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Modelling and predicting an individual’s perception of advertising appeal

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Abstract

Existing research has found that people evaluate an ad as being more appealing when its design matches their psychological traits. Therefore, to personalise ad design or predict the advertising appeal that an individual perceives, it is especially important to understand what psychological traits moderate an ad’s design effect to a large degree. The present research addressed this question. We conducted a questionnaire survey in which we measured participants’ personality and sense of value according to the Big Five personality traits (Big Five) and Schwartz’s Basic Value (SBV), and asked them advertising appeal that they perceived on ads with various designs. By comparing models that predict perceived advertising appeal using the Big Five and the SBV, we found that the SBV moderates ad design’s effect to a greater extent than does the Big Five. This finding will have an impact on the research of ad personalisation, where researchers have focused on the Big Five and paid little attention to sense of value when examining people’s psychological traits. We also found that the personality sphere as measured by the different Big Five questionnaire inventories, of which the number and representation of items differed, moderates an ad design’s effect to a significantly different extent. We elicited potential requirements for the inventories to be used in such research, which will help researchers to select an inventory. We also confirmed that models that incorporate our findings outperformed the existing modelling approach in terms of prediction accuracy.

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Notes

  1. E.g., Chen et al. (2015), Clark and Çallı (2014), Ding and Pan (2016), Hirsh et al. (2012), Kobayashi et al. (2019), Matic et al. (2017), Matz et al. (2017), Myers et al. (2010), Roffo and Vinciarelli (2016) and Sofia et al. (2016).

  2. http://www.worldvaluessurvey.org/wvs.jsp.

  3. https://www.europeansocialsurvey.org/.

  4. Sample size (N), ratio of male to female (M/F) and mean age (MA) were \(N = 129\), \(M/F = 0.7\) and \(MA = 16.9\) in Furnham and Rao (2002) and \(N = 158\), \(M/F = 0.9\) and \(MA = 19.2\) in Swami and Furnham (2012), respectively.

  5. We utilised the Japanese version of the PVQ, which was studied in https://ci.nii.ac.jp/naid/40021433858/en/.

  6. https://tinyurl.com/OSFmaterial.

  7. https://github.com/chakki-works/chakin.

  8. \(\mathrm{Relative\,likelihood} = \exp (\frac{\mathrm{AIC}(m_\mathrm{D2})-\mathrm{AIC}(m_\mathrm{D4})}{2}).\)

  9. More information can be found in the following links: https://www.qualtrics.com/experience-management/brand/how-to-run-a-successful-ad-testing-program/, https://marketlensresearch.com/solutions/creative-testing, and https://blog.constructionmarketingassociation.org/practical-tips-for-advertising-testing/.

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Acknowledgements

The authors wish to acknowledge Atsunori Minamikawa and Chihiro Ono, KDDI Research, Inc., for their help in reviewing the paper.

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  1. KDDI Research, Inc., Saitama, Japan

    Yuichi Ishikawa, Akihiro Kobayashi & Daisuke Kamisaka

  2. KDDI Corporation, Tokyo, Japan

    Yuichi Ishikawa

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  1. Yuichi Ishikawa
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Ishikawa, Y., Kobayashi, A. & Kamisaka, D. Modelling and predicting an individual’s perception of advertising appeal. User Model User-Adap Inter 31, 323–369 (2021). https://doi.org/10.1007/s11257-020-09287-z

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