IDEAS home Printed from https://ideas.repec.org/a/kap/qmktec/v14y2016i4d10.1007_s11129-016-9178-1.html
   My bibliography  Save this article

The palette that stands out: Color compositions of online curated visual UGC that attracts higher consumer interaction

Author

Listed:
  • Nima Y. Jalali

    (University of North Carolina-Charlotte)

  • Purushottam Papatla

    (University of Wisconsin-Milwaukee)

Abstract

Photos posted by consumers on social media, like Instagram, often include brands. Despite the substantial increase in such photos, there have been few investigations into how prospective consumers respond to this visual UGC. We begin to address this gap by investigating the role of the color compositions of visual UGC in consumer response. Consumer response is operationalized as the click-rate for a photo by a consumer when it is curated on the online site of the brand that it includes. This is the proportion of visitors who click on it for an enlarged view. Composition is operationalized as the specific combination of levels of the photo’s color attributes: hue, chroma, and brightness. Our goal is to identify the color compositions of photos, ceteris paribus, which get more clicks when they are curated. Data for our investigation comes from clicks over a one-year period on photos posted on Instagram curated by fifteen brands in six product categories on their sites. We assume Beta distributed proportions and calibrate a Beta regression using MCMC methods for our investigation. We find that click-rates are higher for photos that include higher proportions of green and lower proportions of red and cyan. We also find that chroma of red and blue are higher in photos with higher click-rates. Findings from our research led the sponsoring firm to modify its proprietary curation algorithm for client brands. The firm informed us that, post-modification, there has been a substantial increase in click-rates of curated photos for brands in several categories.

Suggested Citation

  • Nima Y. Jalali & Purushottam Papatla, 2016. "The palette that stands out: Color compositions of online curated visual UGC that attracts higher consumer interaction," Quantitative Marketing and Economics (QME), Springer, vol. 14(4), pages 353-384, December.
  • Handle: RePEc:kap:qmktec:v:14:y:2016:i:4:d:10.1007_s11129-016-9178-1
    DOI: 10.1007/s11129-016-9178-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11129-016-9178-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11129-016-9178-1?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Olivier Droulers & Bernard Roullet, 2005. "Pharmaceutical Packaging Color and Drug Expectancy," Post-Print halshs-00078563, HAL.
    2. Gatignon, Hubert & Robertson, Thomas S, 1985. "A Propositional Inventory for New Diffusion Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 11(4), pages 849-867, March.
    3. Mandel, Naomi & Johnson, Eric J, 2002. "When Web Pages Influence Choice: Effects of Visual Primes on Experts and Novices," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 29(2), pages 235-245, September.
    4. Duan, Wenjing & Gu, Bin & Whinston, Andrew B., 2008. "The dynamics of online word-of-mouth and product sales—An empirical investigation of the movie industry," Journal of Retailing, Elsevier, vol. 84(2), pages 233-242.
    5. Silvia Ferrari & Francisco Cribari-Neto, 2004. "Beta Regression for Modelling Rates and Proportions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 799-815.
    6. Scott K. Shriver & Harikesh S. Nair & Reto Hofstetter, 2013. "Social Ties and User-Generated Content: Evidence from an Online Social Network," Management Science, INFORMS, vol. 59(6), pages 1425-1443, June.
    7. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    8. Laura A. Peracchio & Joan Meyers-Levy, 2005. "Using Stylistic Properties of Ad Pictures to Communicate with Consumers," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(1), pages 29-40, June.
    9. Floyd, Kristopher & Freling, Ryan & Alhoqail, Saad & Cho, Hyun Young & Freling, Traci, 2014. "How Online Product Reviews Affect Retail Sales: A Meta-analysis," Journal of Retailing, Elsevier, vol. 90(2), pages 217-232.
    10. Gerald J. Gorn & Amitava Chattopadhyay & Tracey Yi & Darren W. Dahl, 1997. "Effects of Color as an Executional Cue in Advertising: They're in the Shade," Management Science, INFORMS, vol. 43(10), pages 1387-1400, October.
    11. Nelson, Phillip, 1970. "Information and Consumer Behavior," Journal of Political Economy, University of Chicago Press, vol. 78(2), pages 311-329, March-Apr.
    12. Meyers-Levy, Joan & Peracchio, Laura A, 1995. "Understanding the Effects of Color: How the Correspondence between Available and Required Resources Affects Attitudes," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 22(2), pages 121-138, September.
    13. Nelson, Philip, 1974. "Advertising as Information," Journal of Political Economy, University of Chicago Press, vol. 82(4), pages 729-754, July/Aug..
    14. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    15. Lauren Labrecque & George Milne, 2013. "To be or not to be different: Exploration of norms and benefits of color differentiation in the marketplace," Marketing Letters, Springer, vol. 24(2), pages 165-176, June.
    16. Edell, Julie E & Staelin, Richard, 1983. "The Information Processing of Pictures in Print Advertisements," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 10(1), pages 45-61, June.
    17. Lemmens, A. & Croux, C., 2006. "Bagging and boosting classification trees to predict churn," Other publications TiSEM d5cb664d-5859-44db-a621-e, Tilburg University, School of Economics and Management.
    18. Rajesh Bagchi & Amar Cheema, 2013. "The Effect of Red Background Color on Willingness-to-Pay: The Moderating Role of Selling Mechanism," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 39(5), pages 947-960.
    19. David Constant & Lee Sproull & Sara Kiesler, 1996. "The Kindness of Strangers: The Usefulness of Electronic Weak Ties for Technical Advice," Organization Science, INFORMS, vol. 7(2), pages 119-135, April.
    20. Simonson, Itamar & Winer, Russell S, 1992. "The Influence of Purchase Quantity and Display Format on Consumer Preference for Variety," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 19(1), pages 133-138, June.
    21. Elizabeth G. Miller & Barbara E. Kahn, 2005. "Shades of Meaning: The Effect of Color and Flavor Names on Consumer Choice," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(1), pages 86-92, June.
    22. JoAndrea Hoegg & Joseph W. Alba, 2007. "Taste Perception: More than Meets the Tongue," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 33(4), pages 490-498, December.
    23. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    24. Herr, Paul M, 1989. "Priming Price: Prior Knowledge and Context Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 16(1), pages 67-75, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yu, Joanne & Egger, Roman, 2021. "Color and engagement in touristic Instagram pictures: A machine learning approach," Annals of Tourism Research, Elsevier, vol. 89(C).
    2. He, Jiaxiu & Li, Bingqing & Wang, Xin (Shane), 2023. "Image features and demand in the sharing economy: A study of Airbnb," International Journal of Research in Marketing, Elsevier, vol. 40(4), pages 760-780.
    3. Jalali, Nima Y. & Papatla, Purushottam, 2019. "Composing tweets to increase retweets," International Journal of Research in Marketing, Elsevier, vol. 36(4), pages 647-668.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cheng Zhao & Chong Alex Wang, 2023. "A cross-site comparison of online review manipulation using Benford’s law," Electronic Commerce Research, Springer, vol. 23(1), pages 365-406, March.
    2. Hailin Zhang & Xina Yuan & Tae Ho Song, 2020. "Examining the role of the marketing activity and eWOM in the movie diffusion: the decomposition perspective," Electronic Commerce Research, Springer, vol. 20(3), pages 589-608, September.
    3. Kordrostami, Elika & Rahmani, Vahid, 2020. "Investigating conflicting online review information:evidence from Amazon.com," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    4. Reckmann, Tobias, 2017. "Intellectual Structure and Emancipation of Word of Mouth Research: A Bibliometric Analysis of a Multidisciplinary Research Field," EconStor Preprints 179913, ZBW - Leibniz Information Centre for Economics.
    5. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    6. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    7. Duan, Yongrui & Liu, Tonghui & Mao, Zhixin, 2022. "How online reviews and coupons affect sales and pricing: An empirical study based on e-commerce platform," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    8. Sungsik Park & Woochoel Shin & Jinhong Xie, 2021. "The Fateful First Consumer Review," Marketing Science, INFORMS, vol. 40(3), pages 481-507, May.
    9. Li, Yimeng & Xiong, Yu & Mariuzzo, Franco & Xia, Senmao, 2021. "The underexplored impacts of online consumer reviews: Pricing and new product design strategies in the O2O supply chain," International Journal of Production Economics, Elsevier, vol. 237(C).
    10. Wang, Feng & Liu, Xuefeng & Fang, Eric (Er), 2015. "User Reviews Variance, Critic Reviews Variance, and Product Sales: An Exploration of Customer Breadth and Depth Effects," Journal of Retailing, Elsevier, vol. 91(3), pages 372-389.
    11. Agnieszka Zablocki & Bodo Schlegelmilch & Michael J. Houston, 2019. "How valence, volume and variance of online reviews influence brand attitudes," AMS Review, Springer;Academy of Marketing Science, vol. 9(1), pages 61-77, June.
    12. Thaís L. D. Souza & Marislei Nishijima & Ana C. P. Fava, 2019. "Do consumer and expert reviews affect the length of time a film is kept on screens in the USA?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(1), pages 145-171, March.
    13. Marchand, André & Hennig-Thurau, Thorsten & Wiertz, Caroline, 2017. "Not all digital word of mouth is created equal: Understanding the respective impact of consumer reviews and microblogs on new product success," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 336-354.
    14. Yuchi Zhang & David Godes, 2018. "Learning from Online Social Ties," Marketing Science, INFORMS, vol. 37(3), pages 425-444, May.
    15. Yogesh V. Joshi & Andres Musalem, 2021. "When Consumers Learn, Money Burns: Signaling Quality via Advertising with Observational Learning and Word of Mouth," Marketing Science, INFORMS, vol. 40(1), pages 168-188, January.
    16. Young Kwark & Gene Moo Lee & Paul A. Pavlou & Liangfei Qiu, 2021. "On the Spillover Effects of Online Product Reviews on Purchases: Evidence from Clickstream Data," Information Systems Research, INFORMS, vol. 32(3), pages 895-913, September.
    17. Tingting Nian & Arun Sundararajan, 2022. "Social Media Marketing, Quality Signaling, and the Goldilocks Principle," Information Systems Research, INFORMS, vol. 33(2), pages 540-556, June.
    18. Delre, Sebastiano A. & Luffarelli, Jonathan, 2023. "Consumer reviews and product life cycle: On the temporal dynamics of electronic word of mouth on movie box office," Journal of Business Research, Elsevier, vol. 156(C).
    19. Garrett P. Sonnier & Leigh McAlister & Oliver J. Rutz, 2011. "A Dynamic Model of the Effect of Online Communications on Firm Sales," Marketing Science, INFORMS, vol. 30(4), pages 702-716, July.
    20. Kick, Markus, 2015. "Social Media Research: A Narrative Review," EconStor Preprints 182506, ZBW - Leibniz Information Centre for Economics.

    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:kap:qmktec:v:14:y:2016:i:4:d:10.1007_s11129-016-9178-1. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.