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The Improvement of Retargeting by Big Data: a Decision Support that Threatens the Brand Image?

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  • Maria Mercanti-Guérin

    (IAE Paris - Sorbonne Business School)

Abstract

With the emergence of Big Data and the increasing market penetration of ad retargeting advertising, the advertising industry's interest in using this new online marketing method is rising. Retargeting is an innovative technology based on Big Data. People who have gone to a merchant site and window-shopped but not purchased can be re-pitched with the product they showed an interest in. Therefore click rates and conversion rates are dramatically enhancing by retargeting. However, in spite of the increasing number of companies investing in retargeting, there is little academic research on this topic. In this paper we explore the links between retargeting, perceived intrusiveness and brand image. As results show the importance of perceived intrusiveness, ad repetition and ad relevance, we introduce new analytical perspectives on online strategies with the goal of facilitating collaboration between consumers and marketers.

Suggested Citation

  • Maria Mercanti-Guérin, 2020. "The Improvement of Retargeting by Big Data: a Decision Support that Threatens the Brand Image?," Post-Print hal-03027981, HAL.
    • Handle: RePEc:hal:journl:hal-03027981
    Note: View the original document on HAL open archive server: https://hal.science/hal-03027981
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    References listed on IDEAS

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    1. Ghasemaghaei, Maryam & Calic, Goran, 2020. "Assessing the impact of big data on firm innovation performance: Big data is not always better data," Journal of Business Research, Elsevier, vol. 108(C), pages 147-162.
    2. Mathias Dewatripont & Lars Peter Hansen & Stephen Turnovsky, 2003. "Advances in economics and econometrics :theory and applications," ULB Institutional Repository 2013/9557, ULB -- Universite Libre de Bruxelles.
    3. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-183, May.
    4. Insaf Khelladi & Sylvaine Castellano & Laurie Limongi, 2013. "The impact of profile and location-based personalization on customer behavior in a mobile context," Post-Print hal-01514498, HAL.
    5. Reichlin, Lucrezia, 2002. "Factor Models in Large Cross-Sections of Time Series," CEPR Discussion Papers 3285, C.E.P.R. Discussion Papers.
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    More about this item

    Keywords

    Big Data; Retargeting; Perceived Intrusiveness; Ad Relevance;
    All these keywords.

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