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Marketing Engineering: Computer-Assisted Marketing Analysis and Planning, Revised 2nd Edition

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Marketing Engineering Revised 2nd Edition

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Authors: Gary L. Lilien, Arvind Rangaswamy, Arnaud De Bruyn
Pages: 538
Publisher: Trafford Publishing (2004)
ISBN-10: 1412022525
ISBN-13: 9781412022521

Marketing Engineering is more than just a book. It is an integrated suite of marketing concepts, models, and application software delivered to you at the price of a book. This book explains the underlying marketing concepts and models, and then allows you to "learn by doing" using the associated cases and exercises. This book includes the educational version of Marketing Engineering Classic Software v.2.4 on CD-ROM and a one-year software license (software is not compatible with Office 2007). To learn about our latest software offering, Marketing Engineering for Excel, which is available as a separate purchase, please visit our software page.

With our suite of products, you can go directly from theory to practice without a long lead time. Some of the most beneficial marketing models have traditionally only been used by a very small community of researchers and consultants. Now these powerful tools are available to most marketers, even those without a strong mathematical and statistical knowledge.

A Note from the Author:

Dear Marketing Engineering Revised Edition 2 User:

The several editions of Marketing Engineering that we have published since 1998 have been aimed at a fairly narrow, somewhat technical audience interested in bringing more scientific rigor to the marketing discipline. Versions of that book were adopted by more than 150 business schools on five continents. In 2007 we published Principles of Marketing Engineering to reach a broader, less technical audience. A key complement of that book, in response to user feedback, was Marketing Engineering for Excel (ME>XL), i.e., our Marketing Engineering software as an Excel Add-in. The response to that effort has been extremely positive and we have abandoned the original Marketing Engineering software platform, the one that produced the software complement to previous editions of this book.

Hence, as the note on the cover indicates, software is not included with the book. More importantly, when we reference software in the book, those references refer to a version of the software that is no longer available.

Gary Lilien

Subject Areas

The Marketing Engineering textbook includes the following topics: 

  • Market Response Models
  • Segmentation and Targeting
  • Positioning Analysis
  • Strategic Market Analysis
    • Market Demand and Trend Analysis
    • Product Life Cycle
  • Strategic Marketing Decision Making
    • Shared Experience Models: The PIMS Approach
    • Product Portfolio Models: The GE/McKinsey Approach
  • New Product Decisions
    • Conjoint Analysis for Product Design
    • Forecasting Sales using the Bass Model
    • Pretest Market Forecasting with the Assessor Model
  • Advertising and Communication Decisions
  • Salesforce and Channel Decisions
    • Reallocator Model
    • CALLPLAN Model
  • Price and Sales Promotion Decisions

Segmentation/Targeting Model (Classification)

on . Posted in Commercial Software Models

What you put in... What you get out...
  • Customers' importance ratings for each measure of value for offerings in a product class
  • Customer descriptors (demographic or firmographic variables)
  • Number, size, and profile of needs-based market segments
  • Identification of factors that differentiate segments, both in terms of needs and descriptors
  • Classification tool to allocate any potential customer to a segment based on customer descriptors

segmentationSegmentation/Targeting is an analytic technique that helps firms to segment customers in a market.

Segmentation is the process of classifying customers into homogenous groups (segments) such that each group of customers shares enough characteristics in common to make it viable for the firm to design specific offerings or products for selected segments. The application finds customer segments using needs-based variables called basis variables. Cluster analysis helps firms to:

  • Better understand their customers.
  • Identify different segments in a market.
  • Choose attractive customer segments for targeting its marketing programs.