The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Analyzing the Relationship Between Organic and Sponsored Search Advertising: Positive, Negative, or Zero Interdependence?
Open accessAbstract
The phenomenon of paid search advertising has now become the most predominant form of online advertising in the marketing world. However, we have little understanding of the impact of search engine advertising on consumers' responses in the presence of organic listings of the same firms. In this paper, we model and estimate the interrelationship between organic search listings and paid search advertisements. We use a unique panel data set based on aggregate consumer response to several hundred keywords over a three-month period collected from a major nationwide retailer store chain that advertises on Google. In particular, we focus on understanding whether the presence of organic listings on a search engine is associated with a positive, a negative, or no effect on the click-through rates of paid search advertisements, and vice versa for a given firm. We first build an integrated model to estimate the relationship between different metrics such as search volume, click-through rates, conversion rates, cost per click, and keyword ranks. A hierarchical Bayesian modeling framework is used and the model is estimated using Markov chain Monte Carlo methods. Our empirical findings suggest that click-throughs on organic listings have a positive interdependence with click-throughs on paid listings, and vice versa. We also find that this positive interdependence is asymmetric such that the impact of organic clicks on increases in utility from paid clicks is 3.5 times stronger than the impact of paid clicks on increases in utility from organic clicks. Using counterfactual experiments, we show that on an average this positive interdependence leads to an increase in expected profits for the firm ranging from 4.2% to 6.15% when compared to profits in the absence of this interdependence. To further validate our empirical results, we also conduct and present the results from a controlled field experiment. This experiment shows that total click-through rates, conversions rates, and revenues in the presence of both paid and organic search listings are significantly higher than those in the absence of paid search advertisements. The results predicted by the econometric model are also corroborated in this field experiment, which suggests a causal interpretation to the positive interdependence between paid and organic search listings. Given the increased spending on search engine-based advertising, our analysis provides critical insights to managers in both traditional and Internet firms.
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Cites
Preattentive Mere Exposure Effects
Janiszewski, C. (1993) · Journal of Consumer Research · doi:10.1086/209356 · Cited by 455 · cited 2×
“…Hawkins and Hoch, 1992; Law, and Braun, 2000), and the mere exposure effect (the formulation of a positive affect from exposure to a brief stimulus, Janiszewski 1993) both illustrate changes in consumer behavior following a single exposure to a stimuli without awareness of the prior exposure.”
BackgroundFrom Generic to Branded: A Model of Spillover in Paid Search Advertising
Rutz, O. J., & Bucklin, R. E. (2011) · Journal of Marketing Research · doi:10.1509/jmkr.48.1.87 · Cited by 360
Cited by
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Kannan, P. K., & Li, H. “. (2017) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2016.11.006 · Cited by 1,707
Ursu, R. M. (2018) · Marketing Science · doi:10.1287/mksc.2017.1072 · Cited by 328
Examining the Impact of Ranking on Consumer Behavior and Search Engine Revenue
Ghose, A., Ipeirotis, P. G., & Li, B. (2014) · Management Science · doi:10.1287/mnsc.2013.1828 · Cited by 299
Self-citationThe personalization-privacy paradox: Implications for new media
Aguirre, E., Roggeveen, A. L., Grewal, D., & Wetzels, M. (2016) · Journal of Consumer Marketing · doi:10.1108/jcm-06-2015-1458 · Cited by 251
Mapping the customer journey: Lessons learned from graph-based online attribution modeling
Anderl, E., Becker, I., von Wangenheim, F., & Schumann, J. H. (2016) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2016.03.001 · Cited by 186
Metadata
- Authors
- Yang, S., & Ghose, A.
- Venue
- Marketing Science
- Published
- 2010-07
- Volume
- 29
- Issue
- 4
- Pages
- 602-623
- ISSN
- 0732-2399 (ISSN-L)
- 1526-548X
- OpenAlex
- W3125251328
- Cited by
- 374
- References
- 2
- FWCI
- 88.69
- Type
- journal article
- Language
- en
- Open access
- green
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