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August 2018 (Revised April 2019)
Supplement

Chateau Winery (B): Supervised Learning

By: Srikant M. Datar and Caitlin N. Bowler

This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those... View Details

Keywords: Data Science; Clustering; Analytics and Data Science; Customers; Marketing; Analysis

March 2019
Case

HOPI: Turkey's Shopping Companion

By: Sunil Gupta, Donald Ngwe and Gamze Yucaoglu

The case opens in 2017 as Onur Erbay, CEO of HOPI, a multi-vendor loyalty platform, is contemplating a critical decision. The case chronicles the origins of Boyner Group, the parent company of HOPI and a major retailer in Turkey, and development of retail and customer... View Details

Keywords: Loyalty Programs; Multi-vendor Platform; Retail; Big Data; Customer Relationship Management; Mobile and Wireless Technology; Business Model; Analytics and Data Science; Competitive Strategy; Decision Making; Applications and Software; Digital Platforms; Technology Industry; Retail Industry; Turkey

Teaching Interest

Overview

Managing Service Operations - MBA Elective Curriculum

World-class service organizations deeply understand the needs and behaviors of their customers, and design, manage, and improve their operating models accordingly. This course... View Details

Keywords: Customer Lifetime Value; Customer Centric Initiative; Customer Engagement; Service Management; Service Profit Chain; Service Design; Service Models; Service Excellence; Customer Focus and Relationships; Customer Satisfaction; Customer Value and Value Chain; Service Delivery; Service Operations

August 2018 (Revised September 2018)
Case

Predicting Purchasing Behavior at PriceMart (A)

By: Srikant M. Datar and Caitlin N. Bowler

This case follows VP of Marketing, Jill Wehunt, and analyst Mark Morse as they tackle a predictive analytics project to increase sales in the Mom & Baby unit of a nationally recognized retailer, PriceMart. Wehunt observed that in the midst of the chaos that surrounded... View Details

Keywords: Data Science; Analytics and Data Science; Analysis; Consumer Behavior; Forecasting and Prediction

September 2020 (Revised June 2023)
Supplement

Spreadsheet Supplement to Artea Teaching Note

By: Eva Ascarza and Ayelet Israeli

Spreadsheet Supplement to Artea Teaching Note 521-041. 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; Algorithmic Data; Bias; Advertising; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

Teaching Interest

Managing Service Operations - MBA Elective Curriculum

By: Ryan W. Buell

World-class service organizations deeply understand the needs and behaviors of their customers, and design, manage, and improve their operating models accordingly. This course investigates the distinct challenges inherent in leading service operations, which make up... View Details

Keywords: Service Delivery; Customer Satisfaction; Customer Loyalty; Quality; Employees; Service Models; Service Industry

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

August 2018 (Revised September 2018)
Supplement

Predicting Purchasing Behavior at PriceMart (B)

By: Srikant M. Datar and Caitlin N. Bowler

Supplements the (A) case. In this case, Wehunt and Morse are concerned about the logistic regression model overfitting to the training data, so they explore two methods for reducing the sensitivity of the model to the data by regularizing the coefficients of the... View Details

Keywords: Data Science; Analytics and Data Science; Analysis; Customers; Household; Forecasting and Prediction

24 Mar 2015
News

See Your Company Through the Eyes of a Hacker

Keywords: cyber attacks; private companies; customer data; information technology; cyber security; hacking

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; Apparel and Accessories Industry; Technology Industry; United States

Teaching Interest

Overview

By: John A. Deighton

I teach about the ecosystem of big data, the role of data in advertising and creative industries, and customer management and personal privacy in an era of individual addressability. View Details

Keywords: Digital Marketing; Database Marketing; Social Media; Data Analytics; Information; Advertising; Marketing; Media; Technology; Consumer Products Industry; Entertainment and Recreation Industry; Information Technology Industry; Publishing Industry; Media and Broadcasting Industry

May 2018
Case

The Multiple Myeloma Research Foundation's Answer Fund

By: Richard G. Hamermesh and Matthew G. Preble

January 2014 (Revised January 2017)
Case

Nivea (A)

By: Karim R. Lakhani, Johann Fuller, Volker Bilgram and Greta Friar

The case describes the efforts of Beiersdorf, a worldwide leader in the cosmetics and skin care industries, to generate and commercialize new R&D through open innovation using external crowds and "netnographic" analysis. Beiersdorf, best known for its consumer brand... View Details

Keywords: Innovation; Innovation Management; Crowdsourcing; Big Data; Innovation Strategy; Innovation and Management; Knowledge Management; Knowledge Sharing; Research and Development; Social and Collaborative Networks; Collaborative Innovation and Invention; Analytics and Data Science; Beauty and Cosmetics Industry; Consumer Products Industry

February 2021
Case

Apple: Privacy vs. Safety (A)

By: Henry McGee, Nien-hê Hsieh, Sarah McAra and Christian Godwin

In 2015, Apple CEO Tim Cook debuted the iPhone 6S with enhanced security measures that enflamed a debate on privacy and public safety around the world. The iPhone 6S, amid a heightened concern for privacy following the 2013 revelation of clandestine U.S. surveillance... View Details

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; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States

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

March–April 2020
Article

Building A Culture of Experimentation

By: Stefan Thomke

Why don’t organizations test more? After examining this question for several years, I can tell you that the central reason is culture. As companies try to scale up their experimentation capacity, they often find that the obstacles are not tools and technology but... View Details

Keywords: Experimentation; Culture; Innovation; Online; Customer Experience; Organizational Culture; Innovation and Invention; Internet and the Web; Attitudes; Decision Making; Change; Leadership

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Article

Algorithms Need Managers, Too

By: Michael Luca, Jon Kleinberg and Sendhil Mullainathan

Algorithms are powerful predictive tools, but they can run amok when not applied properly. Consider what often happens with social media sites. Today many use algorithms to decide which ads and links to show users. But when these algorithms focus too narrowly on... View Details

Keywords: Machine Learning; Algorithms; Predictive Analytics; Management; Big Data; Analytics and Data Science

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2020
Working Paper

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

By: Eva Ascarza

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

October 2021
Article

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

By: Nicolas Padilla and Eva Ascarza

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; Programs; Consumer Behavior; Analysis

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