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March 1995 (Revised April 1997)
Case

Co-operative Bank, The

By: Robert S. Kaplan and Srikant M. Datar

A British bank with strong roots in the cooperative movement encounters declining profitability in an increasingly competitive and deregulated financial services industry. It attempts to grow by broadening its customer base and increasing the range of products and... View Details

Keywords: Product; Competition; Expansion; Cost Management; Activity Based Costing and Management; Profit; Banking Industry; Financial Services Industry

June 2011 (Revised May 2012)
Case

L'Oréal: Global Brand, Local Knowledge

By: Rebecca M. Henderson and Ryan Johnson

Worldwide, and in the U.S. marketplace in particular, the French cachet of L'Oréal was one of its most powerful marketing tools. However, with the opening up of emerging markets, L'Oréal had to cater to a diverse customer base: an aging population in the West, ethnic... View Details

Keywords: Globalization; Brands and Branding; Marketing Communications; Change Management; Sales; Emerging Markets; Segmentation; Innovation and Invention; Beauty and Cosmetics Industry; France; United States

26 Jun 2023
Research & Ideas

Want to Leave a Lasting Impression on Customers? Don't Forget the (Proverbial) Fireworks

way of leaving an impression. “A strong ending can have a big impact on people’s evaluations when they look back on an experience,” says De Freitas, coauthor of the working paper “Summarizing the Mental Customer Journey.” “We ended up... View Details

Keywords: by Michael Blanding; Entertainment & Recreation

April 2002 (Revised March 2006)
Background Note

Economics of Retail Banking Note

By: Frances X. Frei and Dennis Campbell

Explains the financial operations of retail banking, highlighting profitability challenges facing the industry. For U.S. banks, it is quite common for more than half of the customer base to be unprofitable and to have relatively few customers make up the vast majority... View Details

Keywords: Customers; Economics; Cost; Banks and Banking; Profit; Revenue; Service Operations; Banking Industry; United States

21 Jul 2008
Research & Ideas

Solving the Marketing Resources Allocation Puzzle

against a control group of customers. Econometric analysis of historical data: Historical data are analyzed to determine how customers have responded to different marketing actions in the past. Predictions... View Details

Keywords: by Sean Silverthorne

April 2008 (Revised October 2008)
Case

TD Canada Trust (A): The Green and the Red

By: Dennis Campbell and Brent Kazan

The case series illustrates the role of performance measurement and analytics in translating TD-Canada Trust's service model of "comfortable banking" into operational terms. In 2000, in a banking market where consumers and regulators were typically hostile to mergers... View Details

Keywords: Mergers and Acquisitions; Customer Focus and Relationships; Customer Satisfaction; Commercial Banking; Profit; Balanced Scorecard; Organizational Change and Adaptation; Banking Industry; Canada

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; Apparel and Accessories Industry; Technology Industry; United States

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; Apparel and Accessories Industry; Technology Industry; United States

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

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

April 1996 (Revised October 1999)
Case

Risk of Stocks in the Long Run, The: The Barnstable College Endowment

By: Andre F. Perold

The manager of the Barnstable College Endowment is evaluating proposals to increase the endowment's exposure to stocks based on an analysis that shows stocks to be much safer over long holding periods. View Details

Keywords: Risk Management; Financial Management; Stocks; Financial Services Industry; Education Industry

February 2001
Case

PlanetFeedback: The Voice of One ... The Power of Many (A)

By: James L. Heskett

The management of PlanetFeedback in proposes a merger with Intelliseek. Their goal is to create a comprehensive C2B and B2B business focused on the generation and analysis for business clients of consumer feedback data via the Internet, Planet Feedback's board of... View Details

Keywords: Mergers and Acquisitions; Decisions; Information Management; Analytics and Data Science; Business Strategy; Internet and the Web; Information Technology Industry

March–April 1979
Article

How Competitive Forces Shape Strategy

By: M. E. Porter

Many factors determine the nature of competition, including not only rivals, but also the economics of particular industries, new entrants, the bargaining power of customers and suppliers, and the threat of substitute services or products. A strategic plan of action... View Details

Keywords: Competition; Strategy

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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; Apparel and Accessories Industry; Technology Industry; United States

August 2021 (Revised February 2024)
Case

Data Science at the Warriors

By: Iavor I. Bojinov and Michael Parzen

The case explores the development and early growth of a data science team at the Golden State Warriors, an NBA team based in San Francisco. The case begins by explaining the initial rationale for investing in data science, then covers a debate on the appropriate team... View Details

Keywords: Digital Marketing; Analysis; Forecasting and Prediction; Technological Innovation; Information Technology; Analytics and Data Science; Sports Industry; San Francisco; United States

July 2010 (Revised August 2012)
Supplement

Assistant Professor Jo Worthington (B)

By: Dorothy A. Leonard

A professor teaching a case discussion based on numeric analysis is pleased that a student finally "cracks" the case--but the numbers differ from her own. The instructor has to decide how to handle the discrepancy. View Details

Keywords: Interpersonal Communication; Teaching; Cases; Mathematical Methods; Conflict Management

February 2001 (Revised January 2002)
Case

Tracmail

By: Paul W. Marshall, Carin-Isabel Knoop and Suma Raju

Tracmail, an online customer service company based in India, is trying to handle support services (e-mail and chat) for companies worldwide. In its quest to break into global markets, Tracmail is contemplating a joint venture with a U.S. call center. Tracmail is also... View Details

Keywords: Salesforce Management; Globalized Firms and Management; Business Startups; Joint Ventures; Service Industry; Information Technology Industry; India; United States

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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 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

Keywords: Targeted Advertising; Targeting; Algorithmic Data; Bias; A/B Testing; Experiment; Advertising; Gender; Race; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

31 May 2023
Research & Ideas

With Predictive Analytics, Companies Can Tap the Ultimate Opportunity: Customers’ Routines

If knowing what customers need is marketing gold, pinpointing exactly when they need it may just be platinum. Services that become part of a customer’s routine may deliver advantages beyond repeat business for a company, Harvard Business... View Details

Keywords: by Rachel Layne; Transportation

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