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- All HBS Web
(117,152)
- Faculty Publications (323)
- 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
Datar, Srikant M., and Caitlin N. Bowler. "Predicting Purchasing Behavior at PriceMart (A)." Harvard Business School Case 119-025, August 2018. (Revised September 2018.)
- 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
Datar, Srikant M., and Caitlin N. Bowler. "Predicting Purchasing Behavior at PriceMart (B)." Harvard Business School Supplement 119-026, August 2018. (Revised September 2018.)
- August 2018 (Revised April 2019)
- Case
Chateau Winery (A): Unsupervised Learning
By: Srikant M. Datar and Caitlin N. Bowler
This case follows Bill Booth, marketing manager of a regional wine distributor, as he applies unsupervised learning on data about his customers’ purchases to better understand their preferences. Specifically, he uses the K-means clustering technique to identify groups... View Details
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (A): Unsupervised Learning." Harvard Business School Case 119-023, August 2018. (Revised April 2019.)
- 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
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (B): Supervised Learning." Harvard Business School Supplement 119-024, August 2018. (Revised April 2019.)
- August 2018 (Revised September 2018)
- Case
LendingClub (A): Data Analytic Thinking (Abridged)
By: Srikant M. Datar and Caitlin N. Bowler
LendingClub was founded in 2006 as an alternative, peer-to-peer lending model to connect individual borrowers to individual investor-lenders through an online platform. Since 2014 the company has worked with institutional investors at scale. While the company assigns... View Details
Keywords: Data Science; Data Analytics; Investing; Loans; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction; Business Model
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (A): Data Analytic Thinking (Abridged)." Harvard Business School Case 119-020, August 2018. (Revised September 2018.)
- August 2018 (Revised September 2018)
- Supplement
LendingClub (B): Decision Trees & Random Forests
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on the LendingClub (A) case. In this case students follow Emily Figel as she builds two tree-based models using historical LendingClub data to predict, with some probability, whether borrower will repay or default on his loan.
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Keywords: Data Science; Data Analytics; Decision Trees; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (B): Decision Trees & Random Forests." Harvard Business School Supplement 119-021, August 2018. (Revised September 2018.)
- August 2018 (Revised September 2018)
- Supplement
LendingClub (C): Gradient Boosting & Payoff Matrix
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on the LendingClub (A) and (B) cases. In this case students follow Emily Figel as she builds an even more sophisticated model using the gradient boosted tree method to predict, with some probability, whether a borrower would repay or default... View Details
Keywords: Data Analytics; Data Science; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (C): Gradient Boosting & Payoff Matrix." Harvard Business School Supplement 119-022, August 2018. (Revised September 2018.)
- August 2018 (Revised October 2019)
- Case
C3.ai—Driven to Succeed
By: Robert Simons and George Gonzalez
CEO Tom Siebel navigates his artificial intelligence (ai) startup through a series of pivots, market expansions, and even an elephant attack to become a leading platform ad service provider. The case describes his unusual management approach emphasizing employee... View Details
Keywords: Strategy Execution; Performance Measurement; Critical Performance Variables; Strategic Boundaries; Internet Of Things; Artificial Intelligence; Software Development; Big Data; Machine Learning; Business Startups; Management Style; Business Strategy; Performance; Measurement and Metrics; Organizational Culture; AI and Machine Learning; Digital Transformation; Applications and Software; Digital Marketing; Analytics and Data Science; Technology Industry; United States; California
Simons, Robert, and George Gonzalez. "C3.ai—Driven to Succeed." Harvard Business School Case 119-004, August 2018. (Revised October 2019.)
- August 2018 (Revised October 2020)
- Case
Tailor Brands: Artificial Intelligence-Driven Branding
By: Jill Avery
Using proprietary artificial intelligence technology, startup Tailor Brands set out to democratize branding by allowing small businesses to create their brand identities by automatically generating logos in just minutes at minimal cost with no branding or design skills... View Details
Keywords: Startup; Services; Artificial Intelligence; Machine Learning; Digital Marketing; Brand Management; Big Data; Internet Marketing; Analytics; Marketing; Marketing Strategy; Brands and Branding; Information Technology; Entrepreneurship; Venture Capital; Business Model; Consumer Behavior; AI and Machine Learning; Analytics and Data Science; Advertising Industry; Service Industry; Technology Industry; United States; North America; Israel
Avery, Jill. "Tailor Brands: Artificial Intelligence-Driven Branding." Harvard Business School Case 519-017, August 2018. (Revised October 2020.)
- August 2018 (Revised February 2023)
- Case
Hubble Contact Lenses: Data Driven Direct-to-Consumer Marketing
By: Jill Avery and Ayelet Israeli
As its Series A extension round approaches, the founders of Hubble, a subscription-based, social-media fueled, direct-to-consumer (DTC) brand of contact lenses, are reflecting on the marketing strategies that have taken them to a valuation of $200 million and debating... View Details
Keywords: DTC; Direct To Consumer Marketing; Health Care; Mobile; Attribution; Experimentation; Experiments; Churn/retention; Customer Lifetime Value; Internet Marketing; Big Data; Analytics; A/B Testing; CRM; Advertising; Marketing; Marketing Channels; Marketing Strategy; Media; Brands and Branding; Marketing Communications; Digital Marketing; Consumer Behavior; Acquisition; Growth and Development Strategy; Customer Focus and Relationships; Social Media; E-commerce; Analytics and Data Science; Health Industry; Consumer Products Industry; United States; North America; Europe
Avery, Jill, and Ayelet Israeli. "Hubble Contact Lenses: Data Driven Direct-to-Consumer Marketing." Harvard Business School Case 519-011, August 2018. (Revised February 2023.)
- 2018
- Working Paper
Measuring Gentrification: Using Yelp Data to Quantify Neighborhood Change
By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
We demonstrate that data from digital platforms such as Yelp have the potential to improve our understanding of gentrification, both by providing data in close to real time (i.e., nowcasting and forecasting) and by providing additional context about how the local... View Details
Keywords: Geographic Location; Local Range; Transition; Analytics and Data Science; Measurement and Metrics; Forecasting and Prediction
Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Measuring Gentrification: Using Yelp Data to Quantify Neighborhood Change." NBER Working Paper Series, No. 24952, August 2018.
- July 2018
- Article
Reimagining Health Data Exchange: An Application Programming Interface-Enabled Roadmap for India
By: Satchit Balsari, Alexander Fortenko MD, MPH, Joaquin A. Blaya PhD, Adrian Gropper MD, Malavika Jayaram LLM, Rahul Matthan LLM, Ram Sahasranam, Mark Shankar MD, Suptendra N. Sarbadhikari PhD, Barbara Bierer, Kenneth D. Mandl MD, Sanjay Mehendale MD, MPH and Tarun Khanna
In February 2018, the Government of India announced a massive public health insurance scheme extending coverage to 500 million citizens, in effect making it the world’s largest insurance program. To meet this target, the government will rely on technology to... View Details
Keywords: Health Information Exchange; India; Health APIs; Health Care and Treatment; Information; Analytics and Data Science; Information Technology; Health Industry; India
Balsari, Satchit, Alexander Fortenko MD, MPH, Joaquin A. Blaya PhD, Adrian Gropper MD, Malavika Jayaram LLM, Rahul Matthan LLM, Ram Sahasranam, Mark Shankar MD, Suptendra N. Sarbadhikari PhD, Barbara Bierer, Kenneth D. Mandl MD, Sanjay Mehendale MD, MPH, and Tarun Khanna. "Reimagining Health Data Exchange: An Application Programming Interface-Enabled Roadmap for India." Journal of Medical Internet Research 20, no. 7 (July 2018).
- June 2018 (Revised January 2019)
- Background Note
Visualizing Data & Effective Communication
By: Srikant M. Datar and Caitlin N. Bowler
This note explores three specific ways an analyst can use visualization. Section 1 considers visualization to explore data. Section 2 discusses visualization as a tool for developing a deeper understanding of trends and phenomena encoded in the data. Section 3... View Details
Keywords: Data Visualization; Graphical Guidelines; Charts; Analytics and Data Science; Communication
Datar, Srikant M., and Caitlin N. Bowler. "Visualizing Data & Effective Communication." Harvard Business School Background Note 118-114, June 2018. (Revised January 2019.)
- June 2018
- Article
Personal and Social Usage: The Origins of Active Customers and Ways to Keep Them Engaged
By: Clarence Lee, Elie Ofek and Thomas Steenburgh
We study how digital service firms can develop an active customer base, focusing on two questions. First, how does the way that customers use the service postadoption to meet their own needs (personal usage) and to interact with one another (social usage) vary across... View Details
Keywords: Customer Engagement; Adoption Routes; Word-of-Mouth; Digital Marketing; Bayesian Estimation; Customers; Communication; Consumer Behavior; Marketing; Internet and the Web; Analytics and Data Science
Lee, Clarence, Elie Ofek, and Thomas Steenburgh. "Personal and Social Usage: The Origins of Active Customers and Ways to Keep Them Engaged." Management Science 64, no. 6 (June 2018): 2473–2495. (Lead Article.)
- May 2018 (Revised February 2019)
- Case
The Powers That Be (Internet Edition): Google, Apple, Facebook, Amazon, and Microsoft
By: Jeffrey F. Rayport, Julia Kelley and Nathaniel Schwalb
As of early 2018, five U.S. technology companies—Google, Apple, Facebook, Amazon, and Microsoft—were among the largest companies in the world. Similarly, three Chinese technology firms—Baidu, Alibaba, and Tencent, or BAT—had emerged as global players due in part to the... View Details
Keywords: Internet and the Web; Business Ventures; Customers; Analytics and Data Science; Safety; Corporate Strategy; Competitive Strategy; Technology Industry
Rayport, Jeffrey F., Julia Kelley, and Nathaniel Schwalb. "The Powers That Be (Internet Edition): Google, Apple, Facebook, Amazon, and Microsoft." Harvard Business School Case 818-111, May 2018. (Revised February 2019.)
- May 2018 (Revised June 2018)
- Case
Cowen Inc.: Leveraging Data
By: Boris Groysberg, Sarah Abbott and Annelena Lobb
Cowen Inc.’s broker-dealer, Cowen and Company, LLC, boasted a number of analysts who had made prescient stock calls on the basis of creative data analysis. Now Cowen Inc. had opened a new subsidiary, Kyber, which would attempt to monetize new data science products.... View Details
Keywords: Data Science; Equity Research; Research Analysts; Investment; Analytics and Data Science; Equity; Research; Analysis; Competitive Strategy
Groysberg, Boris, Sarah Abbott, and Annelena Lobb. "Cowen Inc.: Leveraging Data." Harvard Business School Case 418-035, May 2018. (Revised June 2018.)
- May 2018
- Exercise
Data Visualization & Communication Exercise
By: Srikant M. Datar and Caitlin N. Bowler
This exercise uses the 1986 Challenger shuttle disaster to explore the relationship between data visualization, effective communication, and decision-making. Students review and analyze excerpts from the 13 charts engineers presented to NASA executives the night before... View Details
Keywords: Visualization; Data; Analytics and Data Science; Communication; Performance Effectiveness; Decision Making; Analysis
Datar, Srikant M., and Caitlin N. Bowler. "Data Visualization & Communication Exercise." Harvard Business School Exercise 118-107, May 2018.
- May 2018
- Article
Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change
By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
Data from digital platforms have the potential to improve our understanding of gentrification and enable new measures of how neighborhoods change in close to real time. Combining data on businesses from Yelp with data on gentrification from the Census, Federal Housing... View Details
Keywords: Forecasting Models; Simulation Methods; Regional Economic Activity: Growth, Development, Environmental Issues, And Changes; Geographic Location; Local Range; Transition; Analytics and Data Science; Measurement and Metrics; Economic Growth; Forecasting and Prediction
Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change." AEA Papers and Proceedings 108 (May 2018): 77–82.
- February 2018
- Supplement
People Analytics at Teach For America (B)
By: Jeffrey T. Polzer and Julia Kelley
This is a supplement to the People Analytics at Teach For America (A) case. In this supplement, Managing Director Michael Metzger must decide how to extend his team’s predictive analytics work using Natural Language Processing (NLP) techniques. View Details
- 2019
- Working Paper
Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles
By: Prithwiraj Choudhury, Dan Wang, Natalie A. Carlson and Tarun Khanna
We demonstrate how a novel synthesis of three methods—(1) unsupervised topic modeling of text data to generate new measures of textual variance, (2) sentiment analysis of text data, and (3) supervised ML coding of facial images with a cutting-edge convolutional neural... View Details
Choudhury, Prithwiraj, Dan Wang, Natalie A. Carlson, and Tarun Khanna. "Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles." Harvard Business School Working Paper, No. 18-064, January 2018. (Revised May 2019.)