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Artea (C): Potential Discrimination through Algorithmic Targeting
Ascarza, Eva; Israeli, AyeletCase 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 algorithmStarting at €5.74
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E-Commerce Analytics for CPG Firms(C): Free Delivery Terms
Israeli, Ayelet; Lisitsyn, Fedor TedCase HBS-521080-EMarketingThe E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data chStarting at €5.74
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Artea (B): Including Customer-level Demographic Data
Ascarza, Eva; Israeli, AyeletCase 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 algorithmStarting at €5.74
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Artea: Designing Targeting Strategies
Ascarza, Eva; Israeli, AyeletCase 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 algorithmStarting at €8.20
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eGrocery and the Role of Data for CPG Firms
Israeli, Ayelet; Lisitsyn, Fedor Ted; Irwin, Mark A.Case HBS-521077-EMarketingThis notes provides information about the eGrocery industry and how traditional CPG companies handle this channel and potential data. It is recommended to use together with a series of exercises entitled: "E-Commerce Analytics for CPG Firms (A), (B), and (C)."Starting at €8.20
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Artea (D): Discrimination through Algorithmic Bias in Targeting
Ascarza, Eva; Israeli, AyeletCase 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,...Starting at €5.74