Publications

January 2024 (Revised February 2024)
Course Overview Note

Managing Customers for Growth: Course Overview for Students

Managing Customers for Growth (MCG) is a 14-session elective course for second-year MBA students at Harvard Business School. It is designed for business professionals engaged in roles centered on customer-driven growth activities. The course explores the dynamics of... View Details

Keywords: Customer Relationship Management; Decision Making; Analytics and Data Science; Growth Management; Telecommunications Industry; Technology Industry; Financial Services Industry; Education Industry; Travel Industry

March 2022
Supplement

Allianz Customer Centricity: Is Simplicity the Way Forward?

March 2022
Supplement

Allianz Customer Centricity: Is Simplicity the Way Forward?

Web

Success Academy Charter Schools | Information Technology

Featured Case Success Academy Charter Schools The multimedia case follows the story of Eva Moskowitz and Success Academy, a network of high-performing charter schools in New York City. The case explores the role of the government in the... View Details

April 2025
Teaching Note

Tabby: Winning Customers' Digital Wallets

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

Keywords: Fintech; Business Startups; Marketing; Entrepreneurship; Growth and Development Strategy; Business Strategy; Business Model; Competitive Strategy; Financial Services Industry; Middle East; Saudi Arabia; United Arab Emirates

September 2023
Supplement

Design and Evaluation of Targeted Interventions

Targeted interventions serve as a pivotal tool in business strategy, streamlining decisions for enhanced efficiency and effectiveness. This note delves into two central facets of such interventions: first, the design of potent decision guidelines, or targeting... View Details

Keywords: Marketing; Design; Business Strategy; Policy; Retail Industry; Apparel and Accessories Industry; Technology Industry; Financial Services Industry; Telecommunications Industry

August 2021
Teaching Note

Time Out: The Evolution from Media to Markets

2020
Working Paper

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

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; Customer Value and Value Chain; Consumer Behavior; Analytics and Data Science; Mathematical Methods; Retail Industry

SSRN

November 2022 (Revised February 2024)
Exercise

Managing Customer Retention at Teleko

This exercise aims to teach students about 1) Targeting Policies; and 2) Algorithmic decision making, and 3) Retention management. View Details

Keywords: Algorithmic Decision Making; Marketing Strategy; Customer Focus and Relationships

March 2022
Teaching Note

Allianz Customer Centricity: Is Simplicity the Way Forward?

Teaching Note for HBS Case No. 522-008. View Details

September 2021
Supplement

Interview with Julio Bruno (Time Out)

Video supplement for HBS Case No. 520-128. View Details

August 2021 (Revised February 2022)
Supplement

Melissa Wood Health: How to Win in the Creator Economy

August 2021 (Revised January 2024)
Teaching Note

Melissa Wood Health: How to Win in the Creator Economy

February 2018
Article

Retention Futility: Targeting High-Risk Customers Might Be Ineffective.

Companies in a variety of sectors are increasingly managing customer churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While there is a vast literature on developing churn prediction models... View Details

Keywords: Retention/churn; Proactive Churn Management; Field Experiments; Heterogeneous Treatment Effect; Machine Learning; Customer Relationship Management; Risk Management