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Artea: Designing Targeting Strategies
Ascarza, Eva; Israeli, AyeletCaso HBS-521021-EMarketingThis 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 algorithmDesde 8,20 €
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Amazon Shopper Panel: Paying Customers for Their Data
Ascarza, Eva; Israeli, AyeletCaso HBS-521058-EMarketingThis case introduces a new Amazon program that has consumers upload their receipts from transactions outside of Amazon, in exchange for money. Through the discussion, the case aims to explore issues in customers' privacy in the digital age, the value of customers' own data, and the change in regulations aimed to protect consumers that move companies from using third party data to first party data. In addition, the case offers an opportunity to di...Desde 8,20 €
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Artea (C): Potential Discrimination through Algorithmic Targeting
Ascarza, Eva; Israeli, AyeletCaso HBS-521037-EMarketingThis 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 algorithmDesde 5,74 €
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Artea (B): Including Customer-level Demographic Data
Ascarza, Eva; Israeli, AyeletCaso HBS-521022-EMarketingThis 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 algorithmDesde 5,74 €
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Artea (D): Discrimination through Algorithmic Bias in Targeting
Ascarza, Eva; Israeli, AyeletCaso HBS-521043-EMarketingThis 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,...Desde 5,74 €