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  • March 2021
  • Supplement
  • HBS Case Collection

Artea (A), (B), (C), and (D): Designing Targeting Strategies

By: Eva Ascarza and Ayelet Israeli
  • Format:Electronic
  • | Language:English
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Abstract

Power Point Supplement to Teaching Note for HBS No. 521-021,521-022,521-037,521-043. 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

Targeted Advertising; Targeting; Algorithmic Data; Bias; A/B Testing; Experiment; Advertising; Gender; Race; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

Citation

Ascarza, Eva, and Ayelet Israeli. "Artea (A), (B), (C), and (D): Designing Targeting Strategies." Harvard Business School PowerPoint Supplement 521-719, March 2021.
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About The Authors

Eva Ascarza

Marketing
→More Publications

Ayelet Israeli

Marketing
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    Banorte Móvil: Data-Driven Mobile Growth

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More from the Authors
  • Banorte Móvil: Data-Driven Mobile Growth By: Ayelet Israeli and Carla Larangeira
  • Managing Customers in the Digital Era By: Eva Ascarza
  • Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT) By: Eva Ascarza and Ayelet Israeli
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