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Scheduling Content on Social Media: Theory, Evidence, and Application

Vamsi K. Kanuri, Yixing Chen and Shrihari (Hari) Sridhar

JM Insights in the Classroom

Full Citation: ​
Kanuri, Yixing Chen, and Shrihari Sridhar (2018), “Scheduling Content on Social Media: Theory, Evidence, and Application,” Journal of Marketing, 82 (6), 89-108.

Insight

  1. Timing of social media posts matters: Posting stories in the morning generated about 8.8% increase in link clicks compared to posting stories in the afternoon and an 11.1% increase compared to posting in the evening.
  2. Sponsored content is most effective when it is scheduled in the afternoon: Sponsored content in the afternoon, on average, accumulated about 21% increase in link clicks compared to sponsored content in the morning because sponsored content serves as an attention drawing trigger when the working memory is low.
  3. Content with negative high-arousal emotions (e.g., anger, terror, anxiety, distress) is most effective in the morning: Such content received 1.6% more link clicks in the morning compared to that in the afternoon, and 7.6% than at night.
  4. Firms need not increase their boosting budgets to improve financial performance: Simply rearranging the posts without allocating additional budget for sponsored content can increase the firm’s gross profits by ~8%.
  5. Boosting spend has diminishing returns: Additional spending on sponsored content resulted only in a marginal increase in gross profits.

Abstract Article
Content platforms (e.g., newspapers, magazines) post several stories every day on their dedicated social media pages and promote some of them using targeted content advertising (TCA). Posting stories allows content platforms to grow their social media audiences and generate digital advertising revenue from the impressions channeled through social media posts’ link clicks. However, optimal scheduling of social media posts and TCA is formidable, requiring content platforms to determine what to post, when to post, and whether, when and how much to spend on TCA to maximize profits. Social media managers lament this complexity, while academic literature offers little guidance. Consequently, the authors draw from literature on circadian rhythms in information processing capabilities to build a novel theoretical framework on social media content scheduling and explain how scheduling attributes (i.e., time of day, content type, and TCA) affect the link clicks metric. They test their hypotheses using a model estimated on 366 days of Facebook post data from a top-50 U.S. newspaper. Subsequently, they build an algorithm that allows social media managers to optimally plan social media content schedules and maximize gross profits. Applying the algorithm to a holdout sample, the authors demonstrate a potential increase in gross profits by at least 8%.

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Topic Areas: ​
Consumer Behavior; Digital Marketing; Marketing Analytics; Marketing Strategy; Social Media Marketing ​​​​

Special thanks to Kelley Gullo and Holly Howe, Ph.D. candidates at Duke University, for their support in working with authors on submissions to this program. 

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Vamsi K. Kanuri is Assistant Professor of Marketing, University of Notre Dame, Mendoza College of Business.

Yixing Chen is Doctoral Student in Marketing, Texas A&M University, Mays School of Business.

Shrihari (Hari) Sridhar Associate Professor of Marketing, Center for Executive Development Professor, Texas A&M University, Mays School of Business.