EXPRESS: A New Livestream Retail Analytics Framework to Assess the Sales Impact of Emotional Displays

At the intersection of technology and marketing, the authors develop a framework to unobtrusively detect salespersons’ faces and simultaneously extract six emotions: happiness, sadness, surprise, anger, fear, and disgust. They analyze 99,451 sales pitches on a livestream retailing platform and match them with actual sales transactions. Results reveal that each emotional display, including happiness, uniformly exhibits a negative U-shaped effect on sales over time. The maximum sales resistance appears in the middle rather than at the beginning or the end of sales pitches. Taken together, in one-to-many screen-mediated communications, salespersons should sell with a straight face. In addition, the authors derive closed-form formulae for the optimal allocation of the presence of a face and emotional displays over the presentation span. In contrast to the U-shaped effects, the optimal face presence wanes at the start, gradually builds to a crescendo, and eventually ebbs. Finally, they show how to objectively rank salespeople and circumvent biases in performance appraisals, thereby making novel contributions to people analytics. This research integrates new types of data and methods, key theoretical insights, and important managerial implications to inform the expanding opportunity that livestreaming presents to marketers to create, communicate, deliver, and capture value.

Building a Strategic Framework for Retail Supply Chain Analytics

This chapter attempts to answer the question, “Why investments in analytics haven't always improved the performance?” The concept of strategic fit between retail analytics and retail supply chain is established. It argues that a strategic framework blending analytics and supply chain is imperative for superior performance over time. Such a framework helps to clarify goals of supply chain analytics and identify managerial actions that can improve supply chain performance in terms of desired goals. It also describes major obstacles that retailers need to overcome for making supply chain analytics a source of competitive advantage. This chapter is expected to provide a strategic understanding of retail supply chain analytics.