There is much evidence that the presence of a feature advertisement can increase the sales and market share of the featured product. However, little is known about how feature ad characteristics (e.g., size, color, and location of the advertisement) affect the sales outcomes and how the effects take place. Prior research has predicted that feature advertisements lead to behavioral outcomes through their effect on consumers’ attention. Building on this idea, the authors propose a Bayesian statistical model to study how feature ad characteristics affect sales of the featured products and the mediating role of attention in these relationships. They use data from eye-tracking tests of feature advertisements, aggregated and matched with sales data at the level of the feature advertisement. Their approach accounts for endogeneity in the key variables involved and overcomes limitations of standard mediation analyses. They show that the gaze duration on a feature advertisement affects sales of the featured product beyond the mere presence of the advertisement and that a standard mediation analysis that does not accommodate endogeneity produces biased estimates of the effects of feature ad characteristics on sales. Their proposed methodology is widely applicable to mediation analyses. The findings imply that attention data collected in lab tests can help marketers compare the relative sales outcomes of different feature ad designs and improve the effectiveness and efficiency of feature adverting decisions.
Keywords: endogeneity, instrument variable, promotion, eye tracking, visual marketing
Sales Effects of Attention to Feature Advertisements: A Bayesian Mediation Analysis
Feature advertising is a sales promotion tool that consists of print materials intended to inform consumers about the availability, prices, and discounts of products (Blattberg and Neslin 1990; Mulhern and Leone 1990). It is informative advertising of
References: Allenby, Greg M. and James L. Ginter (1995), “The Effects of InStore Display and Feature Advertising on Consideration Sets,” International Journal of Research in Marketing, 12 (1), 67–80. Baron, Reuben M. and David A. Kenny (1986), “The ModeratorMediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considera- Appendix SAMPLE FEATURE ADVERTISING “SUPER DE BOER” 2003 Sales Effects of Attention to Feature Advertisements ———, ———, and Jie Zhang (2007), “Optimal Feature Advertising Design Under Competitive Clutter,” Management Science, 53 (11), 1815–28. Rosbergen, Edward, Rik Pieters, and Michel Wedel (1997), “Visual Attention to Advertising: A Segment-Level Analysis,” Journal of Consumer Research, 24 (3), 305–314. Russo, J. Edward and France Leclerc (1994), “An Eye-Fixation Analysis of Choice Processes for Consumer Nondurables,” Journal of Consumer Research, 21 (September), 274–90. Shankar, Venky and Lakshman Krishnamurthi (1996), “Relating Price Sensitivity to Retailer Promotional Variables and Pricing Policy: An Empirical Analysis,” Journal of Retailing, 72 (3), 249–72. Shaver, J. Myles (2005), “Testing for Mediating Variables in Management Research: Concerns, Implications, and Alternative Strategies,” Journal of Management, 31 (3), 330–53. Sobel, Michael E. (1982) “Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models,” Sociological Methodology, 13, 290–312. Staiger, Douglas and James H. Stock (1997), “Instrumental Variables Regression with Weak Instruments,” Econometrica, 65 (3), 557–86. Stegeman, Mark (1991), “Advertising in Competitive Markets,” American Economic Review, 81 (1), 210–23. 681 Stock, James H., Jonathan H. Wright, and Motohiro Yogo (2002), “A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments,” Journal of Business and Economic Statistics, 20 (4), 518–29. Treistman, Joan and John P. Greg (1979), “Visual, Verbal and Sales Response to Print Ads,” Journal of Advertising Research, 19 (4), 41–47. Van der Lans, Ralf, Rik Pieters, and Michel Wedel (2008), “EyeMovement Analysis of Search Effectiveness,” Journal of the American Statistical Association, 103 (482), 452–61. Villas-Boas, Miquel J. and Russell S. Winer (1999), “Endogeneity in Brand Choice Models,” Management Science, 45 (10), 1324–38. Wedel, Michel and Rik Pieters (2000), “Eye Fixations on Advertisements and Memory for Brands: A Model and Findings,” Marketing Science, 19 (4), 297–312. ——— and ——— (2007), “A Review of Eye-Tracking Research in Marketing,” in Review of Marketing Research, Vol. 4, Naresh K. Malhotra, ed. Armonk, NY: M.E. Sharpe, 123–47. Zhang, Jie (2006), “An Integrated Choice Model Incorporating Alternative Mechanisms for Consumers’ Reactions to In-Store Display and Feature Advertising,” Marketing Science, 25 (3), 278–90.