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Image data analysis and classification in marketing

  • Daniel Baier


  • Ines Daniel


  • Sarah Frost


  • Robert Naundorf


Registered author(s):

    Nowadays, the diffusion of smartphones, tablet computers, and other multipurpose equipment with high-speed Internet access makes new data types available for data analysis and classification in marketing. So, e.g., it is now possible to collect images/snaps, music, or videos instead of ratings. With appropriate algorithms and software at hand, a marketing researcher could simply group or classify respondents according to the content of uploaded images/snaps, music, or videos. However, appropriate algorithms and software are sparsely known in marketing research up to now. The paper tries to close this gap. Algorithms and software from computer science are presented, adapted and applied to data analysis and classification in marketing. The new SPSS-like software package IMADAC is introduced. Copyright Springer-Verlag Berlin Heidelberg 2012

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    Article provided by Springer in its journal Advances in Data Analysis and Classification.

    Volume (Year): 6 (2012)
    Issue (Month): 4 (December)
    Pages: 253-276

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    Handle: RePEc:spr:advdac:v:6:y:2012:i:4:p:253-276
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    1. Ahmed Albatineh & Magdalena Niewiadomska-Bugaj, 2011. "Correcting Jaccard and other similarity indices for chance agreement in cluster analysis," Advances in Data Analysis and Classification, Springer, vol. 5(3), pages 179-200, October.
    2. Bearden, William O & Netemeyer, Richard G & Teel, Jesse E, 1989. " Measurement of Consumer Susceptibility to Interpersonal Influence," Journal of Consumer Research, University of Chicago Press, vol. 15(4), pages 473-81, March.
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    4. Buckinx, Wouter & Van den Poel, Dirk, 2005. "Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting," European Journal of Operational Research, Elsevier, vol. 164(1), pages 252-268, July.
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