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      • January 2021 (Revised March 2021)
      • Exercise

      E-Commerce Analytics for CPG Firms (A): Estimating Sales

      By: Ayelet Israeli and Fedor (Ted) Lisitsyn
      The 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 challenges for... View Details
      Keywords: Data Analysis; Data Analytics; CPG; Consumer Packaged Goods (CPG); Estimation; Online Channel; Retail Analytics; Retail; Retailing Industry; Data; Data Sharing; Bricks And Mortar; Ecommerce; Direct-to-consumer; DTC; Analytics and Data Science; Sales; Marketing; E-commerce; Retail Industry; Retail Industry; United States
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      Israeli, Ayelet, and Fedor (Ted) Lisitsyn. "E-Commerce Analytics for CPG Firms (A): Estimating Sales." Harvard Business School Exercise 521-078, January 2021. (Revised March 2021.)
      • January 2021
      • Supplement

      E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer

      By: Ayelet Israeli and Fedor (Ted) Lisitsyn
      The 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 challenges for... View Details
      Keywords: Data Analysis; Data Analytics; CPG; Consumer Packaged Goods (CPG); Online Channel; Retail; Retail Analytics; Retailing Industry; Data; Data Sharing; Ecommerce; Assortment Optimization; Assortment Planning; Analytics and Data Science; Retention; Retail Industry; Retail Industry; United States
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      Israeli, Ayelet, and Fedor (Ted) Lisitsyn. "E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer." Harvard Business School Spreadsheet Supplement 521-713, January 2021.
      • January 2021
      • Exercise

      E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer

      By: Ayelet Israeli and Fedor (Ted) Lisitsyn
      The 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 challenges for... View Details
      Keywords: Data Analysis; Data Analytics; CPG; Consumer Packaged Goods (CPG); Online Channel; Retail Analytics; Retail; Retailing Industry; Data; Data Sharing; Ecommerce; CRM; Loyalty Management; Assortment Planning; Assortment Optimization; Lifetime Value (LTV); Analytics and Data Science; Analysis; Retention; E-commerce; Retail Industry; Retail Industry; United States
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      Israeli, Ayelet, and Fedor (Ted) Lisitsyn. "E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer." Harvard Business School Exercise 521-079, January 2021.
      • January 2021 (Revised March 2021)
      • Supplement

      E-Commerce Analytics for CPG Firms (C): Free Delivery Terms

      By: Ayelet Israeli and Fedor (Ted) Lisitsyn
      The 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 challenges for... View Details
      Keywords: Data; Data Analysis; Data Analytics; Data Sharing; CPG; Consumer Packaged Goods (CPG); Delivery Planning; Customer Lifetime Value; Online Channel; Retail; Retail Analytics; Retailing Industry; Ecommerce; Grocery; Grocery Delivery; Margins; Retention; Analytics and Data Science; Analysis; Retail Industry; Retail Industry; United States
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      Israeli, Ayelet, and Fedor (Ted) Lisitsyn. "E-Commerce Analytics for CPG Firms (C): Free Delivery Terms." Harvard Business School Spreadsheet Supplement 521-714, January 2021. (Revised March 2021.)
      • January 2021 (Revised March 2021)
      • Exercise

      E-Commerce Analytics for CPG Firms (C): Free Delivery Terms

      By: Ayelet Israeli and Fedor (Ted) Lisitsyn
      The 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 challenges for... View Details
      Keywords: Data; Data Analysis; Data Analytics; Data Sharing; CPG; Consumer Packaged Goods (CPG); Delivery Planning; Customer Lifetime Value; Online Channel; Retail; Retail Analytics; Retailing Industry; Ecommerce; Grocery; Grocery Delivery; Margins; Analytics and Data Science; Retention; E-commerce; Retail Industry; Retail Industry; United States
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      Israeli, Ayelet, and Fedor (Ted) Lisitsyn. "E-Commerce Analytics for CPG Firms (C): Free Delivery Terms." Harvard Business School Exercise 521-080, January 2021. (Revised March 2021.)
      • January 2021 (Revised March 2021)
      • Case

      Jumia's Path to Profitability

      By: Ramon Casadesus-Masanell, Pippa Tubman Armerding and Gamze Yucaoglu
      The case opens in September 2019 as Sacha Poignonnec and Jeremy Hodara, co-founders and co-CEOs of Jumia, the leading Pan-African e-commerce platform, are contemplating the company’s path to profitability in the aftermath of a fragile investor sentiment, as the company... View Details
      Keywords: Retail; Business Models; Business Model; Business Startups; Emerging Markets; For-Profit Firms; Strategy; Digital Platforms; Information Technology; Technology Adoption; Value Creation; Globalization; Entrepreneurship; Competition; Expansion; Logistics; Profit; Resource Allocation; Diversification; Corporate Strategy; Retail Industry; Retail Industry; Africa
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      Casadesus-Masanell, Ramon, Pippa Tubman Armerding, and Gamze Yucaoglu. "Jumia's Path to Profitability." Harvard Business School Case 721-355, January 2021. (Revised March 2021.)
      • January 2021
      • Article

      The Effects of Menu Costs on Retail Performance: Evidence from Adoption of the Electronic Shelf Label Technology

      By: Ioannis Stamatopoulos, Achal Bassamboo and Antonio Moreno
      We use the adoption of electronic shelf labels (ESLs) by an international grocery retailer in 2015 to identify the effects of physical menu costs (i.e., labor and material costs of price adjustment) on retail performance. We find that the installation of ESLs increased... View Details
      Keywords: Retail Operations; Dynamic Pricing; Revenue Management; Operations; Price; Revenue; Management; Retail Industry
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      Stamatopoulos, Ioannis, Achal Bassamboo, and Antonio Moreno. "The Effects of Menu Costs on Retail Performance: Evidence from Adoption of the Electronic Shelf Label Technology." Management Science 67, no. 1 (January 2021): 242–256.
      • December 2020 (Revised April 2021)
      • Case

      Arcos Dorados: A QSR Recovery Plan

      By: Forest Reinhardt, José B. Alvarez, Jenyfeer Martinez Buitrago and Mariana Cal
      Arcos Dorados—McDonald’s largest independent franchisee, covering Latin America and the Caribbean (LAC)—faced a pandemic that was disrupting the entire consumer foodservice business in 2020. With the exclusive right to own, operate, and sub-franchise McDonald’s... View Details
      Keywords: Agribusiness; Animal-Based Agribusiness; Plant-Based Agribusiness; Customer Value and Value Chain; Income; Macroeconomics; Environmental Management; Environmental Sustainability; Cross-Cultural and Cross-Border Issues; Food; Health Pandemics; Crisis Management; Logistics; Corporate Social Responsibility and Impact; Strategic Planning; Food and Beverage Industry; Food and Beverage Industry; Food and Beverage Industry; Latin America; Aruba; Guadeloupe; Martinique; Mexico; Panama; Costa Rica; Argentina; Brazil; Chile; Colombia; Ecuador; French Guiana; Peru; Uruguay; Venezuela; Puerto Rico; Trinidad and Tobago
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      Reinhardt, Forest, José B. Alvarez, Jenyfeer Martinez Buitrago, and Mariana Cal. "Arcos Dorados: A QSR Recovery Plan." Harvard Business School Case 721-023, December 2020. (Revised April 2021.)
      • 2021
      • Working Paper

      The Value of Descriptive Analytics: Evidence from Online Retailers

      By: Ron Berman and Ayelet Israeli
      Does the adoption of descriptive analytics impact online retailer performance, and if so, how? We use the synthetic difference-in-differences method to analyze the staggered adoption of a retail analytics dashboard by more than 1,500 e-commerce websites, and we find an... View Details
      Keywords: Descriptive Analytics; Big Data; Synthetic Control; E-commerce; Online Retail; Difference-in-differences; Martech; Internet and the Web; Analytics and Data Science; Performance; Retail Industry
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      Berman, Ron, and Ayelet Israeli. "The Value of Descriptive Analytics: Evidence from Online Retailers." Harvard Business School Working Paper, No. 21-067, November 2020. (Revised December 2021. Accepted at Marketing Science.)
      • November 2020 (Revised May 2023)
      • Case

      Holaluz: Taking on the Spanish Energy Market

      By: Elie Ofek, Marco Bertini, Oded Koenigsberg, Elena Corsi and Emer Moloney
      In 2020, the three cofounders of Holaluz, a newcomer to Spain’s electricity retail market, are preparing to launch a new offering: installing and managing solar panels on households' roofs at no extra cost for the consumer, who would still benefit from the energy... View Details
      Keywords: Electricity; Solar Power; Subscription Business; Renewable Energy; Entrepreneurship; Service Delivery; Business Model; Product Launch; Marketing; Energy Industry; Spain
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      Ofek, Elie, Marco Bertini, Oded Koenigsberg, Elena Corsi, and Emer Moloney. "Holaluz: Taking on the Spanish Energy Market." Harvard Business School Case 521-045, November 2020. (Revised May 2023.)
      • November 2020 (Revised March 2021)
      • Case

      Amazon: Cult or Culture?

      By: Boris Groysberg, Sarah L. Abbott and Tricia Gregg
      Amazon was one of the first entrants in e-commerce. Under the leadership of founder Jeff Bezos, Amazon had expanded beyond books to manufacturing and selling a wide range of products and services globally. Bezos had built a customer-centric culture that permeated all... View Details
      Keywords: Culture; Technology Companies; Retail; Human Resource Practices; Growth; Founder; Leadership; Organizational Culture; Growth Management; Information Technology; Human Resources; Talent and Talent Management; Retail Industry; Retail Industry
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      Groysberg, Boris, Sarah L. Abbott, and Tricia Gregg. "Amazon: Cult or Culture?" Harvard Business School Case 421-008, November 2020. (Revised March 2021.)
      • October 2020 (Revised March 2022)
      • Case

      Automercados Plaza's: Surviving Venezuela's Hyperinflation

      By: Alberto Cavallo, Mariana Cal and Carla Larangeira
      Under the rule of presidents Hugo Chávez and Nicolas Maduro, Venezuela experienced one of the worst economic and political meltdowns in modern history, culminating with a massive hyperinflation. Remarkably, during this dramatic times Automercados Plaza's had grown to... View Details
      Keywords: Hyperinflation; Populism; Inflation and Deflation; Macroeconomics; Management; Strategy; Organizational Change and Adaptation; Business and Government Relations; Retail Industry; South America; Venezuela
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      Cavallo, Alberto, Mariana Cal, and Carla Larangeira. "Automercados Plaza's: Surviving Venezuela's Hyperinflation." Harvard Business School Case 721-014, October 2020. (Revised March 2022.)
      • October 2020 (Revised February 2021)
      • Case

      Twiga Foods: Revolutionizing African Retail (A)

      By: Shikhar Ghosh, Pippa Tubman Amerding and Wale Lawal
      Twiga is a leading agricultural produce supplier in Kenya offering services to mostly informal retailers. Under Peter Njonjo, a co-founder and Twiga’s new CEO, the company is considering multiple options for expanding its business, including offering packaged foods and... View Details
      Keywords: Leadership; Expansion; Growth and Development Strategy; Organizational Structure; Retail Industry; Nairobi
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      Ghosh, Shikhar, Pippa Tubman Amerding, and Wale Lawal. "Twiga Foods: Revolutionizing African Retail (A)." Harvard Business School Case 821-043, October 2020. (Revised February 2021.)
      • October 2020 (Revised March 2021)
      • Supplement

      Migros Turkey: Scaling Online Operations During COVID-19 (C)

      By: Antonio Moreno and Gamze Yucaoglu
      The case opens in August 2020 as Ozgur Tort and Mustafa Bartin, CEO and chief large-format and online retail officer of Migros Ticaret A.S. (Migros), Turkey’s oldest and one of its largest supermarket chains, are navigating Migros through COVID-19 and the unprecedented... View Details
      Keywords: Business Model; Strategy; Digital Platforms; Information Technology; Technology Adoption; Value Creation; Globalization; Competition; Expansion; Logistics; Profit; Resource Allocation; Diversification; Corporate Strategy; Crisis Management; Health Pandemics; Strategic Planning; Food and Beverage Industry; Turkey
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      Moreno, Antonio, and Gamze Yucaoglu. "Migros Turkey: Scaling Online Operations During COVID-19 (C)." Harvard Business School Supplement 621-062, October 2020. (Revised March 2021.)
      • 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; Retail Industry; Retail Industry; United States
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      Israeli, Ayelet, and Eva Ascarza. "Algorithmic Bias in Marketing." Harvard Business School Teaching Note 521-035, September 2020. (Revised July 2022.)
      • September 2020 (Revised July 2022)
      • Technical Note

      Algorithmic Bias in Marketing

      By: Ayelet Israeli and Eva Ascarza
      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 product—characterizing the marketing... View Details
      Keywords: Algorithmic Data; Race And Ethnicity; Promotion; "Marketing Analytics"; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeting; Targeted Advertising; Pricing Algorithms; Ethical Decision Making; Customer Heterogeneity; Marketing; Race; Ethnicity; Gender; Diversity; Prejudice and Bias; Marketing Communications; Analytics and Data Science; Analysis; Decision Making; Ethics; Customer Relationship Management; E-commerce; Retail Industry; Retail Industry; United States
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      Israeli, Ayelet, and Eva Ascarza. "Algorithmic Bias in Marketing." Harvard Business School Technical Note 521-020, September 2020. (Revised July 2022.)
      • September 2020 (Revised February 2024)
      • Teaching Note

      Artea (A), (B), (C), and (D): Designing Targeting Strategies

      By: Eva Ascarza and Ayelet Israeli
      Teaching Note for HBS No. 521-021,521-022,521-037,521-043. 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; Targeting; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Retail Industry; Retail Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (A), (B), (C), and (D): Designing Targeting Strategies." Harvard Business School Teaching Note 521-041, September 2020. (Revised February 2024.)
      • September 2020 (Revised July 2022)
      • Exercise

      Artea (B): Including Customer-Level Demographic Data

      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; Demographics; Prejudice and Bias; Retail Industry; Retail Industry; Retail Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (B): Including Customer-Level Demographic Data." Harvard Business School Exercise 521-022, September 2020. (Revised July 2022.)
      • 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; Retail Industry; Retail Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (C): Potential Discrimination through Algorithmic Targeting." Harvard Business School Exercise 521-037, September 2020. (Revised July 2022.)
      • 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; Retail Industry; Retail Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (D): Discrimination through Algorithmic Bias in Targeting." Harvard Business School Exercise 521-043, September 2020. (Revised July 2022.)
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