Optimizing mobile in-app advertising effectiveness using app publishers-controlled factors

Abstract

Mobile in-app advertising has become one of the most popular business advertising platforms in recent years. This relatively new advertising strategy’s annual spending has increased dramatically in recent years. Despite its practical success, the background theory for mobile in-app advertising is still in its infancy. This type of advertising also sees the emergence of new participants, such as ad networks and app publishers, which leads to the development of new theoretical constructs and more nuanced conceptual relationships on top of popularly accepted frameworks, e.g. Mobile Advertising Effectiveness Framework. This study especially looks at app publishers’ roles, which have received the least attention in the advertising literature and are almost non-existent in the previous effectiveness frameworks. The empirical goal of this study was to assess the moderating effects of ad space characteristics on the effectiveness of mobile in-app advertising. To test the research’s conceptual model, a 24-factorial online experiment was set up. Accordingly, this study established a common goal for participants and a metric to measure that common effectiveness goal. Ultimately, the model was successfully tested by both Moderated Regression Analysis and Multigroup Moderation Analysis techniques with data from over 15,000 ad impressions and over 800 ad clicks from thousands of mobile users in over 160 countries around the world. The study theoretically found that publishers can significantly moderate the effects controlled by advertisers, and users, which can practically help increase the revenue of advertising through designing and delivering ad spaces on their applications.

In-app advertising: a systematic literature review and implications for future research

“…The influence of antecedents such as advertisement types affects the click-through rate (Rosenkrans and Myers, 2018), advertising avoidance behaviors (Keem and Lee, 2018), purchase intention (Sung, 2021) and social media sharing (Sung et al ,2022). The interactive effects of publisher-controlled factors, namely, ad space size, ad space position ad space timing (Truong et al , 2019), and ad space duration (Truong, 2023), with advertiser-controlled factors, namely, ad type, ad medium, location (Truong et al , 2019) and time (Truong, 2023), on the click-through rate were investigated. Wang and Chou (2019) examine how the degree of congruity between promoted products in interstitial ads and the app environment affects consumer response toward the ad.…”

“…Publishers can either sell their inventory directly to ad networks or buy-side or engage in real-time bidding (Kaplan, 2021). Truong (2023) found that the optimal combination of publisher-controlled factors such as duration, timing, size and position of the ad space significantly improves the click-through rate of in-app advertising.…”

“…The thematic analysis indicates the relationship between the two themes in the literature, namely, ad platform optimizationad effectiveness (Truong, 2023) and ad effectiveness -…”

“…The thematic analysis indicates the relationship between the two themes in the literature, namely, ad platform optimization – ad effectiveness (Truong, 2023) and ad effectiveness – mobile app user behavior (Mattke et al , 2021). The click-through rate was one of the outcome variables that was investigated by several researchers for the optimal combination of in-app advertisement factors and the optimal sequencing of in-app advertisements (Adikari and Dutta, 2020; Sun et al , 2017; Truong et al , 2019).…”