016; Horwitz, R.
- Embedding Survey Questions within Non-research Mobile Apps: A Method for Collecting High-quality Data...; 2016; Bapna, V.; Antoun, C.
- Does Changing Monetary Incentive Schemes in Panel Studies Affect Cooperation? A Quasi-experiment on...; 2016; Schaurer, I.; Bosnjak, M.
- Survey Mode and Mail Method: A Practical Experiment in Survey Fielding for a Multi-round Survey ; 2016; Sullivan, B. D.; Duda, N.; Bogen, K.; Clusen, N. A.; Wakar, B.; Zhou, H.
- Web Probing for Question Evaluation: The Effects of Probe Placement ; 2016; Fowler, S.; Willis, G. B.; Moser, R. P.; Townsend, R. L. M.; Maitland, A.; Sun, H.; Berrigan, D.
- Early-bird Incentives: Results From an Experiment to Determine Response Rate and Cost Effects ; 2016; De Santis, J.; Callahan, R.; Marsh, S.; Perez-Johnson, I.
- Using Cash Incentives to Help Recruitment in a Probability Based Web Panel: The Effects on Sign Up Rates...; 2016; Krieger, U.
- Assessing Changes in Coverage Bias of Web Surveys a s Internet Access Increases in the United States...; 2016; Sterrett, D.; Malato, D.; Benz, J.; Tompson, T.; English, N.
- Timing is Everything: Discretely Discouraging Mobile Survey Response through the Timing of Email Contacts...; 2016; Richards, A.; C.; Shook-Sa, B. E.; C.; Berzofsky, M.; Smith, A. C.
- Dynamic Instructions in Check-All-That-Apply Questions ; 2016; Kunz, T.; Fuchs, M.
- Patterns of Unit and Item Nonresponse in a Multinational Web Survey ; 2016; Ackermann, A.; Howard Ecklund, E.; Phillips, B. T.; Brulia, A.
- Debunking Myths About the Quality of Industry and O ccupation Data Collected Through Self-administered...; 2016; Hurwitz, F. I.; Stein, J.; Skaff, A. L.
- Desktops, Tablets and Phones, Oh My! Device Prefere nce for Web Based Surveys ; 2016; Schy, S.; Ghirardelli, A.; Morrison, H.
- Assessing Potential Bias in Respondent-driven Incident Based Data from a Web Survey of College Students...; 2016; Peterson, K.; Berzofsky, M.; Shook-Sa, B. E.; Krebs, C.; Lindquist, C.
- Making Connections on the Internet: Online Survey Panel Communications ; 2016; Libman Barry, A.; Eiginger, C.; Walton, L.; Ricci, K.