26 Spring 2010

software review

A Time for ReviewUpdates to several essential software applications (plus a book).

By Ken Deal

T he capabilities of several applications have been enhanced in recent months to the point where I felt compelled to devote this article to brief reviews of new versions

of several noteworthy programs that have been reviewed previously here. These include Sawtooth Software’s CBC/HB (Choice-Based Conjoint/ Hierarchical Bayes), first reviewed in the Summer 2001 issue of Marketing Research, PASW (SPSS) version 18, SYSTAT, reviewed in the Winter 2009 issue, and StatWizards, reviewed in the Spring 2008 issue. I’ve added a short review the new edition of Getting Started with Conjoint Analysis: Second Edition by Bryan Orme (Research Publish-ers, 2009).

Sawtooth Software CBC/HB (Hierarchical Bayes) version 5. Sawtooth Software (SS) has extended its hierarchical Bayes-ian analysis application for choice-based conjoint analysis to include several valuable additions. One can argue about which is most important but I suspect that all will be at least fairly important to most users.

At some point in their investigations, many analysts will in-tegrate covariates from outside the conjoint tasks into the cal-culations. Very often that activity occurs at the segmentation stage, and that segmentation would be conducted using many alternative methodologies. In version 5, CBC/HB provides for covariates to be entered into the HB analysis directly so that the part-worth utility coefficients will be calculated around those covariates rather than around the overall measures.

As SS often does, it collaborated with renowned academics to extend CBC/HB to utilize covariates within the estima-tion process. The effect of this algorithmic change is to more efficiently focus the calculations on two or more partitions of the survey sample. In the typical execution of a HB analysis, the upper model is shrunk, in the Bayesian sense, toward the aggregate mean. When using a binomial covariate, the upper model shrinks part of the sample toward one mean and the remaining toward the other mean; similarly for multinomial covariates.

In its technical papers, SS provides evidence of the ben-efits of entering effective covariates into the modeling. These include a reduction in the number of parameters needing estimation when compared to splitting the file and estimating HB coefficients for each split; improved prediction of holdout tasks; and greater separation among segments. The CBC/HB

manual states that the purpose is more to model heterogene-ity and better understand segments than to predict better. It also states that the benefit of covariates will be more greatly experienced when addressing sparse data sets where there is less information at the individual level.

Speed has also been enhanced, and the application au-tomatically installs as 64 bit on appropriate computers. A calibration tool has been included for rescaling part worths based on scaled ratings of purchase likelihoods for concepts presented individually and separately from the conjoint tasks; this is conducted in the purchase likelihood simulation model.

Furthermore, it is now possible to provide the data in *.csv layout format in addition to the *.cho format that has been the only supported format until this version. The design file and the data files can be combined in one file or provided in two separate files.

StatWizards version 4.2. StatWizards has been regularly updated by its developer, George Boomer. The newest version (4.2) will have been released by the time you read this review.

StatWizards is a useful application for designing discrete choice experiments (Design Wizard), preparing responses to the discrete choice tasks for analysis (Data Wizard) and cap-turing the analyzed data and building a simulator to support investigation of proposed market offering scenarios (Simula-tor Wizard). StatWizards is an Excel Add-in. Since my initial review in the summer 2006 issue, important changes have been added to this conjoint environment. The most signifi-cant recent additions are (1) the facility in Data Wizard for producing a *.cho data file, which is the default format for Sawtooth Software data, without having a StatWizards design file and (2) the ability in the simulator to use part-worth utili-ties directly from the Sawtooth Software CBC HB estimation application, CBC/HB.

Both of these procedures are very easy to implement. Perhaps the most typical use would be to take responses to choices that were designed using Design Wizard and simply producing a *.cho file and the corresponding *.att file. Both of those files are necessary for analyzing the results of a dis-crete choice experiment in Sawtooth Software. Most analysts would define a new study in the Sawtooth Software SMRT application by importing the *.cho and *.att files and calcu-lating the aggregate logit utilities. Then the individual-level

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part-worth utility coefficients would be estimated in CBC/HB (hierarchical Bayes) and imported into the Run Manager. I found both procedures very easy to run.

The next stage would be to either simulate scenarios of interest in SMRT or to build a simulator using Simulator Wizard. While those who own Sawtooth Software SMRT simulation application would likely use that for simulations, Simulator Wizard has some interesting features such as being able to perform calculations of potential revenue under appro-priate assumptions, forecasting diffusion of products using the Bass model, generating price curves and conveniently saving multiple simulations.

It is important to ensure that the table of part-worth utili-ties is in the exact format needed by Simulator Wizard. This can be done quite easily by following the format of the files provided for the tutorials. Basically, the format of the *.hbu file, without the leading design rows, is what is needed. Unfor-tunately, three essential columns are not included in the utility

csv file, but can be added easily. Also, it is necessary that the column headings are of the form “attribute name: attribute level” and, once again, that takes just a few minutes of typing.

Getting Started with Conjoint Analysis: 2nd Edition by Bryan Orme. The second edition of Getting Started with Conjoint Analysis was released in the summer of 2009 with a 2010 copyright date. The first edition of this book provided the first introduction to conjoint analysis in book format. I reviewed that book in the Winter 2005 issue of Marketing Research. Most of the second edition is identical to the earlier publication. The main differences lie in Chapter 3, Under-standing the Value of Conjoint Analysis, Chapter 11, Maxi-mum Difference Scaling, and Chapter 12, Adaptive Choice-Based Conjoint.

As usual with Orme’s writing, this book is clear, easily read, informative in content and authoritative in quality. Chapter 11 provides excellent motivation for using MaxDiff and includes a very useful list of concerns about this topic.

With all of the concerns regarding the decision rules used by customers and the resulting work on adapting survey methods to those decision rules, a chapter on adap-tive conjoint was necessary in this survey of the field. Orme provides valuable background on why adaptive approaches are important and how they have been developing. He next discusses the new Adaptive Choice-Based Conjoint (ACBC) developed by Sawtooth Software over the past several years, including the build-your-own section, screening questions and the choice tournament.

Comparisons between ACBC and CBC are provided along with contrasts regarding internal and external validity. With the number of projects conducted using ACBC approaching, or possibly exceeding 100, there is now a substantial body of work on which to judge its merits.

As I mentioned in my review of the first edition, the glos-sary to this book is just pure gold. An essential part of learn-ing any new discipline is understanding the language, and this glossary provides that plus excellent explanations of terms, many with examples provided.

SYSTAT version 13. I reviewed SYSTAT 12 during the past year (spring 2009) and, while I greatly liked many features, there were a few basic programming issues that were prob-lematic. SYSTAT 13 seems to have rectified the two main problems that bothered me about version 12, and version 13 has features that were not available in version 12. For those wanting to investigate unfamiliar statistical procedures, there is a very handy menu of examples that appears to cover all of the statistical procedures in this application. Each accesses an appropriate data set and automatically performs the calcula-tions and produces one or more very attractive and descriptive graphs to accompany the statistical output. While SYSTAT 13 is a very fast and attractive general purpose statistical applica-tion, there remain a few programming glitches that appear to be quite minor but will slightly reduce the usability of this program for some users.

PASW (SPSS) Statistics 18. In my opinion, PASW version 18 is the first revision of SPSS in some time that I consider

Simulator Wizard has some interesting features such as being able to perform calculations of potential revenue under

appropriate assumptions.

28 Spring 2010

an improvement over version 14. Version 15 had some problems coexisting with Vista, and versions 16 and 17 had usability problems that should not have crept into a major commercial application. While version 18 is not fully clear of programming problems, it is a significant improvement over the previous three versions. The look of the GUI has changed significantly and I find it attractive, descriptive and engaging. PASW continues to be one of several principal contenders for top position among general purpose statistical applications offering the most analytical procedures in an easy-to-use for-mat. Unfortunately, it seems like the positive additions have reduced its speed; it is now very slow to open and some of the calculations take longer than previously.

There have been some additions to the statistical methods and expansion of data manipulation. Many of those will make using PASW more rewarding to beginning to intermedi-ate analysts and might make it slightly less appealing to more advanced users who prefer to focus more on the statistics and less on the format and GUI.

ConclusionI greatly respect software providers who are regularly chal-

lenged to provide applications that keep pace with theoretical and conceptual advances in statistics and marketing research while needing to attend to their internal measures of success. This is not an easy job, especially when ownership changes, as has been the case with SPSS and SYSTAT. However, think-ing back even 10 years, I’m very grateful for the substantial contributions made by many software providers that have made the jobs of marketing research analysts more fulfilling, effective and efficient. l

Ken Deal is in strategic market leadership and health services management at the DeGroote School of Business, McMas-ter University, in Hamilton, Ontario. He is also president of marketPOWER research inc. in Winona, Ontario, and St. Joseph-du-Moine, Cape Breton Island, Nova Scotia. He may be reached at kendeal@marketpowerresearch.com.