Publications
Publications
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- All HBS Web
(227)
- Faculty Publications (68)
- October 2021 (Revised March 2022)
- Supplement
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli and Fabrizio Fantini
PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once... View Details
Keywords: Artificial Intelligence; Pricing; Pricing Algorithm; Pricing Decisions; Pricing Strategy; Pricing Structure; Promotion; Promotions; Online Marketing; Data-driven Decision-making; Data-driven Management; Retail; Retail Analytics; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; Retail Industry; Italy
- October 2021 (Revised June 2022)
- Case
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli
PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once... View Details
Keywords: Artificial Intelligence; Pricing; Pricing Algorithm; Pricing Decisions; Pricing Strategy; Pricing Structure; Promotion; Promotions; Online Marketing; Data-driven Decision-making; Data-driven Management; Retail; Retail Analytics; AI; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy
- May 2021 (Revised February 2024)
- Teaching Note
THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)
By: Ayelet Israeli and Jill Avery
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details
Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Retail Industry; Retail Industry; Retail Industry; Retail Industry; United States
- May 2021
- Article
The Firm Next Door: Using Satellite Images to Study Local Information Advantage
By: Jung Koo Kang, Lorien Stice-Lawrence and Forester Wong
We use novel satellite data that track the number of cars in the parking lots of 92,668 stores for 71 publicly listed U.S. retailers to study the local information advantage of institutional investors. We establish car counts as a timely measure of store-level... View Details
- March 2021
- Supplement
Artea (A), (B), (C), and (D): Designing Targeting Strategies
By: Eva Ascarza and Ayelet Israeli
Power Point Supplement to 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... View Details
- 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
While the pandemic is still playing out, our preliminary investigations... View Details
Keywords: Retail; Retail Analytics; Consumer; Pandemic; COVID; COVID-19; Apparel; Ecommerce; Online Shopping; Online Apparel; Online Sales; Returns; CRM; Customer Retention; Customer Experience; Customer Value; Digital; Customer Focus and Relationships; Customers; Health Pandemics; Consumer Behavior; Customer Relationship Management; Internet and the Web; Behavior; E-commerce; Retail Industry; Retail Industry; Retail Industry; United States; United Kingdom
- February 2021 (Revised February 2021)
- Background Note
eGrocery and the Role of Data for CPG Firms
By: Ayelet Israeli, Fedor (Ted) Lisitsyn and Mark A. Irwin
This 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)." 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; Optimization; Analytics and Data Science; Analysis; Customer Value and Value Chain; Marketing Channels; E-commerce; Retail Industry; Retail Industry; United States
- January 2021 (Revised March 2021)
- Case
THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)
By: Jill Avery, Ayelet Israeli and Emma von Maur
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details
Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Retail Industry; Retail Industry; Retail Industry; Retail Industry; United States
- January 2021 (Revised May 2021)
- Case
Amazon Shopper Panel: Paying Customers for Their Data
By: Eva Ascarza and Ayelet Israeli
This case introduces a new Amazon program that has consumers upload their receipts from transactions outside of Amazon, in exchange for money. Through the discussion, the case aims to explore issues in customers’ privacy in the digital age, the value of customers’ own... View Details
Keywords: Data Analytics; Data Privacy; Data Management; ＂Marketing Analytics＂; Marketing Communication; Marketing Research; Data-driven Management; E-Commerce Strategy; Ethical Decision Making; CRM; Consumer Protection; Targeted Advertising; Targeted Policies; Data Ownership; Marketing; Research; Marketing Communications; Analytics and Data Science; Management; Customer Relationship Management; Ethics; E-commerce; Retail Industry; Retail Industry; United States
- January 2021 (Revised March 2021)
- Supplement
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; Analytics and Data Science; Analysis; Sales; Goods and Commodities; Retail Industry; Retail Industry; United States
- 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
- 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
- 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
- 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
- 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
- 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
- 2020
- Working Paper
Reverse Information Sharing: Reducing Costs in Supply Chains with Yield Uncertainty
By: Pavithra Harsha, Ashish Jagmohan, Retsef Levi, Elisabeth Paulson and Georgia Perakis
Supply uncertainty in produce supply chains presents major challenges to retailers. Supply shortages create frequent disruptions in terms of promised delivery times, quantity and quality delivered. To alleviate these challenges, dual sourcing--a strategy in which... View Details
- 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
- 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
- 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