The 21st century business environment demands more analysis and rigor in marketing decision making. Increasingly, marketing decision making resembles design engineering-putting together concepts, data, analyses, and simulations to learn about the marketplace and to design effective marketing plans. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering (that is, combining art and science to solve specific problems).

Marketing Engineering is the systematic approach to harness data and knowledge to drive effective marketing decision making and implementation through a technology-enabled and model-supported decision process. (For more information on Excel-based models that support these concepts, visit DecisionPro.biz.)

We have designed this book primarily for the business school student or marketing manager, who, with minimal background and technical training, must understand and employ the basic tools and models associated with Marketing Engineering.

We offer an accessible overview of the most widely used marketing engineering concepts and tools and show how they drive the collection of the right data and information to perform the right analyses to make better marketing plans, better product designs, and better marketing decisions.

What's New In the 2nd Edition

While much has changed in the nearly five years since the first edition of Principles of Marketing Engineering was published, much has remained the same. Hence, we have not changed the basic structure or contents of the book. We have, however

• Updated the examples and references.
• Added new content on customer lifetime value and customer valuation methods.
• Added several new pricing models.
• Added new material on "reverse perceptual mapping" to describe some exciting enhancements to our Marketing Engineering for Excel software. Provided some new perspectives on the future of Marketing Engineering.
• Provided better alignment between the content of the text and both the software and cases available with Marketing Engineering for Excel 2.0.

Gary L. Lilien is Distinguished Research Professor of Management Science at the Smeal College of Business at Penn State. He is also cofounder and Research Director of the ISBM. He is the author or co-author of twelve books (including Marketing Models with Phil Kotler, Marketing Engineering and Principles of Marketing Engineering), as well as over 100 professional articles. He is on the editorial board of the International Journal for Research in Marketing; is functional Editor for Marketing for Interfaces, and is Area Editor at Marketing Science. He was Editor in chief of Interfaces for six years. He is an Inaugural INFORMS Fellow, was honored as Morse Lecturer for INFORMS and also received the Kimball medal for distinguished contributions to the field of operations research. He is on the Board of Directors of the American Marketing Association.

Arvind Rangaswamy is Senior Associate Dean and Anchel Professor of Marketing at Penn State. Prof. Rangaswamy has published numerous articles in such leading journals as Marketing Science, Journal of Marketing Research, Journal of Marketing, Management Science, Information Systems Research, Service Science, International Journal of Research in Marketing, Marketing Letters, Psychometrika, Multivariate Behavioral Research, and Journal of Economics and Statistics. He was an Area Editor for Marketing Science (1997-2011) and serves on the editorial boards of the Journal of Interactive Marketing; International Journal of Intelligent Systems in Accounting, Finance and Management; Journal of Service Research; Journal of Business-to-Business Marketing; and Journal of Electronic Commerce.

Arnaud De Bruyn is Professor of Marketing and Head of the Marketing Department at ESSEC Business School, Paris, France, and Associate Director for the Marketing Engineering Program at the Institute for the Study of Business Markets at Penn State. His work has been published in Marketing Science, Management Science, International Journal of Research in Marketing, Information Systems Research, etc., and serves on the editorial board of IJRM, Journal of Interactive Marketing and RAM. His work on the quantitative analysis of viral marketing behavior, co-authored with Gary Lilien, has won the IJRM Best Paper Award.