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More prizes are not always more attractive: factors increasing prospective sweepstakes participants’ sensitivity to the number of prizes

Abstract

Sweepstakes that offer more identical prizes do not necessarily attract more participants. When deciding whether to participate in a sweepstakes presented in isolation (typical case), most consumers cannot evaluate if the number of prizes offered is “good” or “bad” within a certain range (1–10 prizes), because of the low evaluability of this attribute. Therefore, they do not perceive their odds of winning as better with more prizes, nor are they more likely to participate. Five studies detail this process and illustrate which individual and contextual factors (participation frequency in sweepstakes, availability of information about the usual number of prizes for comparable sweepstakes, visual reinforcement of the number of prizes by a consistent number of pictures) increase the evaluability of the number of prizes, which can reduce magnitude insensitivity. This study in turn provides managerial insights into how to design and advertise efficient sweepstakes.

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Notes

  1. The average probability estimate was 1.79 % (SD = .07). The answers did not follow a Gaussian distribution (skewness = 5.90 with a SE = .23; kurtosis = 37.50 with a SE = .45), so we performed a logarithmic transformation to support the parametric tests (after the transformation, skewness = .80, with a SE = .23, kurtosis = −.30 with a SE = .45).

  2. The answers did not follow a Gaussian distribution (M = 1,763,523; SD = 11,672,458; skewness = 10.00 with a SE = .23; kurtosis = 102.03 with a SE = .46) so we performed a logarithm transformation (after the transformation, skewness = .30, with a SE = .23; kurtosis = −.18 with a SE = .46).

  3. We also computed what should have been a “rational” probability of winning for each respondent, by dividing the number of prizes in the experimental condition to which they were assigned by their estimation of the number of participants. The distribution of these calculated probabilities was lognormal, so we took their natural logarithms. The values increased significantly with the number of prizes (F(3,103) = 34.06; p < .001). The contrast between 1 and 10 prizes was significant (d = 1.74, t(103) = 2.60, p = .01), as were the contrasts between 1 and 100 (d = 4.92, t(103) = 7.50, p < .001) and between 1 and 1000 (d = 5.88; t(103) = 8.87, p < .001). The contrast between 10 and 100 prizes was significant (d = 3.18, t(103) = 4.67, p < .001), but that between 100 and 1,000 prizes was not (d = .96, t(103) = 1.43, NS). Thus, the probability estimates by the respondents did not follow the same pattern as the “rational” probabilities calculated on the basis of their estimates of the number of entrants and the manipulated number of prizes. The former were magnitude insensitive within a certain range; the latter increased even for moderate variations of the number of prizes. This discrepancy helps rule out the idea that the magnitude insensitivity of probability estimates resulted from rational inferences about the number of participants.

  4. The answers did not follow a Gaussian distribution (M = 723.22; SD = 1,839.51; skewness = 4.35 with a SE = .25; kurtosis = 19.09 with a SE = .49), so we performed a logarithm transformation (after the transformation, skewness = .11 with a SE = .25; kurtosis = 1.33 with a SE = .49).

  5. After testing different values for c from .001 to 1, we adopted a value of .3, which generated a distribution of transformed probabilities that was close to Gaussian (after transformation, skewness = .84 with a SE = .23; kurtosis = −.00 with a SE = .46). Using smaller or larger values of c did not alter the key findings though.

References

  • Ailawadi, K. L., Gedenk, K., Langer, T., Ma, Y., & Neslin, S. A. (2014). Consumer response to uncertain promotions: an empirical analysis of conditional rebates. International Journal of Research in Marketing, 31(1), 94–106.

    Article  Google Scholar 

  • Ariely, D., & Loewenstein, G. (2000). When does duration matter in judgment and decision making? Journal of Experimental Psychology. General, 129, 508–529.

    Article  Google Scholar 

  • Bettman, J. R., & Park, C. W. (1980). Effects of prior knowledge and experience and phase of the choice process on consumer decision processes: a protocol analysis. Journal of Consumer Research, 234–248.

  • Blattberg, R. C., Kim, B.-D., & Neslin, S. A. (2008). Database marketing: analyzing and managing customers. New York: Springer.

    Book  Google Scholar 

  • Chandler, J., Mueller, P., & Paolacci, G. (2013). Nonnaïveté among Amazon Mechanical Turk workers: Consequences and solutions for behavioral researchers. Behavior Research Methods, 1–19, doi: 10.3758/s13428–013–0365–7

  • Cryder, C.E., Mullen, E.E., & Loewenstein, G. (2008, November). Wanting versus choosing: A disconnect between what moves us and what we prefer. Paper presented at the Society for Judgment and Decision Making Preconference: Using Human Nature to Improve Human Life, Chicago, IL.

  • Dehaene, S. (2011). The number sense: How the mind creates mathematics, revised and updated edition. Oxford: Oxford University Press.

    Google Scholar 

  • Desvousges, W. H., Johnson, F., Dunford, R., Hudson, S., Wilson, K., & Boyle, K. (1993). Measuring natural resource damages with contingent valuation: tests of validity and reliability. In J. Hausman (Ed.), Contingent valuation: A critical assessment (pp. 91–159). Amsterdam: North-Holland.

    Google Scholar 

  • Dhar, S. K., Gonzalez-Vallejo, C., & Soman, D. (1999). Modeling the effects of advertised price claims: tensile versus precise claims? Marketing Science, 18(2), 154–177.

    Article  Google Scholar 

  • Erev, I., & Rapoport, A. (1998). Coordination, “magic”, and reinforcement learning in a market entry game. Games and economic behavior, 23(2), 146–175.

    Article  Google Scholar 

  • Feinman, J. P., Blashek, R. D., & McCabe, R. J. (1986). Sweepstakes, prize promotions, games and contests. New York: McGraw-Hill.

    Google Scholar 

  • Fetherstonhaugh, D., Slovic, P., Johnson, S., & Friedrich, J. (1997). Insensitivity to the value of human life: a study of psychophysical numbing. Journal of Risk and Uncertainty, 14, 283–300.

    Article  Google Scholar 

  • Fredrickson, B. L., & Kahneman, D. (1993). Duration neglect in retrospective evaluations of affective episodes. Journal of Personality and Social Psychology, 65, 45–55.

    Article  Google Scholar 

  • Goldsmith, K., & Amir, O. (2010). Can uncertainty improve promotion? Journal of Marketing Research, 47(6), 1070–1077.

    Article  Google Scholar 

  • Gonzalez-Vallejo, C., & Moran, E. (2001). The evaluability hypothesis revisited: joint and separate evaluation preference reversal as a function of attribute importance. Organizational Behavior and Human Decision Processes, 86, 216–233.

    Article  Google Scholar 

  • Hönekopp, J. (2003). Precision of probability information and prominence of outcomes: a description and evaluation of decision under uncertainty. Organizational Behaviors and Human Decision Processes, 90, 124–138.

    Article  Google Scholar 

  • Hsee, C. K. (1996). The evaluability hypothesis: an explanation for preference reversals between joint and separate evaluations of alternatives. Organizational Behavior and Human Decision Processes, 67, 247–257.

    Article  Google Scholar 

  • Hsee, C. K. (1998). Less is better: when low-value options are valued more highly than high-value options. Journal of Behavioral Decision Making, 11, 107–121.

    Article  Google Scholar 

  • Hsee, C. K. (2000). Attribute evaluability: its implications for joint-separate evaluation reversals and beyond. In D. Kahneman & A. Tversky (Eds.), Choices, values, and frames (pp. 543–565). New York: Russell Sage.

    Google Scholar 

  • Hsee, C. K., & Zhang, J. (2004). Distinction bias: misprediction and mischoice due to joint evaluation. Journal of Personality and Social Psychology, 86, 680–695.

    Article  Google Scholar 

  • Hsee, C. K., & Zhang, J. (2010). General evaluability theory. Perspectives on Psychological Science, 5(4), 343–355.

    Article  Google Scholar 

  • Hsee, C. K., Blount, S., Loewenstein, G., & Bazerman, M. (1999). Preference reversals between joint and separate evaluations of options: a review and theoretical analysis. Psychological Bulletin, 125, 576–590.

    Article  Google Scholar 

  • Hsee, C. K., Rottenstreich, Y., & Xiao, Z. (2005). When is more better? on the relationship between magnitude and subjective value. Current Directions in Psychological Science, 14(5), 234–237.

    Article  Google Scholar 

  • Hsee, C. K., Yang, Y., Li, N., & Shen, L. (2009). Wealth, warmth, and well-being: whether happiness is relative or absolute depends on whether it is about money, acquisition, or consumption. Journal of Marketing Research, 46, 396–409.

    Article  Google Scholar 

  • Jiang, Y., Cho, A., & Adaval, T. (2009). The unique consequences of feeling lucky: implications for consumer behavior. Journal of Consumer Psychology, 19, 171–184.

    Article  Google Scholar 

  • Kahneman, D., Fredrickson, B. L., Schreiber, C. A., & Redelmeier, D. A. (1993). When more pain is preferred to less: adding a better end. Psychological Science, 4, 401–405.

    Article  Google Scholar 

  • Kalra, A., & Shi, M. (2010). Consumer value-maximizing sweepstakes and contests. Journal of Marketing Research, 47, 287–300.

    Article  Google Scholar 

  • Kogut, T., & Ritov, I. (2005). The singularity effect of identified victims in separate and joint evaluations. Organizational Behavior and Human Decision Processes, 97, 106–116.

    Article  Google Scholar 

  • List, J. (2002). Preference reversals of a different kind: the “more is less” phenomenon. American Economic Review, 92, 1636–1643.

    Article  Google Scholar 

  • Loftus, E. F. (1975). Leading questions and the eyewitness report. Cognitive Psychology, 7(4), 560–572.

    Article  Google Scholar 

  • Madzharov, A. V., & Block, L. (2010). Effects of product unit image on consumption of snack foods. Journal of Consumer Psychology, 20, 398–409.

    Article  Google Scholar 

  • Mogelefsky, D. (2000). Million dollar madness. Incentive, 174(2), 18–25.

    Google Scholar 

  • Morewedge, C. K., Kassam, K. S., Hsee, C. K., & Caruso, E. M. (2009). Duration sensitivity depends on stimulus familiarity. Journal of Experimental Psychology. General, 138, 177–186.

    Article  Google Scholar 

  • Odell, P. (2009). Spending up by a nose. (accessed September 13, 2011) [available at http://promomagazine.com/contests/marketing_spending_nose/].

  • Paivio, A. (1986). Mental representations: A dual coding approach. New York: Oxford University Press.

    Google Scholar 

  • Park, C. W., Mothersbaugh, D. L., & Feick, L. (1994). Consumer knowledge assessment. Journal of Consumer Research, 21(1), 71–82.

    Article  Google Scholar 

  • Pezdek, K. (1977). Cross-modality semantic integration of sentence and picture memory. Journal of Experimental Psychology: Human Learning and Memory, 3(5), 515.

    Google Scholar 

  • Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879.

    Article  Google Scholar 

  • Rapoport, A., Seale, D. A., Erev, I., & Sundali, J. A. (1998). Equilibrium play in large group market entry games. Management Science, 44(1), 119–141.

    Article  Google Scholar 

  • Rottenstreich, Y., & Kivetz, R. (2006). Decision making without likelihood judgment. Organizational Behavior and Human Decision Processes, 101, 74–88.

    Article  Google Scholar 

  • Sasson, R. Y. (1971). Interfering images at sentence retrieval. Journal of Experimental Psychology, 89(1), 56.

    Article  Google Scholar 

  • Shapira, Z., & Venezia, I. (1992). Size and frequency of prizes as determinants of the demand for lotteries. Organizational Behavior and Decision Making Processes, 52, 307–318.

    Article  Google Scholar 

  • Path to Purchase Institute and Shopper Marketing (2013). Type of digital marketing content used for digital shopper marketing programs according to US CPG executives, march 2013 (% of respondants) [chart], Digital Shopper Marketers Survey 2013. As cited by emarketer. Retrieved March 14th 2014.

  • Spiller, S. A., Fitzsimons, G. J., Lynch, J. G., Jr., & McClelland, G. H. (2013). Spotlights, floodlights, and the magic number zero: simple effects tests in moderated regression. Journal of Marketing Research, 50(2), 277–288.

    Article  Google Scholar 

  • Sundali, J. A., Rapoport, A., & Seale, D. A. (1995). Coordination in market entry games with symmetric players. Organizational Behavior and Human Decision Processes, 64(2), 203–218.

    Article  Google Scholar 

  • Teichmann, M. H., Gedenk, K., & Knaf, M. (2005). Consumers’ preferences for online vs. offline sweepstakes and contests: the impact of promotion attributes on consumers’ entry decisions. Marketing Journal of Research and Management, 1, 76–90.

    Google Scholar 

  • Townsend, C., & Kahn, B. E. (2014). The “visual preference heuristic”: the influence of visual versus verbal depiction on assortment processing, perceived variety, and choice overload. Journal of Consumer Research, 40(5), 993–1015.

    Article  Google Scholar 

  • Tukey, J. W. (1977). Exploratory data analysis. Boston: Addison-Wesley.

    Google Scholar 

  • Ward, J. C., & Hill, R. P. (1991). Designing effective promotional games: opportunities and problems. Journal of Advertising, 20(3), 69–81.

    Article  Google Scholar 

  • Wildfire (2012a). Facebook users’ rate of sharing facebook marketing campaigns worldwide, by type, April 2012 [Chart]. Earned Media Study. As cited by emarketer. Retrieved March 27th 2014.

  • Wildfire (2012b). Earned Media Click Rate for Facebook Marketing Campaigns Worldwide, by Type, April 2012 [Chart]. Earned Media Study. As cited by emarketer. Retrieved March 27th 2014.

  • Woloshin, S., Schwartz, L. M., Byram, S., Fischoff, B., & Welsch, G. (2000). A new scale for assessing perceptions of chance. Medical Decision Making, 20(3), 298–307.

    Article  Google Scholar 

  • Yan, D., & Muthukrishnan, A. V. (2014). Killing hope with good intentions: the effects of consolation prizes on preference for lottery promotions. Journal of Marketing Research: In-Press.

    Google Scholar 

  • Yeung, C. W. M., & Soman, D. (2005). Attribute evaluability and the range effect. Journal of Consumer Research, 32, 363–369.

    Article  Google Scholar 

  • Yeung, C. W. M., & Soman, D. (2007). The duration heuristic. Journal of Consumer Research, 34, 315–326.

    Article  Google Scholar 

  • Zikmund-Fisher, B. J., Fagerlin, A., & Ubel, P. A. (2004). “Is 28% good or bad?” evaluability and preference reversals in health care decisions. Medical Decision Making, 24, 142–148.

    Article  Google Scholar 

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Acknowledgments

The authors thank Yany Grégoire, Renaud Legoux, Christian Pinson, Bernard Pras, Marc Vanhuele, and Luk Warlop for their comments and suggestions on previous versions of this manuscript

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Correspondence to Sandra Laporte.

Appendices

Appendix A

Example ad for an actual sweepstakes, featuring as many pictures as prizes to win

figure a

Appendix B

Visual analog scale (Woloshin et al. 2000) from Study 1 to measure estimated probability of winning

If you enter this lottery, what do you believe your chance of winning is?

Place an “X” in EITHER the magnifying glass OR the lower part of the scale to describe the chance you win if you participate to the random drawing.

figure b

Appendix C

Example of a sweepstakes used in Study 3 for the evaluability manipulation

A cosmetics store gives some secret codes to its customers and invites them to come back 2 weeks later where six winning secret codes will be drawn. The customers who received a secret code have to visit the store 2 weeks later if they want to enter the drawing. Each of the [only in the high evaluability condition: six] winners will receive the women’s fragrance “Allure” de Chanel (100 ml, 3.4 fl. oz.).

How demanding are the requirements to enter the sweepstake?

(Not demanding at all 1 2 3 4 5 6 7 Very demanding)

Is the type of prize appropriate for 30-year old women?

(Not appropriate at all 1 2 3 4 5 6 7 Very appropriate)

Is the type of prize consistent with the organizer?

(Not at all consistent 1 2 3 4 5 6 7 Very consistent)

[High evaluability condition] What do you think about the number of winners (6)?

(It’s a low number 1 2 3 4 5 6 7 It’s a high number)

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Laporte, S., Laurent, G. More prizes are not always more attractive: factors increasing prospective sweepstakes participants’ sensitivity to the number of prizes. J. of the Acad. Mark. Sci. 43, 395–410 (2015). https://doi.org/10.1007/s11747-014-0389-2

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  • DOI: https://doi.org/10.1007/s11747-014-0389-2

Keywords

  • Magnitude insensitivity
  • Evaluability
  • Sweepstakes
  • Subjective winning odds