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Online Advertising Suppresses Visual Competition during Planned Purchases

Author

Listed:
  • Ralf van der Lans
  • Rik Pieters
  • Michel Wedel
  • Vicki G Morwitz
  • J Jeffrey Inman
  • Olivier Toubia

Abstract

Online advertising can help consumers to implement their purchase intentions on shopping websites. This research tests the hypothesis that online advertising can speed-up product search by visually suppressing competing products rather than by enhancing the target product on websites that lack a systematic visual organization. First, a survey shows that searching for products on a shopping website after having clicked on an online ad is a common experience. Second, a lay-theory experiment shows that the majority of participants incorrectly predict that online ads do not affect product search, but if these ads do, product search would be independent of shopping website design. Third, three eye-tracking and two search-time experiments reveal that online ads with an image of the target product improved search speed by about 25%, for websites without a systematic visual organization of products. Improved search speed was primarily due to faster rejection of competing products because the ads helped to perceptually suppress their color features. These results provide new insights into online advertising effects, the fundamental search processes through which these accrue, and how ads can support consumers in making their planned purchases.

Suggested Citation

  • Ralf van der Lans & Rik Pieters & Michel Wedel & Vicki G Morwitz & J Jeffrey Inman & Olivier Toubia, 2021. "Online Advertising Suppresses Visual Competition during Planned Purchases," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 48(3), pages 374-393.
    • Handle: RePEc:oup:jconrs:v:48:y:2021:i:3:p:374-393.
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    File URL: http://hdl.handle.net/10.1093/jcr/ucab017
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    Citations

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    Cited by:

    1. Ohlwein, Martin, 2022. "Same but different - The effect of the unit of measure on the valuation of a unit price," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    2. Nordfält, Jens & Ahlbom, Carl-Philip, 2024. "Utilising eye-tracking data in retailing field research: A practical guide," Journal of Retailing, Elsevier, vol. 100(1), pages 148-160.
    3. Di Wu & Zhenning Xu & Seung Bach, 2023. "Using Google Trends to predict and forecast avocado sales," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(4), pages 629-641, December.
    4. Yang, Shuai & Wang, Yizhe & Li, Zhen & Chen, Chiyin & Yu, Ziyue, 2022. "Time-of-day effects on (un)healthy product purchases: Insights from diverse consumer behavior data," Journal of Business Research, Elsevier, vol. 152(C), pages 447-460.
    5. Michel Wedel & Rik Pieters & Ralf Lans, 2023. "Modeling Eye Movements During Decision Making: A Review," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 697-729, June.
    6. Magdalena Iordache Platis & Cosmin Olteanu & Anca Luiza Hotoi, 2022. "Evolution of the Online Sales of Sustainable Products in the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(22), pages 1-16, November.

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