September 2020 (Revised July 2022)
Exercise

Artea (B): Including Customer-level Demographic Data

Format:Print
| Language:English
| Pages:2

Abstract

This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The exercises are designed such that the issues of algorithmic bias and discrimination would emerge inductively, “surprising” the students in the act of recommending a strategy that, inadvertently, is discriminating against customers who belong to minority groups. This is achieved via the combination of hands-on exercises, where students would make decisions based on data analyses and visualization, and in-class discussions, where students would defend their proposed strategies, discover the (discriminating) implications of those actions, and discuss possible solutions.

Keywords

Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Demographics; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

Citation

Ascarza, Eva, and Ayelet Israeli. "Artea (B): Including Customer-level Demographic Data." Harvard Business School Exercise 521-022, September 2020. (Revised July 2022.)