Web Survey Bibliography
Title Translucent is the mind of the web user
Author Britschgi, M.
Year 2005
Access date 29.04.2005
Abstract Psychographic and qualitative segmentation finds its way into Swiss internet research. The "blue mind Strategy Tool for Online Advertising" is the first standardized internet research which includes psychography. Therewith a deficiency of the hitherto mere quantitative research should be removed, which only registers range, visits, page views etc., but owes information about the qualitative characteristics of the users. The aim of the psychographic research is to enable website carriers to offer the same structural data to the advertisers that they are used to by the "Offline-Media". As it is very difficult to compare the values concerning range of a website with the values of a magazine the psychography can serve as a common denominator. So far psychography has not been used in the internet, because questionnaires that are necessary in order to determine psychographic characteristics on the one hand are too long. On the other hand, because of the content of the questions which is value-free (neutral) they have the effect that the respondent does not understand their sense leading finally to a dropout of the online interview. blue mind is the newest development for psychography on the Swiss market. blue mind benefits from the fact that the preference for certain visual incentives (pictures, photos etc. ) are demonstrably related to ideals and values. This awareness is nothing new in empiric market research and statistically provable. 12'000 online interviews and 2'000 offline interviews with up to 30 pictures correlated to many questions concerning attitude have been realized. Meanwhile by means of 16 pictures different patterns of values and attitudes showing great variety (consumption, leisure time, media, advertising) can be determined. The blue mind psychography has proved itself in the application of online and offline studies. Software is provided for visualising the data. The blue mind - questionnaire is placed at the disposal of any interested party (institutes etc.), not depending on whether the study is realized with blue eyes marketing or not. Only the editing of the data has to be realized coercively by blue eyes marketing. This marketing model (release of the items to anyone interested) is unique in Switzerland.
Abstract - optional Gläsern ist die Psyche des WebusersNeue Internetforschung von blue eyes marketing sorgt für mehr Transparenz für WerbetreibendeDie psychografische und qualitative Segmentierung hält Einzug in die schweizerische Internetforschung. Das "blue mind Strategie Tool für Online Werbung" ist die erste standardisierte Internetforschung, welche auch die Psychografie mit einbezieht.Damit soll ein Mangel der bisherigen rein quantitativen Forschung bereinigt werden, die lediglich Reichweiten, Visits, Page Views etc. erfasst, aber Aussagen über qualitative Merkmale der User schuldig bleibt.Ziel der psychografischen Forschung soll es sein, dass die Website-Betreiber den Werbetreibenden die gleichen Strukturdaten liefern können wie sie es von den "Offline"-Medien gewohnt sind. Da es sehr schwer ist, die Reichweiten-Werte einer Website mit den Werten einer Zeitschrift zu vergleichen, kann die Psychografie als gemeinsamer Nenner dienen.Die Psychografie wurde im Internet bisher nicht eingesetzt, weil die Fragebatterien, welche zur Bestimmung der psychografischen Merkmale nötig sind, einerseits zu lang sind und anderseits durch die wertfreien (neutralen) Frageinhalte der Befragte den Sinn der Fragen nicht versteht und dadurch das Online-Interview abbricht. blue mind ist die neuste Entwicklung auf dem Schweizermarkt für Psychografie. blue mind macht sich die Tatsache zu Nutzen, dass die Präferenz für gewisse visuelle Anreize (Bilder, Fotos etc.) beweisbar mit den Wertvorstellungen zusammenhängt. Diese Erkenntnis ist in der empirischen Marktforschung absolut nicht neu und ist statistisch belegbar. Für den blue mind Test wurden 12'000 Interviews online und 2'000 Interviews offline mit bis zu 30 Bildern und vielen Einstellungsfragen zur Korrelation durchgeführt. Mittlerweile lassen sich mit 16 Bildern Werthaltungsmuster ermitteln, die im Verhalten (Konsum, Freizeit, Medien, Werbung) stark differenzieren.Die blue mind Psychgrafie hat sich im Einsatz von online und offline Studien bewährt. Zur Visualisierung der Daten wird eine Software mitgeliefert. Die blue mind - Fragebatterie wird allen Interessierten zur Verfügung gestellt (Institute etc.), unabhängig davon, ob die Studie mit blue eyes marketing durchgeführt wird oder nicht. Einzig die Aufbereitung der Daten erfolgt zwingend bei blue eyes marketing. Dieses Marketingmodel (Freigabe der Items für alle Interessierten) ist in der Schweiz einzigartig.
Access/Direct link Homepage - conference (abstract)
Year of publication2005
Bibliographic typeConference proceedings
Web survey bibliography (4086)
- Displaying Videos in Web Surveys: Implications for Complete Viewing and Survey Responses; 2017; Mendelson, J.; Lee Gibson, J.; Romano Bergstrom, J. C.
- Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not...; 2017; Toepoel, V.; Emerson, H.
- Mind the Mode: Differences in Paper vs. Web-Based Survey Modes Among Women With Cancer; 2017; Hagan, T. L.; Belcher, S. M.; Donovan, H. S.
- Answering Without Reading: IMCs and Strong Satisficing in Online Surveys; 2017; Anduiza, E.; Galais, C.
- Ideal and maximum length for a web survey; 2017; Revilla, M.; Ochoa, C.
- Social desirability bias in self-reported well-being measures: evidence from an online survey; 2017; Caputo, A.
- Web-Based Survey Methodology; 2017; Wright, K. B.
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Lessons from recruitment to an internet based survey for Degenerative Cervical Myelopathy: merits of...; 2017; Davies, B.; Kotter, M. R.
- Web Survey Gamification - Increasing Data Quality in Web Surveys by Using Game Design Elements; 2017; Schacht, S.; Keusch, F.; Bergmann, N.; Morana, S.
- Effects of sampling procedure on data quality in a web survey; 2017; Rimac, I.; Ogresta, J.
- Comparability of web and telephone surveys for the measurement of subjective well-being; 2017; Sarracino, F.; Riillo, C. F. A.; Mikucka, M.
- Achieving Strong Privacy in Online Survey; 2017; Zhou, Yo.; Zhou, Yi.; Chen, S.; Wu, S. S.
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Telephone versus Online Survey Modes for Election Studies: Comparing Canadian Public Opinion and Vote...; 2017; Breton, C.; Cutler, F.; Lachance, S.; Mierke-Zatwarnicki, A.
- Examining Factors Impacting Online Survey Response Ratesin Educational Research: Perceptions of Graduate...; 2017; Saleh, A.; Bista, K.
- Usability Testing for Survey Research; 2017; Geisen, E.; Romano Bergstrom, J. C.
- Paradata as an aide to questionnaire design: Improving quality and reducing burden; 2017; Timm, E.; Stewart, J.; Sidney, I.
- Fieldwork monitoring and managing with time-related paradata; 2017; Vandenplas, C.
- Interviewer effects on onliner and offliner participation in the German Internet Panel; 2017; Herzing, J. M. E.; Blom, A. G.; Meuleman, B.
- Interviewer Gender and Survey Responses: The Effects of Humanizing Cues Variations; 2017; Jablonski, W.; Krzewinska, A.; Grzeszkiewicz-Radulska, K.
- Millennials and emojis in Spain and Mexico.; 2017; Bosch Jover, O.; Revilla, M.
- Where, When, How and with What Do Panel Interviews Take Place and Is the Quality of Answers Affected...; 2017; Niebruegge, S.
- Comparing the same Questionnaire between five Online Panels: A Study of the Effect of Recruitment Strategy...; 2017; Schnell, R.; Panreck, L.
- Nonresponses as context-sensitive response behaviour of participants in online-surveys and their relevance...; 2017; Wetzlehuetter, D.
- Do distractions during web survey completion affect data quality? Findings from a laboratory experiment...; 2017; Wenz, A.
- Predicting Breakoffs in Web Surveys; 2017; Mittereder, F.; West, B. T.
- Measuring Subjective Health and Life Satisfaction with U.S. Hispanics; 2017; Lee, S.; Davis, R.
- Humanizing Cues in Internet Surveys: Investigating Respondent Cognitive Processes; 2017; Jablonski, W.; Grzeszkiewicz-Radulska, K.; Krzewinska, A.
- A Comparison of Emerging Pretesting Methods for Evaluating “Modern” Surveys; 2017; Geisen, E., Murphy, J.
- The Effect of Respondent Commitment on Response Quality in Two Online Surveys; 2017; Cibelli Hibben, K.
- Pushing to web in the ISSP; 2017; Jonsdottir, G. A.; Dofradottir, A. G.; Einarsson, H. B.
- The 2016 Canadian Census: An Innovative Wave Collection Methodology to Maximize Self-Response and Internet...; 2017; Mathieu, P.
- Push2web or less is more? Experimental evidence from a mixed-mode population survey at the community...; 2017; Neumann, R.; Haeder, M.; Brust, O.; Dittrich, E.; von Hermanni, H.
- In search of best practices; 2017; Kappelhof, J. W. S.; Steijn, S.
- Redirected Inbound Call Sampling (RICS); A New Methodology ; 2017; Krotki, K.; Bobashev, G.; Levine, B.; Richards, S.
- An Empirical Process for Using Non-probability Survey for Inference; 2017; Tortora, R.; Iachan, R.
- The perils of non-probability sampling; 2017; Bethlehem, J.
- A Comparison of Two Nonprobability Samples with Probability Samples; 2017; Zack, E. S.; Kennedy, J. M.
- Rates, Delays, and Completeness of General Practitioners’ Responses to a Postal Versus Web-Based...; 2017; Sebo, P.; Maisonneuve, H.; Cerutti, B.; Pascal Fournier, J.; Haller, D. M.
- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
- Nonresponse in Organizational Surveying: Attitudinal Distribution Form and Conditional Response Probabilities...; 2017; Kulas, J. T.; Robinson, D. H.; Kellar, D. Z.; Smith, J. A.
- Theory and Practice in Nonprobability Surveys: Parallels between Causal Inference and Survey Inference...; 2017; Mercer, A. W.; Kreuter, F.; Keeter, S.; Stuart, E. A.
- Is There a Future for Surveys; 2017; Miller, P. V.
- Reducing speeding in web surveys by providing immediate feedback; 2017; Conrad, F.; Tourangeau, R.; Couper, M. P.; Zhang, C.
- Social Desirability and Undesirability Effects on Survey Response latencies; 2017; Andersen, H.; Mayerl, J.
- A Working Example of How to Use Artificial Intelligence To Automate and Transform Surveys Into Customer...; 2017; Neve, S.
- A Case Study on Evaluating the Relevance of Some Rules for Writing Requirements through an Online Survey...; 2017; Warnier, M.; Condamines, A.
- Estimating the Impact of Measurement Differences Introduced by Efforts to Reach a Balanced Response...; 2017; Kappelhof, J. W. S.; De Leeuw, E. D.
- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.