Filter Results:
(1,467)
Show Results For
- All HBS Web
(1,467)
- News (357)
- Research (887)
- Events (3)
- Multimedia (4)
- Faculty Publications (231)
Show Results For
- All HBS Web
(1,467)
- News (357)
- Research (887)
- Events (3)
- Multimedia (4)
- Faculty Publications (231)
- 15 May 2017
- Sharpening Your Skills
The Promises and Limitations of Big Data
Source: peterhowell Although many people claim we have entered the era of big data, research firms tell us that most collected information is never used. It sits uncleaned, unanalyzed, unused in databases. But when data analytics is used... View Details
- 30 Apr 2021
- Research & Ideas
Why Anger Makes a Wrongly Accused Person Look Guilty
University—found that anger can make a person come across as guilty even when they are not. Too often, when an employee is accused of wrongdoing, people evaluating the situation can make snap judgments based on biases and hunches. This... View Details
Keywords: by Michael Blanding
- 22 May 2014
- News
For Website Personalization, Simple Is the New Sexy
- January–February 2018
- Article
Ads That Don't Overstep: How to Make Sure You Don't Take Personalization Too Far
By: Leslie John, Tami Kim and Kate Barasz
Data gathered on the web has vastly enhanced the capabilities of marketers. With people regularly sharing personal details online and internet cookies tracking every click, companies can now gain unprecedented insight into individual consumers and target them with... View Details
John, Leslie, Tami Kim, and Kate Barasz. "Ads That Don't Overstep: How to Make Sure You Don't Take Personalization Too Far." Harvard Business Review 96, no. 1 (January–February 2018): 62–69.
- 16 Nov 2010
- Lessons from the Classroom
Data.gov: Matching Government Data with Rapid Innovation
Obama-to move government data to the Web-lead to public benefits much faster? Data.gov, the subject of a new HBS case study, taught for the first time this summer, highlights the potential of raw data to... View Details
- 07 Dec 2016
- HBS Case
Why Millennials Flock to Fintech for Personal Investing
asset accumulators of the future” A new breed of financial technology companies, known collectively as fintech, has taken advantage of these traits to disrupt an unexpected industry: personal investing. Just as manufacturing companies... View Details
- 18 Mar 2014
- News
The Oz of Data Opens the Curtain
personal data collection have a surprising ally: Scott Howe. Why? Because it's good for business. "How people think about data is going to change seismically in the coming... View Details
- 01 Dec 1997
- News
1997 Placement Data Reflect January Cohort's Success
interviews, summer career fairs that drew more than seventy firms to campus, and more personalized counseling support. Some students also completed a fall internship before entering HBS, while others worked for companies briefly during... View Details
- 19 Dec 2023
- Research & Ideas
$15 Billion in Five Years: What Data Tells Us About MacKenzie Scott’s Philanthropy
finished giving, but with more than $15 billion granted to nearly 2,000 organizations, some meaningful patterns have begun to emerge. We parsed all the Yield Giving donation information available to date and matched it with Internal Revenue Service View Details
- Web
Protecting Data at HBS | Information Technology
information that must be safeguarded as confidential and shared only with individuals with a need to know. Most university data falls into this broad classification This includes personal information,... View Details
- 18 Apr 2023
- Research & Ideas
The Best Person to Lead Your Company Doesn't Work There—Yet
details, including a top executive’s stake in the firm. So, the researchers turned to Pitchbook, a company that tracks buyout data for private companies. They added specific CEO data from Capital IQ,... View Details
- Web
Using Personal Devices for HBS Business | Information Technology
Personal Device Requirements Any device which will be used for HBS business or connect to HBS systems, data must adhere to the requirements listed in the Minimum Security Responsibilities: Computers and... View Details
- 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.)
- 21 Aug 2017
- Lessons from the Classroom
Companies Love Big Data But Lack the Strategy To Use It Effectively
the class toward her personal passion, precision medicine. “Health care is rife with examples like these—and such applications of big data will only expand over the coming years. I spend a lot of time... View Details
Keywords: by Dina Gerdeman
- 12 Apr 2022
- Research & Ideas
Swiping Right: How Data Helped This Online Dating Site Make More Matches
person is higher than me on the desirability scale. Maybe I’m more desirable than I thought I was. Confidence leads to better outcomes,” he says. Some love matches fizzled. When a targeting man was very desirable but a focal woman had low... View Details
Keywords: by Kara Baskin
Eliminating unintended bias in personalized policies using Bias Eliminating Adapted Trees (BEAT) - PNAS
An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those... View Details
- 07 Dec 2015
- Research & Ideas
The Rise of Personalized Entrepreneurial Finance and Other VC Trends
industries in different ways. Venture capital, for example, was once mostly reserved for institutional investors backed by endowments and pension funds. Today, it increasingly includes individual investors who are using technological tools and View Details
- 2015
- Working Paper
Selling to a Moving Target: Dynamic Marketing Effects in US Presidential Elections
By: Doug J. Chung and Lingling Zhang
We examine the effects of various political campaign activities on voter preferences in the domain of US Presidential elections. We construct a comprehensive data set that covers the three most recent elections, with detailed records of voter preferences at the... View Details
Keywords: Multi-channel Marketing; Personal Selling; Advertising; Political Campaigns; Dynamic Panel Data; Instrumental Variables; Marketing Communications; Political Elections; Advertising Campaigns; United States
Chung, Doug J., and Lingling Zhang. "Selling to a Moving Target: Dynamic Marketing Effects in US Presidential Elections." Harvard Business School Working Paper, No. 15-095, June 2015. (Revised December 2015.)
- 06 Jul 2017
- Working Paper Summaries
Do All Your Detailing Efforts Pay Off? Dynamic Panel Data Methods Revisited
- 2025
- Working Paper
Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning
Reinforcement learning (RL) offers potential for optimizing sequences of customer interactions by modeling the relationships
between customer states, company actions, and long-term value. However, its practical implementation often faces significant
challenges.... View Details
Keywords: Dynamic Policy; Deep Reinforcement Learning; Representation Learning; Dynamic Difficulty Adjustment; Latent Variable Models; Customer Relationship Management; Customer Value and Value Chain; Foreign Direct Investment; Analytics and Data Science
Ma, Liangzong, Ta-Wei Huang, Eva Ascarza, and Ayelet Israeli. "Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning." Harvard Business School Working Paper, No. 25-037, February 2025.