A Dynamic Model for Digital Advertising: The Effects of Creative Format, Message Content, and Targeting on Engagement

被引:105
作者
Bruce, Norris I. [1 ]
Murthi, B. P. S. [1 ]
Rao, Ram C. [1 ]
机构
[1] Univ Texas Dallas, Naveen Jindal Sch Management, Mkt, Richardson, TX 75083 USA
关键词
online advertising; ad formats (static vs. animated); ad content; dynamic zero-inflated Poisson; particle filtering/smoothing; BANNER ADVERTISEMENTS; MEDIA; WEB; IMPACT; DESIGN;
D O I
10.1509/jmr.14.0117
中图分类号
F [经济];
学科分类号
02 ;
摘要
The authors study the joint effects of creative format, message content, and targeting on the performance of digital ads over time. Specifically, they present a dynamic model to measure the effects of various sizes of static (GIF) and animated (Flash) display ad formats and consider whether different ad contents, related to the brand or a price offer, are more or less effective for different ad formats and targeted or retargeted customer segments. To this end, the authors obtain six months of data on daily impressions, clicks, targeting, and ad creative content from a major U.S. retailer, and they develop a dynamic zero-inflated count model. Given the sparse, nonlinear, and non-Gaussian nature of the data, the study designs a particle filter/Markov chain Monte Carlo scheme for estimation. Results show that carry-over rates for dynamic formats are greater than those for static formats; however, static formats can still be effective for price ads and retargeting. Most notably, results also show that retargeted ads are effective only if they offer price incentives. The study then considers the import of these results for the retailer's media schedules.
引用
收藏
页码:202 / 218
页数:17
相关论文
共 73 条
[1]  
Agarwal Deepak, 2010, APPL STOCH MODEL BUS, V26, P639
[2]  
[Anonymous], INFORMS INT MARK SCI
[3]  
[Anonymous], 2015, Working Paper
[4]  
[Anonymous], 2005, Bayesian statistics and marketing
[5]  
[Anonymous], 2003, Beyond the Kalman Filter: Particle Filters for Tracking Applications
[6]  
Baltas G, 2003, INT J MARKET RES, V45, P505
[7]   Wearout effects of different advertising themes: A dynamic Bayesian model of the advertising-sales relationship [J].
Bass, Frank M. ;
Bruce, Norris ;
Majumdar, Sumit ;
Murthi, B. P. S. .
MARKETING SCIENCE, 2007, 26 (02) :179-195
[8]   Estimating differential lag effects for multiple media across multiple stores [J].
Berkowitz, D ;
Allaway, A ;
D'Souza, G .
JOURNAL OF ADVERTISING, 2001, 30 (04) :59-65
[9]   Online Display Advertising: Modeling the Effects of Multiple Creatives and Individual Impression Histories [J].
Braun, Michael ;
Moe, Wendy W. .
MARKETING SCIENCE, 2013, 32 (05) :753-767
[10]   Incorporating long-term effects in determining the effectiveness of different types of online advertising [J].
Breuer, Ralph ;
Brettel, Malte ;
Engelen, Andreas .
MARKETING LETTERS, 2011, 22 (04) :327-340