Conjoint Analysis

Chapter 8

Traditional Conjoint Analysis with Excel

A traditional conjoint analysis may be thought of as a multiple regression problem. The respondent’s ratings for the product concepts are observations on the dependent variable. The characteristics of the product or attribute levels are observations on the independent or predictor variables. The estimated regression coefficients associated with the independent variables are the part-worth utilities or preference scores for the levels. The R2 for the regression characterizes the internal consistency of the respondent. Consider a conjoint analysis problem with three attributes, each with levels as follows: Brand A B C Color Red Blue Price $50 $100 $150

For simplicity, let us consider a full-factorial experimental design. A full-factorial design includes all possible combinations of the attributes. There are 18 possible product concepts or cards that can be created from these three attributes: 3 brands × 2 colors × 3 prices = 18 cards Further assume that respondents rate each of the 18 product concepts on a scale from 0 to 10, where 10 represents the highest degree of preference. Exhibit 8.1 shows the experimental design. We can use Microsoft Excel to analyze data from traditional conjoint questionnaires. This chapter shows how to code, organize, and analyze data from one hypothetical respondent, working with spreadsheets and spreadsheet functions. Multiple regression functions come from the Excel Analysis ToolPak add-in.

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Reprinted from Orme, B. (2010) Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research. Second Edition, Madison, Wis.: Research Publishers LLC. c 2010 by Research Publishers LLC. No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, mechanical, electronic, photocopying, recording, or otherwise, without the prior written permission of the publisher.

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Traditional Conjoint Analysis with...