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- 2025
- Working Paper
In Privacy We Trust: The Effect of Privacy Regulations on Data Sharing Behavior
By: Ozge Demirci, Ayelet Israeli and Eva Ascarza
This paper studies the impact of privacy policies on consumer data-sharing behavior, focusing on policy changes in California and Virginia that took effect in 2023. Using data from a leading customer engagement app in the United States, where users upload shopping... View Details
Keywords: Privacy; Privacy Regulation; Data Sharing; Digital Platforms; Policy; Surveys; Behavior; Public Opinion; California; Virginia
- July 2025
- Exercise
Travelogo: Customer Segmentation Instructions
By: Eva Ascarza
- June 2025
- Simulation
Teleko: Managing Customer Retention
By: Eva Ascarza
Supplement to the A Case, No. 523-005. This interactive tool is designed to enhance engagement with the Managing Customer Retention at Teleko case by allowing the student to explore and analyze key data from the experiment run in July (“July... View Details
- June 2025
- Simulation
Travelogo: Customer Segmentation
By: Eva Ascarza and Noah Ahmadi
This interactive tool is designed to enhance engagement with the Travelogo: Understanding Customer Journeys case by allowing the student to explore the company's data. Through this tool, the student can examine the variables used for segmentation, analyze the resulting... View Details
- April 2025
- Teaching Note
Tabby: Winning Customers' Digital Wallets
By: Eva Ascarza
Teaching Note for HBS Case No. 524-056. Tabby, a Saudi-based fintech founded in 2019, rapidly became one of the MENA region’s first unicorns by offering buy-now-pay-later (BNPL) services with a unique twist: instead of charging end consumers, it partnered with... View Details
- March 2025
- Teaching Note
Unintended Consequences of Algorithmic Personalization
By: Ayelet Israeli and Eva Ascarza
Teaching Note for HBS Case No. 524-052. View Details
- 2025
- Working Paper
Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning
Reinforcement learning (RL) offers potential for optimizing sequences of customer interactions by modeling the relationships
between customer states, company actions, and long-term value. However, its practical implementation often faces significant
challenges.... View Details
- 2025
- Working Paper
Policy-Aware Experimentation: Strategic Sampling for Optimized Targeting Policies
By: Yi-Wen Chen, Eva Ascarza and Oded Netzer
Firms often rely on randomized experiments to estimate customer-level treatment effects for targeting policies. Standard "test-then-learn" approaches typically sample customers uniformly to optimize estimation accuracy but ignore economic objectives, leading to... View Details
- November 2024
- Article
The Customer Journey as a Source of Information
By: Nicolas Padilla, Eva Ascarza and Oded Netzer
We introduce a probabilistic machine learning model that fuses customer click-stream data and purchase data within and across journeys. This approach addresses the critical business need for leveraging first-party data (1PD), particularly in environments with... View Details
- 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
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
By: Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
- April 2024
- Article
Detecting Routines: Applications to Ridesharing CRM
By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal... View Details
- March 2024 (Revised April 2024)
- Case
Angel City Football Club: Scoring a New Model
By: Jeffrey F. Rayport, Jennifer Fonstad and Nicole Tempest Keller
In January 2024, Kara Nortman, Julie Uhrman, and Natalie Portman, the founders of Angel City Football Club (ACFC) were developing the club’s first three-year strategic plan. Founded in 2020, ACFC had a star-studded investor group, including Portman and celebrities such... View Details
- 2025
- Working Paper
Greenlighting Innovative Projects: How Evaluation Format Shapes the Perceived Feasibility of Early-Stage Ideas
By: Jacqueline N. Lane, Simon Friis, Tianxi Cai, Michael Menietti, Griffin Weber and Eva C. Guinan
The evaluation of innovative early-stage projects is essential for allocating limited resources. We
investigate how the evaluation format affects the identification of feasibility issues through a
field experiment at a leading research university. Experts were... View Details
- March 2024
- Supplement
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Peter Fader, Bruce G.S. Hardie and Michael Ross
This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in understanding the customer base, prompting an... View Details
- March 2024
- Supplement
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Bruce Hardie, Peter S. Fader and Michael Ross
This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in understanding the customer base, prompting an... View Details
- March 2024
- Supplement
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Bruce Hardie, Peter S. Fader and Michael Ross
This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in understanding the customer base, prompting an... View Details
- March 2024
- Teaching Note
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Peter S. Fader, Bruce Hardie and Michael Ross
Teaching Note for HBS Case No. 524-046. This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in... View Details
- March 2024
- Case
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Bruce Hardie, Michael Ross and Peter S. Fader
This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in understanding the customer base, prompting an... View Details
- 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