Research

Selected Working Papers

Effectiveness of Micro Ads on Television

• with Beth L. Fossen and Inyoung Chae

• Revising for 4th round review at Journal of Marketing (Minor Revision) 

As media viewers continue to shift expectations toward ads, TV advertisers and networks are showing an increased interest in short ad formats, such as micro ads (i.e., ads that are 10 seconds or less). Yet, limited research has considered micro ads on TV. We use a multimethod approach to investigate the effectiveness of micro TV ads and, more broadly, assess the relationship between TV ad length and ad effectiveness. Our analyses of observational data leverage retailers’ TV advertising, web traffic, and online sales. We find that micro TV ads spur more traffic to the retailers’ websites post-ad than longer ads. Micro and non-micro TV ads exhibit similar direct impacts on online sales, but micro ads can indirectly increase online sales more by driving increased traffic. We find that viewers’ impatience for longer ads may explain the effectiveness of micro TV ads. Results from an experiment provide additional support for these findings. Our analyses further probe the impact of ad length on ad effectiveness beyond micro ads and find support for the effectiveness of shorter TV ads more broadly. Our research provides timely insights for advertisers and TV networks seeking economical, attractive ad inventory.

Effectiveness of Influencer Marketing for Political Campaigns

• with Beth L. Fossen

• Job market paper

• Preparing for submission to Journal of Marketing Research.

Social media influencers are playing an increasingly important role in digital marketing given their ability to affect consumers. Such influence has extended to political campaigns, especially as many social media platforms restrict traditional political advertisements. Consequently, influencer marketing (IM) has emerged as an attractive digital advertising option for political candidates. Yet, little is known about whether IM is effective in impacting voters. We investigate the impact of sponsored influencer activities on Twitter on voter preference and social media engagement, using data from the 2020 U.S. Democratic Party presidential primary. To detect sponsored influencer posts that lack sponsorship disclosures, we employ a text-based machine learning classification method, ensuring that the data comprehensively captures the IM activities employed during the election. We find that positively valenced IM about the political candidates is associated with increased voter preference for the candidate. We further find that effectiveness of political IM is contingent on emotionality of the IM content. Specifically, the impact of positively valenced IM on voter preference is amplified with low emotional intensity, whereas negatively valenced IM is associated with decreased voter preference for the attacked candidate only when it is highly emotional. Such patterns are also observed when we consider social media engagement as the outcome. Our research provides valuable insights for political marketers on strategizing effective IM campaigns and for voters in understanding the impact of political IM.

Dynamics of Influencer Marketing Strategy

• with Maximilian Matthe and Xian Gu

• Preparing for submission to Marketing Science.

Livestream commerce has emerged as a disruptive retail channel for brands to connect with consumers and drive product sales. Through its immersive, video-based engagement led by sponsored influencers, livestreams facilitate a streamlined customer journey to promote on-the-spot purchases that differ significantly from traditional online shopping. However, livestreams provide fleeting experiences, unlike static social media content which offers enduring engagement and allows consumers to revisit influencer content, thus posing a challenge for facilitating sales beyond the live sessions. In addition, the temporal dynamics of these livestream sessions can differentially impact sales over time. For instance, a brand can choose to employ a burst strategy where an intense concentration of livestreams is hosted within a short timeframe to drive immediate sales. Alternatively, a drip strategy can be used, distributing livestreams consistently over time to mitigate oversaturation and consumer fatigue. We leverage a rich dataset from TikTok (Douyin) spanning over 100,000 products and 7 million livestreams to investigate the impact that livestreams have on post-session sales, specifically the dynamic effects of different temporal distributions of livestreams. Our findings reveal that while a drip strategy leads to diminishing returns on additional livestreams, employing a burst strategy significantly multiplies their impact on sales. This study provides data-driven insights, enabling brands to strategically plan their influencer marketing campaigns and optimize reach through livestream channels.

Selected Works in Progress

"Online Brand Safety and Political Content," with Beth L. Fossen, and Alexander Bleier

"When Influencers Go Political: The Impact on Follower Dynamics," with Maximilian Matthe

"Impact of AI on Firm Data Breach and Subsequent Word of Mouth," with Ben Lee

"Promoting Music on TikTok"