CBC-related papers

This paper discusses a real-world case study using Choice-Based Conjoint. The Choice-Based Conjoint approach is shown to be a powerful method for uncovering brand x price interactions. The authors show that neglecting that important interaction would have been a bad assumption for their research study. This paper was originally presented at the ART Forum and is an excellent paper for researchers interested in Discrete Choice Modeling.

download paper

This paper discusses successful strategies for using CBC properly, and warns against common pitfalls. Topics include: using prohibitions, determining number of attribute levels to include, sample size, precision of estimates, counting analysis versus logit analysis, whether to include "None" in the questionnaire and in analysis, calibrating CBC results to market shares, and IIA and the red bus/blue bus problem.

download paper

Sawtooth Software's founder, Rich Johnson, describes the events that led to the development of the CBC software product. This document provides insights into key developments that have made CBC the most commonly used conjoint software product for conducting conjoint-related studies. An enjoyable read to develop an appreciation for the key people and main forces behind the creation of a classic.

download paper

"Choice-Based Conjoint" Analysis (CBC) is a PC-based software for conducting choice-based conjoint studies. The main characteristic distinguishing choice-based conjoint analysis from other types is that the respondent expresses preferences by choosing concepts from sets of concepts, rather than by rating or ranking them. This paper discusses the method of choice-based conjoint analysis from a practitioner-oriented point of view, and describes Sawtooth Software's CBC System for choice-based conjoint analysis in some detail. It also provides suggestions about how to select a particular conjoint method from the variety of those available, considering characteristics of the research problem at hand.

download paper

This paper demonstrates why recognizing differences between segments or respondents results in more predictive and valid choice simulations than simple aggregate models. Latent Class and ICE solutions are shown to better handle the traditional "Red bus/Blue bus" problem, cross-elasticities and interaction effects than the equivalent main-effects model using aggregate logit. Though cross-effects and IIA violations can be modeled in the aggregate, it requires modeling expertise and software other than CBC. The author concludes that it is beneficial to start with underlying utilities that are less susceptible to the "Red bus/Blue bus" problem.

download paper

This paper, by practitioner Jon Pinnell, was first delivered at the 2004 Sawtooth Software Conference, as a comment on Joel Huber's paper (also available for download within this library) entitled "Conjoint Analysis: How We Got Here and Where We Are--An Update." Jon gives many practical pieces of advice based on his years as a researcher using CBC analysis. His suggestions include: use choice-based rather than ratings-based tasks; use randomized rather than fixed designs; use more alternatives per task; use first-choices rather than allocations or full ranks; use HB; and to be cautious with partial-profile designs.

This article is a good review of best practice, with suggestions based on numerous methodological and commercial CBC studies.

download paper

CBC is a popular tool for studying brand and price effects for packaged goods and beverages. Under the proper conditions, it can produce quite accurate predictions of buyer behavior. The purpose of this document is to discuss some of the common approaches (and mistakes made) with past versions of our CBC software, and to point out some new capabilities available with the latest version of the Advanced Design Module for CBC/Web.

Common mistakes made were based on excessive use of level prohibitions within CBC software. Also, given the previous limitations of no more than 15 levels for brand and 16 concepts per choice task, it was difficult for researchers to represent the variety of unique brands available to buyers. The new version of CBC/Web Advanced Design Module offers up to 100 levels per attribute and 100 concepts per task, and supports a realistic "Shelf-Display" where the choice tasks look like shelves in a store, with products resting on the shelves.

download paper

The authors (Orme and Heft) provide evidence that, under proper conditions, conjoint analysis can accurately predict what buyers do in the real world. Their results are based on CBC interviews conducted in grocery stores, where the CBC results were used to predict actual sales for three product categories of packaged goods from those same stores with good success.

A second purpose of the paper is to show that capturing heterogeneity (reflecting differences in preference between groups or individuals) with Latent Class or ICE can improve predictions. Many complex effects (substitution, cross-effects and interactions) can be accounted for with disaggregate Main Effect models. The authors note that complex terms can be built into large aggregate logit models, but that such models risk overfitting. Moreover, that approach places a great deal of responsibility on the analyst to choose the right combination of terms. This paper was originally presented at the 1999 Sawtooth Software Conference.

download paper

In this article, the author (Orme) uses random split-sample experiments to test different ways of asking CBC and Adaptive CBC (ACBC) questionnaires. Specifically, he examines:

• Use of minimal overlap vs. modest overlap for CBC questionnaires (modest overlap seems to improve results)
• ACBC for small designs--just 4 attributes (ACBC is shown to work as well as CBC)
• Placing “Unacceptable” screening questions prior to “Must-Have” screening questions in ACBC (seems to work better)
• Individual-level (customized) utility constraints in ACBC (no benefit shown for this 4-attribute data set, though benefits should be greater for larger, more demanding designs)
• Whether giving respondents a “consistency game” will improve their data and their experience (minimal gains in fit observed, but with the risk of annoying about 1/5 of the respondents

download paper

When planning a choice-based conjoint study, one must decide how many choice tasks to give each respondent. Too many may produce biased or noisy results, and too few will reduce precision. We re-analyzed data from 21 commercial studies, conducted in several countries and languages, with widely varying product categories, to see how results depend on the number of tasks respondents are given. [The paper was awarded "Best Presentation" at the ART Forum at Beaver Creek in June 1996.]

download paper

In this paper (originally published in our 1997 Sawtooth Software Conference Proceedings) Tom Pilon of TRAC, Inc. presents some additional types of analysis that can be done using standard CBC data. He reports results from a beer study, and shows how cross-elasticities for brands can be calculated (by regressing the log of choice volume on the log of price) and incorporated into a market simulator.

Pilon argues that the standard logit simulator which assumes constant cross-elasticity across brands was not entirely realistic for the beer market. A cross-elasticity simulator lets brands that compete closely (perceived as close substitutes) take relatively more share from one another as a result of price changes than from brands which are not perceived to be as substitutable. Pilon also demonstrates how to convert a cross-elasticity matrix into a "brand similarities matrix" for use in an MDS perceptual map. Brands which compete closely with one another are situated close to one another on the map.

download paper

Huber, Wittink, Johnson and Miller report on a methodological study which featured an ACA interview between two short Choice-Based Conjoint modules. The study sought to discover if 1) the Choice-Based Conjoint utilities shifted when interrupted by ACA; 2) if the results from ACA were different from Choice-Based Conjoint; and 3) if ACA can be modified to approximate the Choice-Based results. They conclude that the answer to all three questions is yes. The authors suggest that ACA may be better at predicting how buyers would choose given sufficient information and time, whereas Choice-Based Conjoint results portray customers who are primarily motivated by brand name and price, and who have little time to make a decision. Originally published in 1992 Sawtooth Conference Proceedings.

download paper