Social Influence in Social Advertising: The Differential Impact of Likes on User Engagement
A recent trend among social media platforms, such as Instagram and Facebook, is the reassessing of how “likes” and engagement metrics influence user behavior and advertising effectiveness. Instagram, for instance, has been testing features that hide like counts to reduce social pressure and foster genuine engagement. Our Journal of Marketing study reveals that displaying “likes” in social advertising affects users' liking and clicking behavior differently, depending on the interplay between normative and informational social influence. These insights underscore the importance of understanding social influence when developing advertising strategies on social media platforms.
Through a large-scale field experiment on a social media platform, we investigate the impacts of displaying social cues such as “likes” on user engagement in the context of social advertising. We discovered that displaying “likes” in ads can influence two key outcomes: the likelihood of users liking the ad and their propensity to click on it. Our findings reveal that, although the presence of the first “like” can significantly boost both liking and clicking rates, additional “likes” enhance the liking rate but fail to impact click-through rates.
Informational vs. Normative Influence
We found that social influence plays a crucial role in viewer responses to advertising. Specifically, we identified two types of social influence: informational and normative. Informational social influence occurs when individuals rely on others’ actions as evidence to inform their decisions. In contrast, normative social influence reflects viewers’ desire to conform to social norms and gain approval from others. Our study demonstrates that liking an ad is more influenced by normative social influence, while clicking is primarily driven by informational social influence.
When users see a single “like” on an ad, they are more likely to engage with it. This initial “like” serves as a social cue, encouraging others to follow suit. However, as more “likes” are displayed, the effect on clicking diminishes. This is because users may perceive the additional “likes” as being influenced by social norms rather than genuine interest in the product. Consequently, the informational value of these “likes” can weaken, leading to a crowding-out effect on clicking behavior.
Adaptations for Advertisers
Our findings have important implications for marketers and advertisers. For brands that focus on building awareness and enhancing their image, employing normative social influence through visible “likes” can be an effective strategy. In such a case, companies should consider targeting consumers who are more susceptible to normative social influence, such as those who frequently engage with friends on social media. By doing so, advertisers can amplify the impact of “likes” on their ads.
On the other hand, for performance-driven advertising, where the goal is to maximize click-through rates and drive conversions, marketers should be cautious. While accumulating “likes” can improve brand perception, more and more “likes” may not translate into immediate actions, such as clicks. Advertisers should assess the balance between normative and informational social influences when designing their campaigns.
Platform Design Considerations
The research also highlights the importance of social media platform design in shaping advertising effectiveness. Platforms that feature normative social influence can encourage higher liking rates using these social cues, but this strategy may inadvertently dilute their informational value. Therefore, social media platforms should consider how their features impact the effectiveness of social advertising.
As platforms evolve, advertisers and firms must adapt their strategies accordingly. For example, they might consider displaying only one or a few “likes” to maximize click-through rates, especially for well-known brands or for targeted consumers. This approach can help maintain the perceived informational value of the “likes” displayed.
Harnessing Social Influence in Real Estate
Many real estate firms leverage social advertising to boost engagement and strengthen brand visibility. However, they can fine-tune and align branding and performance objectives more precisely by harnessing informational and normative social influence. Up-and-coming real estate agents can increase ad clicks and user engagement by offering expert, information-rich, fact-based content that helps the audience make informed decisions rather than relying on social cues or trends. In contrast, established real estate agents can use social proofs and validation to emphasize that they are trustworthy, popular, and appealing.
Additionally, real estate firms can tailor targeting-based strategies to users’ historical online behavior, then combine both social influences to design dual-purpose campaigns. “Likes,” testimonials, and endorsements can be used to build brand awareness with audiences that are driven by social validation, while personalized data-driven materials can be used to engage and convert those who value informative content. This balanced, evidence-based approach to social advertising can yield measurable performance improvement for all real estate segments.
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Recommended Reading
Huang, Shan and Song Lin (2025), “Do More Likes Lead to More Clicks? Evidence from a Field Experiment on Social Advertising,” Journal of Marketing, 89(5), 88-110. https://doi.org/10.1177/00222429241307608
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About the Authors
Shan Huang, PhD
Assistant Professor, University of Hong Kong (Hong Kong)
Dr. Shan Huang’s (PhD – Massachusetts Institute of Technology) research focuses on the digital economy, social networks, and business analytics, and her current work aims to understand the business value and social implications of new social media. Specifically, her studies examine how social advertising and social referral affect product virality, how emotions shape online content diffusion, and how weak ties can or cannot break people out of the echo chamber, in massive social networks. Dr. Huang’s research has been published in prominent management journals, including Marketing Science and the Journal of Management Information Systems. She has been collaborating closely with the leading tech firms (e.g., Tencent) to understand the cutting-edge digital phenomena and the tools such as A/B testing.
Song Lin, PhD
Associate Professor, University of Science and Technology (Hong Kong)
Dr. Song Lin’s (PhD – Massachusetts Institute of Technology) research interests include generative AI, advertising, pricing, platform design, new product and innovation, and consumer attention, search and learning. Dr. Song has published in journals such as Journal of Marketing, Marketing Science, Management Science, and Journal of MarketingResearch, among others. His research has also been featured in more than 100 media outlets including the New York Times, Financial Times, Wall Street Journal, Forbes, Bloomburg, NBC, BBC, NPR, and more. Dr. Song serves as associate editor for Marketing Science and on the editorial board of the Journal of Marketing Research.
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KCRR 2026 June -
