Estimating the capacity of the Location-Based Advertising channel

Abstract

Delivering 'relevant' advertisements to consumers carrying mobile devices is regarded by many as one of the most promising mobile business opportunities. The relevance of a mobile ad depends on at least two factors:(1) the proximity of the mobile consumer to the product or service being advertised, and (2) the match between the product or service and the interest of the mobile consumer. The interest of the mobile consumer can be either explicit (expressed by the mobile consumer) or implicit (inferred from user characteristics). This paper tries to empirically estimate the capacity of the Mobile Advertising channel, i.e. the number of relevant ads that can be delivered to mobile consumers. The estimations are based on a simulated mobile consumer population and simulated mobile ads. Both of the simulated data sets are realistic and derived based on real-world data sources about population geo-demographics, businesses offering products or services, and related consumer surveys. The estimations take into consideration both the proximity and interest requirements of mobile ads, i.e. ads are delivered only to mobile consumers that are close-by and are interested, where interest is either explicit or implicit. Results show that the capacity of the Location-Based Advertising channel is rather large, which is evidence for a strong business case, but it also indicates the need for user-control of the received mobile ads.

Investigating the Effects of Location-Based Advertising in the Supermarket: Does Goal Congruence Trump Location Congruence?

“…As we have discussed above, location congruent messages will be more likely to be perceived as relevant for consumers than location incongruent messages, but only if consumers have an actual interest in the advertised product. In line with previous theorizing (Gidofalvi et al, 2008), we therefore expected that location-congruent advertising would be Effects of location-based advertising 12 especially likely to be in line with consumers' goals, and hence more likely to result in increased purchase behavior, decreased perceptions of intrusiveness and more positive ad attitudes, under conditions of high goal relevance. Therefore, our second set of hypotheses was:…”

“…The results underline the pivotal role of goal relevance, as this factor not only moderated the effect of Effects of location-based advertising 29 location congruence on behavior, but also had strong main effects on behavior and perceptions of the ad. Gallego et al 2013 Consumer acceptance Survey Gidofalvi et al 2008 Capacity of the LBA channel Simulation study Hühn et al 2012 Consumer impact Experimental study Junglas et al 2008 Consumer acceptance Survey Lee and Hill 2013 Consumer acceptance Survey Lee et al 2012 Consumer impact Interviews with consumers Lin et al 2013 Consumer acceptance Survey Okazaki 2011…”

“…However, there is no empirical research on this. This is problematic because, as Gidofalvi et al (2008) have pointed out, location congruence and relevance are distinct constructs. After all, it is unlikely that knowing where a consumer is will always be sufficient to know what the consumer is up to.…”

“…In the present paper, we therefore make a distinction between location congruence and relevance. According to Gidofalvi et al (2008), LBA should not only be tailored to consumers' location, but also to their interests, in order to create involving advertising content . Adopting this reasoning, we expected that goal relevance is not the inevitable result of location congruence but rather an important additional predictor of advertising effectiveness.…”

Boost Movie Ticket Sales by Location-Based Advertising: A Bayesian VAR Approach

“…Banerjee and Dholakia (2008) examined the effectiveness of mobile advertising through an experiment that manipulated the location and what the recipients were doing. Gidofalvi, Larsen, and Pedersen (2008) empirically estimated the capacity of the mobile advertising channel based on simulated mobile consumer population from real-world sources and simulated mobile ads offering both the proximity and interest requirements. Xu, Oh, and Teo (2009) empirically examined the effects of multimedia advertisement versus text-based advertisements on consumer perceptions and behaviors in a simulated LBA environment, which showed that multimedia LBA messages led to more favorable attitude, increased the intention to use the LBA application, and had significant impact on purchase intention.…”