Photo of Peter Fader

Peter Fader

Frances and Pei-Yuan Chia Professor

Co-Director - Wharton Customer Analytics Initiative

Professor of Marketing

Research Interests: lifetime value of the customer, sales forecasting for new products, using behavioral data to understand and forecast shopping/purchasing activities across a wide range of industries. managerial applications focus on topics such as customer relationship management

Links: CV, CoolNumbers.com, Google Scholar page

Contact Information

Address: 771 Jon M. Huntsman Hall, 3730 Walnut Street
University of Pennsylvania, Philadelphia, PA 19104
Email: faderp@wharton.upenn.edu
Office: (215) 898-1132

Overview

Professor Fader's expertise centers around the analysis of behavioral data to understand and forecast customer shopping/purchasing activities. He works with firms from a wide range of industries, such as consumer packaged goods, interactive media, financial services, and pharmaceuticals. Managerial applications focus on topics such as customer relationship management, lifetime value of the customer, and sales forecasting for new products. Much of his research highlights the consistent (but often surprising) behavioral patterns that exist across these industries and other seemingly different domains.

Many of these cross-industry experiences have led to the development of the Wharton Customer Analytics Initiative, an innovative research center that serves as a “matchmaker” between leading-edge academic researchers and top companies that depend on granular, customer-level data for key strategic decisions.

Professor Fader believes that marketing should not be viewed as a “soft” discipline, and he frequently works with different companies and industry associations to improve managerial perspectives in this regard. His work has been published in (and he serves on the editorial boards of) a number of leading journals in marketing, statistics, and the management sciences. He has won many awards for his teaching and research accomplishments

Research


  • Arun Gopalakrishnan, Eric Bradlow, Peter Fader (Under Review), A Cross-Cohort Changepoint Model for Customer-Base Analysis.  Abstract
  • Eric Schwartz, Eric Bradlow, Peter Fader (2014), Model Selection Using Database Characteristics: Developing a Classification Tree for Longitudinal Incidence Data, Marketing Science , 33 (2), 188 - 205.    Abstract
  • Elea McDonnell Feit, Pengyuan Wang, Eric Bradlow, Peter Fader (2013), Fusing Aggregate and Disaggregate Data with an Application to Multiplatform Media Consumption , Journal of Marketing Research, 50, 348 - 364.    Abstract
  • Valeria Stourm, Eric Bradlow, Peter Fader (Under Revision), Stockpiling in Linear Loyalty Programs.  Abstract
  • Vibhanshu Abhishek, Kartik Hosanagar, Peter Fader (Under Revision), Aggregation Bias in Sponsored Search Data: The Curse and The Cure.  Abstract
  • Zhiqiang Zheng, Peter Fader, Balaji Padmanabhan (2012), From Business Intelligence to Competitive Intelligence: Inferring Competitive Measures Using Augmented Site-Centric Data, Forthcoming at Information Systems Research    Abstract
  • Kinshuk Jerath, Peter Fader, Bruce Hardie (2011), New Perspectives on Customer ‘Death’ Using a Generalization of the Pareto/NBD Model, Marketing Science, 30 (5), 866-880    Abstract
  • David Schweidel, Eric Bradlow, Peter Fader (2011), Portfolio Dynamics for Customers of a Multi-Service Provider, Management Science, 57 (3), 471-486    Abstract
  • Wendy Moe, Peter Fader, Barry Kahn (Working), Buying Tickets: Capturing the Dynamic Factors that Drive Consumer Purchase Decisions for Sporting Events.    Abstract
  • Peter Fader (2011), Modèles marketing pour l’espace des médias sociaux, Recherche et Applications en Marketing, 26 (3), 120 - 121.  
  • Peter Fader, Bruce Hardie, Jen Shang (2010), Customer-Base Analysis in a Discrete-Time Noncontractual Setting, Marketing Science, 29 (6), 1086-1108    Abstract
  • Peter Fader, Bruce Hardie (2010), Customer-Base Valuation in a Contractual Setting: The Perils of Ignoring Heterogeneity, Marketing Science, 29 (1), 85-93    Abstract
  • Peter Fader, Bruce Hardie (2010), Comment on “On Estimating Current-customer Equity Using Company Summary Data, Journal of Interactive Marketing, 25 (February), 18-19  
  • David Schweidel, Peter Fader, Eric Bradlow (2009), Modeling Retention Within and Across Cohorts in Contractual Relationships, Journal of Marketing    Abstract
  • Peter Fader, Wendy Moe, "Integrating Online and Offline Retailing". In Inside the Mind of the Shopper: The Science of Retailing, edited by Herb Sorensen, (2009).
  • Peter Fader, Bruce Hardie (2009), Probability Models for Customer-Base Analysis, Journal of Interactive Marketing, 23 (1), 61-69    Abstract
  • Sam Hui, Peter Fader, Eric Bradlow (2009), Path Data in Marketing: An Integrative Framework and Prospectus for Model-Building, Marketing Science, 28 (2), 320-335    Abstract
  • Wendy Moe, Peter Fader (2009), The Role of Price Tiers in Advance Purchasing of Event Tickets, Journal of Service Research, 12 (1), 73-86.    Abstract
  • Sam Hui, Eric Bradlow, Peter Fader (2009), Testing Behavioral Hypotheses using an Integrated Model of Grocery Store Shopping Paths, Journal of Consumer Research, 36 (3), 478-493.    Abstract
  • David Schweidel, Peter Fader (2009), Dynamic Changepoints Revisited: An Evolving Process Model of New Product Sales, International Journal of Research in Marketing, 26 (2), 119-124.    Abstract
  • Sam Hui, Peter Fader, Eric Bradlow (2009), The Traveling Salesman Goes Shopping: The Systematic Deviations of Grocery Paths from TSP-Optimality, Marketing Science, 28 (3), 566-572    Abstract
  • David Schweidel, Peter Fader, Eric Bradlow (2008), A Bivariate Timing Model of Customer Acquisition and Retention, Marketing Science, 27 (5), 829–843.    Abstract
  • Blake McShane, Moshe Adrian, Eric Bradlow, Peter Fader (2008), Count Models Based on Weibull Interarrival Times, Journal of Business and Economic Statistics, 26 (3), 369-378    Abstract
  • David Schweidel, Peter Fader, Eric Bradlow (2008), Modeling Service Retention Within and Across Cohorts under Limited Information, Journal of Marketing, 72 (1), 82-94    Abstract
  • Ka Lok Lee, Peter Fader, Bruce Hardie (2007), How to Project Patient Persistency, Foresight: The International Journal of Applied Forecasting    Abstract
  • Peter Fader, Bruce Hardie (2007), How to Project Customer Retention, Journal of Interactive Marketing, 21 (1), 76 - 90.    Abstract
  • Peter Fader, Bruce Hardie, Kinshuk Jerath (2007), Estimating CLV Using Aggregated Data: The Tuscan Lifestyles Case Revisited, Journal of Interactive Marketing, 21 (3), 55 - 57.    Abstract
  • Michael Braun, Peter Fader, Eric Bradlow, Howard Kunreuther (2006), Modeling the “Pseudodeductible” in Insurance Claims Decisions, Management Science, 52 (8), 1258 - 1272.    Abstract
  • Peter Fader, Bruce Hardie, Ka Lok Lee (2006), More than Meets the Eye, Marketing Research  
  • Peter Fader, Bruce Hardie, Ka Lok Lee (2005), ’RFM’ and ‘CLV’: Using Iso-value Curves for Customer Base Analysis, Journal of Marketing Research  
  • Peter Fader, Bruce Hardie, Ka Lok Lee (2005), Counting Your Customers’ the Easy Way: An Alternative to the Pareto/NBD Model, Marketing Science, 24, 275 - 284.    Abstract
  • Wagner Kamakura, Carl F. Mela, Asim Ansari, Anand Bodapati, Peter Fader, Raghuram Iyengar, Prasad Naik, Scott Neslin, Baohong Sun, Peter Verhoef, Michel Wedel, Ron Wilcox (2005), Choice Models and Customer Relationship Management, Marketing Letters, 16 (3-4), 279 - 291.    Abstract
  • Jeffrey Larson, Eric Bradlow, Peter Fader (2005), An Exploratory Look at Supermarket Shopping Paths, International Journal of Research in Marketing, 22 (4), 395 - 414.  
  • Peter Fader, Bruce G.S. Hardie, Ka Lok Lee (2005), RFM and CLV: Using Iso-value Curves for Customer Base Analysis, , Journal of Marketing Research, Vol XLII, 415-430.    Abstract
  • Peter Fader, Bruce G.S. Hardie (2005), The Value of Simple Models in New Product Forecasting and Customer-Base Analysis,  Abstract
  • Bruce G.S. Hardie, Peter Fader (2005), The Value of Simple Models in New Product Forecasting and Customer-Base Analysis, , Applied Stochastic Models in Business and Industry, 21 (4-5), 461-473.    Abstract
  • Peter Fader, Bruce G.S. Hardie, Chun-Yao Huang (2004), A Dynamic Changepoint Model for New Product Sales Forecasting, , Marketing Science, 23 (Winter), 50-65.    Abstract
  • Wendy Moe, Peter Fader (2004), Capturing Evolving Visit Behavior in Clickstream Data, , Journal of Interactive Marketing, 18 (Winter), 5-19.    Abstract
  • Wendy Moe, Peter Fader (2004), Dynamic Conversion Behavior at e-Commerce Sites, , Management Science, 50 (3), 326-335.    Abstract
  • Young-Hoon Park, Peter Fader (2004), Modeling Browsing Behavior at Multiple Web Sites, , Marketing Science, 23 (Summer), 280-303.    Abstract
  • Eric J Johnson, Wendy Moe, Peter Fader, Steven Bellman, Jerry Lohse (2004), On the Depth and Dynamics of Online Search Behavior, , Management Science, 50 (3), 299-308.    Abstract
  • Peter Fader, Bruce G.S. Hardie (Working), Can We Infer ‘Trial and Repeat' Numbers From Aggregate Sales Data?.    Abstract
  • Peter Fader, Bruce G.S. Hardie, Robert Zeithammer (2003), Forecasting New Product Trial in a Controlled Test Market Environment, , Journal of Forecasting, 22, 391-410.    Abstract
  • Peter Fader, Bruce Hardie (2002), A Note on an Integrated Model of Customer Buying Behavior, European Journal of Operational Research, 139 (3), 682 - 687.  
  • Eric Bradlow, Bruce Hardie, Peter Fader (2002), Bayesian Inference for the Negative Binomial Distribution via Polynomial Expansions, Journal of Computational and Graphical Statistics, 11 (1), 189 - 202.  
  • Wendy Moe, Peter Fader (2002), Using Advance Purchase Orders to Forecast New Product Sales, , Marketing Science, 21 (Summer), 347-364.    Abstract
  • Eric T. Bradlow, Peter Fader (2001), A Bayesian Lifetime Model for the ‘Hot 100' Billboard Songs, , Journal of the American Statistical Association, 96, 368-381.  
  • Peter Fader, Bruce G.S. Hardie (2001), Forecasting Repeat Sales at CDNOW: A Case Study, , Interfaces, 31, S94-S107.    Abstract
  • Wendy Moe, Peter Fader (2001), Modeling Hedonic Portfolio Products: A Joint Segmentation Analysis of Music CD Sales, , Journal of Marketing Research, 38 (August), 376-385.    Abstract
  • Wendy Moe, Peter Fader (2001), Uncovering Patterns in Cybershopping, , California Management Review, 43 (Summer), 106-117. (Reprinted in Understanding Consumer Behavior, Harvard Business School Publishing, 2002.).  
  • Peter Fader, Bruce Hardie (2000), A Note on Modelling Underreported Poisson Counts, Journal of Applied Statistics , 27 (8), 953 - 964.
  • B. G. S. Hardie, Leonard Lodish, Peter Fader, A. P. Sutcliffe, W. T. Kirk (Working), Attribute-based Market Share Models: Methodological Development and Managerial Applications.
  • Bruce G.S. Hardie, Peter Fader, Michael Wisniewski (1998), An Empirical Comparison of New Product Trial Forecasting Models, , Journal of Forecasting, 17, 209-229.    Abstract
  • Peter Fader, Bruce Hardie (1996), Modeling Consumer Choice Among SKUs, Journal of Marketing Research, 33, 442 - 452.  
  • C. B. Bhattacharya, Peter Fader, Leonard Lodish, Wayne Desarbo (1996), The Relationship Between the Marketing Mix and Share of Category Requirements, Marketing Letters, 7, 5 - 18.
  • Russell S. Winer, Randolph E. Bucklin, John Deighton, Tulin Erdem, Peter Fader, J. Jeffrey Inman, Hotaka Katahira, Kay Lemon, Andrew Mitchell (1994), When Worlds Collide: The Implications of Panel Data-Based Models for Consumer Behavior, Marketing Letters, 5, 385 - 394.
  • Peter Fader, David Schmittlein (1993), Excess Behavioral Loyalty for High-Share Brands: Deviations from the Dirichlet Model for Repeat Purchasing, Journal of Marketing Research, 30, 478 - 493.    Description
  • Bruce Hardie, Eric J Johnson, Peter Fader (1993), Modeling Loss Aversion and Reference Dependence Effects on Brand Choice, Marketing Science, 12, 378 - 394.  
  • Peter Fader, James M Lattin (1993), Accounting for Heterogeneity and Nonstationarity in a Cross-Sectional Model of Consumer Purchase Behavior, Marketing Science  
  • Peter Fader (1993), “Integrating the Dirichlet-Multinomial and Multinomial Logit Models of Brand Choice,, Marketing Letters, 4, 99 - 112.  
  • Peter Fader, James M Lattin, John D.C. Little (1992), Estimating Nonlinear Parameters in the Multinomial Logit Model, Marketing Science, 11, 372 - 385.  
  • Peter Fader, Leonard Lodish (1990), A Cross-Category Analysis of Category Structure and Promotional Activity for Grocery Products, Journal of Marketing, 54, 52 - 65.  
  • Peter Fader, Leigh McAlister (1990), An Elimination by Aspects Model of Consumer Response to Promotion Calibrated on UPC Scanner Data, Journal of Marketing Research, 27, 322 - 332.  
  • Peter Fader, John Hauser (1988), Implicit Coalitions in a Generalized Prisoners' Dilemma, Journal of Conflict Resolution, 32, 553 - 582.  
  • Leigh McAlister, Max Bazerman, Peter Fader (1986), Power and Goal Setting in Channel Negotiations, Journal of Marketing Research, 23, 228 - 236.

Awards And Honors

  • AMA 25-year Consortium Fellow Research Excellence Award, 2009
  • Finalist, O'Dell Award for Best Paper in Journal of Marketing Research, 2009
  • David Hardin Award for best paper published in Marketing Research magazine, 2007
  • EXPLOR Award from the American Marketing Association for “the most innovative use of technology that advances marketing research”, 2007
  • Robert B. Clarke Outstanding Educator Award, given by the Direct Marketing Educational Foundation to honor an academic's overall achievement in direct/interactive marketing, 2007
  • Best paper award at the Advanced Research Techniques Forum, 2006 Description
  • Paul E. Green Award, 1997, 2006 (given annually by the American Marketing Association for the best article published in the Journal of Marketing Research for its “potential to contribute significantly to the practice of marketing research”), 2006 Description
  • Journal of Interactive Marketing Best Paper Award, 2005 Description

In The News

Knowledge @ Wharton

Teaching

Managing the Value of Customer Relationships

Applied Probability Models in Marketing

Courses

Previous

  • MKTG399 - Independent Study

  • MKTG476 - Applied Probability Models for Marketing

    This course will expose students to the theoretical and empirical "building blocks" that will allow them to construct, estimate, and interpret powerful models of consumer behavior. Over the years, researchers and practitioners have used these models for a wide variety of applications, such as new product sales, forecasting, analyses of media usage, and targeted marketing programs. Other disciplines have seen equally broad utilization of these techniques. The course will be entirely lecture-based with a strong emphasis on real-time problem solving. Most sessions will feature sophisticated numerical investigations using Microsoft Excel. Much of the material is highly technical.

  • MKTG775 - Managing Customer Value

    As the concept of CRM becomes common parlance for every marketing executive, it is useful to take a step back to better understand the various different behaviors that underlie the development of successful CRM systems. These "behaviors" include customer-level decisions, firm actions, and the delicate but complex interplay between the two. Accordingly this course is comprised of four main modules.

    We start with the discussion of customer profitability - focusing on the concepts of "customer lifetime value" and "customer equity". We will examine how to measure long-run customer profitability in both business-to-customer and business-to-business environments, and the uses of these measures as major components assessing overall firm valuation. Second, we move to the value that the firm provides to its customers - better understanding the true nature of customer satisfaction and its non-trivial relationship with firm profitability. Third, we examine each of the three main components of the firm's management of its customer base: customer acquisition, development, and retention - and the complex resource allocation task that must be balanced across them. Finally, we conclude with a discussion of various tactical and organizational aspects of customer relationship management.

  • MKTG776 - Applied Probability Models in Marketing

    This course will expose students to the theoretical and empirical "building blocks" that will allow them to develop and implement powerful models of customer behavior. Over the years, researchers and practitioners have used these methods for a wide variety of applications, such as new product sales forecasting, analyses of media usage, customer valuation, and targeted marketing programs. These same techniques are also very useful for other types of business (and non-business) problems. The course will be entirely lecture-based with a strong emphasis on real-time problem solving. Most sessions will feature sophisticated numerical investigations using Microsoft Excel. Much of the material is highly technical.

  • MKTG899 - Independent Study

    A student contemplating an independent study project must first find a faculty member who agrees to supervise and approve the student's written proposal as an independent study (MKTG 899). If a student wishes the proposed work to be used to meet the ASP requirement, he/she should then submit the approved proposal to the MBA adviser who will determine if it is an appropriate substitute. Such substitutions will only be approved prior to the beginning of the semester.

  • MKTG995 - Dissertation

  • MKTG999 - Supervised Independent Study

    Requires written permission of instructor and the department graduate adviser.