IDEAS home Printed from https://ideas.repec.org/a/vrs/gfkmir/v7y2015i2p34-39n7.html
   My bibliography  Save this article

Predicting Preferences for Innovative Design: The “Repeated Evaluation Technique” (RET)

Author

Listed:
  • Carbon Claus-Christian

    (Head of General Psychology and Methodology, University of Bamberg, Germany)

Abstract

How do you realistically assess the success potential of innovative products? This task is quite challenging because the Average Joe generally has an aversion to innovation. Therefore it is not really possible to get valid innovation evaluations from typical consumers. Only when we feel secure and have time to become familiar with a new thing can innovation become exciting and attractive. The “Repeated Evaluation Technique” (RET) was developed especially for the purpose of systematic familiarization with products to be evaluated. Subjects in an RET, for example, typical consumers, are encouraged to think explicitly and intensively about a product and its competitors. By forcing the subjects to engage with the material, known as the “elaboration,” the procedure helps consumers understand the product better and distinguish differences. The ascertained judgments come closer and closer to real everyday assessments that one would usually only gain after weeks and months of dealing with products.

Suggested Citation

  • Carbon Claus-Christian, 2015. "Predicting Preferences for Innovative Design: The “Repeated Evaluation Technique” (RET)," NIM Marketing Intelligence Review, Sciendo, vol. 7(2), pages 34-39, November.
  • Handle: RePEc:vrs:gfkmir:v:7:y:2015:i:2:p:34-39:n:7
    DOI: 10.1515/gfkmir-2015-0016
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/gfkmir-2015-0016
    Download Restriction: no

    File URL: https://libkey.io/10.1515/gfkmir-2015-0016?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:gfkmir:v:7:y:2015:i:2:p:34-39:n:7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.