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- November 5, 2021
- Article
Leaders: Stop Confusing Correlation with Causation
By: Michael Luca
We’ve all been told that correlation does not imply causation. Yet many business leaders, elected officials, and media outlets still make causal claims based on misleading correlations. These claims are too often unscrutinized, amplified, and mistakenly used to guide...
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- November 2021
- Supplement
PittaRosso (B): Human and Machine Learning
By: Ayelet Israeli
This case supplements the "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion" case, and provides major highlights on what happened at the company since the first case.
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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;
Data and Data Sets;
Analysis;
Online Advertising;
Budgets and Budgeting;
Marketing Strategy;
Marketing;
Transformation;
Decision Making;
Retail Industry;
Italy
- 2021
- Article
A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects
By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public...
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- October 2021
- 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...
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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;
Data and Data Sets;
Analysis;
Online Advertising;
Budgets and Budgeting;
Marketing Strategy;
Marketing;
Transformation;
Decision Making;
Retail Industry;
Italy
- October 2021
- 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;
Price;
Advertising Campaigns;
Data and Data Sets;
Analysis;
Online Advertising;
Budgets and Budgeting;
Marketing Strategy;
Marketing;
Transformation;
Decision Making;
Retail Industry;
Italy
- June 2021
- Technical Note
Introduction to Linear Regression
By: Michael Parzen and Paul J. Hamilton
This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical...
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- May 2021 (Revised October 2021)
- 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...
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Keywords:
Data;
Data Analytics;
Artificial Intelligence;
AI;
AI Algorithms;
AI Creativity;
Fashion;
Retail;
Retail Analytics;
Digital Marketing;
E-commerce;
E-Commerce Strategy;
Platform;
Platforms;
Big Data;
Preference Elicitation;
Predictive Analytics;
App Development;
＂Marketing Analytics＂;
Advertising;
Mobile App;
Mobile Marketing;
Apparel;
Referral Rewards;
Referrals;
Female Ceo;
Female Entrepreneur;
Female Protagonist;
Data and Data Sets;
Analysis;
Creativity;
Marketing Strategy;
Brands and Branding;
Consumer Behavior;
Demand and Consumers;
Forecasting and Prediction;
Marketing Channels;
Online Advertising;
Online Technology;
Mobile Technology;
Fashion Industry;
Retail Industry;
Apparel and Accessories Industry;
Consumer Products Industry;
United States
- April 2021
- Teaching Note
Social Media War 2021: Snap vs. Facebook vs. TikTok
By: David B. Yoffie and Daniel Fisher
This teaching note provides analysis and a teaching plan for the Social Media War 2021: Snap vs. Facebook vs. TikTok case.
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- April 2021
- Case
Social Media War 2021: Snap vs. Facebook vs. TikTok
By: David B. Yoffie and Daniel Fisher
This case explores the competitive war between Snap, Facebook, and TikTok in 2021. The strategic focus is on Snapchat: how should it respond to the emergence of TikTok, and how should it compete with the dominant competitor in its space—Facebook. The case examines...
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- 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...
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- 2021
- Working Paper
Judging Foreign Startups
Can accelerators and investors pick the most promising startup ideas no matter their provenance? We investigate this question using unique data from a global accelerator in which judges across international regions are randomly assigned to evaluate startups...
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- March 2021
- Article
The Crowd Emotion Amplification Effect
By: Amit Goldenberg, Erika Weisz, Timothy D. Sweeney, Mina Cikara and James Gross
How do people go about reading a room or taking the temperature of a crowd? When people catch a brief glimpse of an array of faces, they can only focus their attention on some of the faces. We propose that perceivers preferentially attend to faces exhibiting strong...
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- February 2021
- Background Note
Jobs to Be Done: A Toolbox
By: Derek C. M. van Bever, Bob Moesta, Iuliana Mogosanu, Shaye Roseman and Katie Zandbergen
The Jobs to Be Done methodology is both a theory and a practical approach for understanding customer behavior and why people make the choices they make. Many practitioners, whether they work for startups or incumbent businesses, find Jobs to Be Done useful because it...
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- 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;
Digital Marketing;
E-commerce;
E-Commerce Strategy;
Platform;
Platforms;
Big Data;
Preference Elicitation;
Preference Prediction;
Predictive Analytics;
App Development;
＂Marketing Analytics＂;
Advertising;
Mobile App;
Mobile Marketing;
Apparel;
Referral Rewards;
Referrals;
Female Ceo;
Female Entrepreneur;
Female Protagonist;
Data and Data Sets;
Analysis;
Creativity;
Marketing Strategy;
Brands and Branding;
Consumer Behavior;
Demand and Consumers;
Forecasting and Prediction;
Marketing Channels;
Online Advertising;
Online Technology;
Mobile Technology;
Fashion Industry;
Retail Industry;
Apparel and Accessories Industry;
Consumer Products Industry;
United States
- January 2021
- Case
The FIRE Savings Calculator
By: Michael Parzen and Paul J. Hamilton
This case follows Carol Muñoz, a member of the Financial Independence, Retire Early (FIRE) lifestyle movement. At the age of 45, Carol is considering retiring and living off the $1 million she has accumulated. Using Monte Carlo simulation, Carol forecasts the...
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- January 2021
- Article
Machine Learning for Pattern Discovery in Management Research
By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect...
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- November 2020
- Case
Axis My India
By: Ananth Raman, Ann Winslow and Kairavi Dey
Pradeep Gupta founded Axis My India (AMI) as a printing and publishing company in 1998. In 2013, AMI expanded into consumer research and election forecasting. Although a relatively unknown entity, AMI predicted several election results accurately. Gupta describes AMI’s...
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- November 2020
- Teaching Note
Valuing Celgene's CVR
By: Benjamin C. Esty and Daniel Fisher
When Bristol-Myers Squibb (BMS) acquired Celgene Corporation in November 2019, Celgene shareholders received cash, BMS stock, and a contingent value right (CVRs) that would pay $9 if the U.S. Food and Drug Administration (FDA) approved three of Celgene’s late stage...
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- November 2020
- Supplement
Valuing Celgene's CVR
By: Benjamin C. Esty and Daniel Fisher
When Bristol-Myers Squibb (BMS) acquired Celgene Corporation in November 2019, Celgene shareholders received cash, BMS stock, and a contingent value right (CVRs) that would pay $9 if the U.S. Food and Drug Administration (FDA) approved three of Celgene’s late stage...
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