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

Managing the Value of Customer Relationships

Applied Probability Models in Marketing


  • 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.

    MKTG476401  ( Syllabus

    STAT476401  ( Syllabus

  • 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.

    MKTG776001  ( Syllabus

  • 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.

    MKTG899005 

  • MKTG995 - Dissertation

    MKTG995018 

  • MKTG999 - Supervised Independent Study

    Requires written permission of instructor and the department graduate adviser.

    MKTG999005