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Article

Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

By: Eva Ascarza and Ayelet Israeli

An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details

Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods

February 2024 (Revised February 2024)
Teaching Note

Travelogo: Understanding Customer Journeys

By: Eva Ascarza and Ta-Wei Huang

Teaching Note for HBS Exercise 524-044. The exercise aims to teach students about 1) Customer Segmentation; and 2) constructing buying personas, 3) Get actionable insights from clickstream data. View Details

Keywords: Customer Relationship Management; Analysis; Analytics and Data Science; Marketing Strategy; Segmentation; Consumer Behavior; Travel Industry; United States

November 2023 (Revised March 2024)
Technical Note

Customer Data Privacy

By: Eva Ascarza and Ta-Wei Huang

This note provides an overview of the evolving landscape of customer data privacy in 2023. It highlights two pivotal aspects that make privacy a central concern for businesses: building and maintaining customer trust and navigating the intricate regulatory... View Details

Keywords: Customer Relationship Management; Governance Compliance; Governing Rules, Regulations, and Reforms; Risk and Uncertainty; Reputation; Trust; Information Management; Retail Industry; Technology Industry; Financial Services Industry; Telecommunications Industry; Europe; United States

October 2021
Article

Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach

By: Nicolas Padilla and Eva Ascarza

The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details

Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Programs; Consumer Behavior; Analysis

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July 2021 (Revised January 2022)
Teaching Note

Amazon Shopper Panel: Paying Customers for Their Data

By: Eva Ascarza and Ayelet Israeli

Teaching Note for HBS Case No. 521-058. View Details

September 2020 (Revised June 2023)
Supplement

Spreadsheet Supplement to Artea Teaching Note

By: Eva Ascarza and Ayelet Israeli

Spreadsheet Supplement to Artea Teaching Note 521-041. 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... View Details

Keywords: Targeted Advertising; Algorithmic Data; Bias; Advertising; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

September 2020 (Revised July 2022)
Exercise

Artea (D): Discrimination through Algorithmic Bias in Targeting

By: Eva Ascarza and Ayelet Israeli

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... View Details

Keywords: Targeted Advertising; Discrimination; Algorithmic Data; Bias; Advertising; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

July–August 2024
Article

Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals

By: Ta-Wei Huang and Eva Ascarza

Firms are increasingly interested in developing targeted interventions for customers with the best response, which requires identifying differences in customer sensitivity, typically through the conditional average treatment effect (CATE) estimation. In theory, to... View Details

Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing Strategy

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March 2024
Case

Unintended Consequences of Algorithmic Personalization

By: Eva Ascarza and Ayelet Israeli

“Unintended Consequences of Algorithmic Personalization” (HBS No. 524-052) investigates algorithmic bias in marketing through four case studies featuring Apple, Uber, Facebook, and Amazon. Each study presents scenarios where these companies faced public criticism for... View Details

Keywords: Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Customization and Personalization; Technology Industry; Retail Industry; United States

October 2023 (Revised February 2024)
Supplement

Managing Customer Retention at Teleko

By: Eva Ascarza and Ta-Wei Huang

June 2023
Simulation

Artea Dashboard and Targeting Policy Evaluation

By: Ayelet Israeli and Eva Ascarza

Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea... View Details

September 2020 (Revised July 2022)
Supplement

Spreadsheet Supplement to Artea (B) and (C)

By: Eva Ascarza and Ayelet Israeli

Spreadsheet Supplement to "Artea (B): Including Customer-level Demographic Data" and "Artea (C): Potential Discrimination through Algorithmic Targeting" View Details

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

September 2020 (Revised July 2022)
Exercise

Artea (C): Potential Discrimination through Algorithmic Targeting

By: Eva Ascarza and Ayelet Israeli

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... View Details

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

September 2020 (Revised July 2022)
Teaching Note

Algorithmic Bias in Marketing

By: Ayelet Israeli and Eva Ascarza

Teaching Note for HBS No. 521-020. This note focuses on algorithmic bias in marketing. First, it presents a variety of marketing examples in which algorithmic bias may occur. The examples are organized around the 4 P’s of marketing – promotion, price, place and... View Details

Keywords: Marketing; Race; Ethnicity; Gender; Diversity; Prejudice and Bias; Decision Making; Ethics; Customer Relationship Management; Retail Industry; Technology Industry; Apparel and Accessories Industry; United States

May 2016 (Revised November 2022)
Teaching Note

RegionFly: Cutting Costs in the Airline Industry

By: Susanna Gallani and Eva Labro

Teaching Note for HBS No. 116-047. View Details

November 2005
Article

Importation as Innovation: Transposing managerial practices across fields

By: Eva Boxenbaum and Julie Battilana

Keywords: Innovation and Invention; Management; Practice

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January 2024 (Revised February 2024)
Exercise

Travelogo: Understanding Customer Journeys

By: Eva Ascarza, Nicolas Padilla and Oded Netzer

In late May 2023, Sarah Merino, the newly appointed manager of the Customer Insights group at Travelogo—an online travel booking platform—initiates a comprehensive analysis of clickstream data to understand the varied behaviors and needs of their users. In preparation... View Details

Keywords: Customer Relationship Management; Analysis; Analytics and Data Science; Marketing Strategy; Segmentation; Consumer Behavior; Travel Industry; United States

March 17, 2021
Other Article

Beyond Pajamas: Sizing Up the Pandemic Shopper

By: Ayelet Israeli, Eva Ascarza and Laura Castrillo

A first look at how the COVID-19 pandemic impacted e-commerce apparel shopping in the US and the UK. Extensive analysis and interactive graphics utilizing millions of transactions.
While the pandemic is still playing out, our preliminary investigations... View Details

2023
Working Paper

The Customer Journey as a Source of Information

By: Nicolas Padilla, Eva Ascarza and Oded Netzer

In the face of heightened data privacy concerns and diminishing third-party data access, firms are placing increased emphasis on first-party data (1PD) for marketing decisions. However, in environments with infrequent purchases, reliance on past purchases 1PD... View Details

Keywords: Customer Journey; Privacy; Consumer Behavior; Analytics and Data Science; AI and Machine Learning; Customer Focus and Relationships

November 2019 (Revised December 2023)
Teaching Note

Othellonia: Growing a Mobile Game

By: Eva Ascarza, Tomomichi Amano and Sunil Gupta

Teaching note for case 520-016 View Details

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