Improving Social Media Video Advertising Acceptance Using Priming: Evidence from Big Data Analysis

Wen Xie, Ron Dotsch, Maarten Bos, Yozen Liu
Event AMS 2023
Research Areas Behavioral Science

Video advertising has drawn much attention from marketers and researchers due to its remarkable performance in boosting traffic and communicating a clear picture of products. We study ad acceptance of Story ads, a unique form of social media video ads. As Story ads are popular among major online social platforms such as Instagram and Snapchat but understudied in academia, it is crucial and timely to understand their effectiveness. To that end, we collect a large-scale first-party dataset with 8,260,689 individual-level observations from a top-ranked American technology company. Using the Story preceding each ad as a natural prime, we investigate how two types of Story-ad congruence: media format (i.e., video or image) and content (17 types, e.g., sports and gaming), affect ad acceptance. After accounting for endogeneity issues using propensity score weighting, the results show that both Story-ad format and content congruence significantly generate additional ad viewing time. However, the format congruence between video Stories and video ads has an attenuating effect. Our research makes theoretical and managerial contributions. The findings offer insights to marketers and publishers and can be helpful for ad placement, ranking, and recommendation systems.

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