Sepehr Safari

My main research focus is on customer-firm interactions on social media platforms. I also have research on marketing-finance interface and generative AI. Across my work, I primarily leverage advanced methods to uncover insights valuable for both academic research and practical applications in the marketing field. I utilize various methodologies, including econometric modeling, machine learning, and text analysis, to address complex marketing problems. I am in the job market right now.
 

JOB MARKET PAPER

"The Art of Responding to Customer Online Messages: The Role of Response Standardization"

Social media has become a prevalent venue for customer service, transforming the dynamics of customer-firm interactions. This study investigates the impact of standardized responses (i.e., template responses) on customer satisfaction within these online engagements, a practice favored for its efficiency and consistency. Through an analysis of over 1 million messages between 167 American firms and their customers on X platform, our findings indicate that while standardized responses typically diminish satisfaction, they are particularly effective in addressing complaints from highly dissatisfied customers. Additionally, the uniqueness of customer messages intensifies the negative effects of response standardization. This study underscores the necessity for strategic decisions regarding response strategies, especially with the increasing ease of text generation. These insights offer invaluable guidance for brands striving to balance efficiency with customer satisfaction in their social media engagement strategies.

WORKING PAPERS

• The Game After the Whistle: The Effect of Soccer Matches on Bond Prices" with Gaia Rubera (Bocconi University) 
• Fact-Checking through Crowdsourcing Generative Models" with Yu Ding (Stanford Graduate School of Business) and Gaia Rubera (Bocconi University)