"Applied Probability Models in Marketing Research" Seminar

July 1, 2002
The DMA Seminar Center
1120 Avenue of the Americas
13th Floor (between 43rd and 44th Street)

9:00 a.m. - 2:30 p.m.

Central to a complete understanding of today's "leading edge" market research techniques is a sound intuitive appreciation of the basic foundations upon which these sophisticated tools are built. For example, both hierarchical Bayes models and latent class models build on simple probability modeling concepts (e.g., zero-order choice process, Poisson counts, conditional expectations, exponential interpurchase times) --- yet how many researchers are comfortable at precisely defining these concepts or explaining the motivation for using them?

This tutorial aims to fill in these gaps by bringing practitioners fully up to speed on the basic methods that may underlie many of their current or future research activities.

Our two broad objectives are:

• To review the basic terminology and logic associated with the area of probability models as applied to marketing research problems
• To develop participants' skills through a set of case studies that demonstrate the model building process in detail. We illustrate all of the steps required to develop a probability model, estimate its parameters, and interpret the results. Careful and extensive use is made of the Solver tool in Microsoft Excel, which makes it possible to construct all of these models within a familiar spreadsheet environment.

By the end of the morning half of this tutorial, participants should be quite comfortable with all of the aforementioned principles and models, and the managerial issues that surround them.

In the afternoon this tutorial extends this knowledge base in several directions.

• We explore how to incorporate the effects of covariates (e.g., marketing activities, demographics) into the basic counting, timing, and choice models.
• We examine some additional model structures to complement the set of distributions (and behavioral assumptions) that we worked with originally.
• (If we have enough time) we will demonstrate how to combine the basic models to develop "integrated" models of marketing phenomena that represent combinations of counting, timing, and/or choice behaviors. For example, the "stickiness," or total amount of time someone spends at a given web site in any given month is a combination of the number of times she visits the site (counting) and the duration of each visit (timing).

These extensions are explored through a set of case studies that demonstrate the model-building and application process in detail. To facilitate the learning process, we continue to rely on Excel for all of the empirical analyses.

Speakers:

Peter S. Fader, Associate Professor of Marketing, Wharton School of the University of Pennsylvania

Bruce Hardie, Assistant Professor of Marketing, London Business School

Register online or call our Customer Service Department at 212.790.1500. For more information about the Council, please contact Melissa Catalfamo at 212.768.7277, ext. 1608 or mcatalfa@the-dma.org. For more information about this and other events, please contact Heidi Jessop at 212.790.1531 or hjessop@the-dma.org.

Fees:

Research Council Member Rate: $75
DMA Member Rate: $90
Non-member Rate: $105

Peter S. Fader
Associate Professor of Marketing
Wharton School of the University of Pennsylvania

Peter S. Fader is Associate Professor of Marketing at the Wharton School of the University of Pennsylvania. He joined the faculty in 1987 after receiving his PhD at MIT. His research focuses on using data generated by new information technology, such as retail point-of-sale scanners and the Internet, to understand consumer preferences and to assist companies in fine-tuning their marketing tactics and strategies. Recent projects include predictive and explanatory models for electronic commerce (e.g., forecasting models for website usage and purchasing behavior) consumer packaged goods industries (e.g., models of new product trial and repeat purchasing patterns), and the music industry (e.g., understanding the role of radio airplay in generating album sales).

Professor Fader has been published in numerous professional journals and is an editorial board member for four leading Marketing journals (Journal of Marketing Research, Marketing Science, Journal of Interactive Marketing, and Marketing Letters). His teaching interests include Marketing Management, Marketing Research, and a new course, "Probability Models for Marketing and E-Commerce." He has won many teaching awards both at the undergraduate and MBA levels. He regularly teaches in a variety of executive education programs at Wharton's Aresty Institute, including active participation in several programs associated with WeBI (the Wharton e-Business Initiative). Most recently, he served as Academic Director for a unique "Online Conversion Workshop" that took place at Wharton in May 2001.

Bruce Hardie
Assistant Professor of Marketing, London Business School

Bruce Hardie is an Assistant Professor of Marketing at London Business School. He holds MA and PhD degrees from the University of Pennsylvania, and B.Com and M.Com degrees from the University of Auckland (New Zealand).

His primary research interest is in the area of stochastic modeling in marketing. Current projects include the development of probability models for new product sales forecasting and understanding online consumer behavior. Bruce's research has appeared in academic journals such as Marketing Science, the Journal of Marketing Research, Marketing Letters, and the Journal of Forecasting. He was the recipient of the AMA's 1997 Paul E. Green Award.

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