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Including “touch-and-feel” in online consumer research: optimizing information gain given costs of data online versus in-person

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  • Brooks Oppenheimer

    (Reason Research)

Abstract

Given the high cost to corporations of in-person data collection attributable to focus group facility rental costs, recruitment costs, and honoraria, the corporate market researcher working with finite budget must weigh the pros and cons of in-person versus online research for tangible goods. The purpose of the study was to establish a practitioner accessible approach to maximizing information gain per dollar spent collecting sample. In phase one, a repeated-measures sample was obtained from in-person respondents who also completed the research online. Using the phase one covariance of online/in-person ratings, phase two online-only data were collected, transformed, and blended with phase one data to create a weighted purchase intent metric reflecting both online and in-person evaluations. By blending in-person (expensive) and online (cheap) data collection modes, cost-savings were realized without expanding the confidence internal around purchase intent.

Suggested Citation

  • Brooks Oppenheimer, 2024. "Including “touch-and-feel” in online consumer research: optimizing information gain given costs of data online versus in-person," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(2), pages 411-416, June.
    • Handle: RePEc:pal:jmarka:v:12:y:2024:i:2:d:10.1057_s41270-022-00205-3
    DOI: 10.1057/s41270-022-00205-3
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    References listed on IDEAS

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    1. Hamsa Bastani, 2021. "Predicting with Proxies: Transfer Learning in High Dimension," Management Science, INFORMS, vol. 67(5), pages 2964-2984, May.
    2. Daria Dzyabura & Srikanth Jagabathula & Eitan Muller, 2019. "Accounting for Discrepancies Between Online and Offline Product Evaluations," Marketing Science, INFORMS, vol. 38(1), pages 88-106, January.
    3. Maria Petrescu & Anjala S. Krishen, 2017. "Marketing analytics: from practice to academia," Journal of Marketing Analytics, Palgrave Macmillan, vol. 5(2), pages 45-46, June.
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