Running a Max-Diff analysis with XLSTAT-Conjoint

Max-Diff analysis is a marketing method allowing the user to know the consumer's expectations about a product and to model the importance of the attributes related to the product. The Max-Diff analysis method is now common in marketing. Modeling of consumer choice is a key area of marketing. Max-Diff analysis is used to understand attributes of a products, it is much less complicated than conjoint analysis but gives interesting results.

If you are looking to simulate markets, you should prefer conjoint analysis.

XLSTAT-Conjoint is a statistical program which allows you to run through all the analytical steps of Max-Diff analysis which can be divided in four steps:

  1. Choice of the relevant attributes to describe the products.
  2. Generation of design of experiments based on incomplete block designs.
  3. Collection of the results in Microsoft Excel sheets.
  4. Data analysis with a specific method: hierarchical bayes.

In this tutorial, we will detail the steps necessary for the implementation and interpretation of a Max-Diff analysis with XLSTAT-Conjoint.

Dataset to conduct a Max-Diff analysis

An Excel spreadsheet containing the results of this example can be downloaded by clicking here. The results are divided into different sheets:

  1. Attributes: this sheet contains the attributes selected to describe the products.
  2. Max-Diff Design: this sheet contains the generated design, and the choices given by the 5 individuals.
  3. Max-Diff: this sheet contains the results of Max-Diff analysis by hierarchical Bayes.

First step: Choosing the attributes

In this tutorial we will look at a simple simulated case of Max-Diff analysis based on tourism marketing.

An hotel brand wish to open a new hotel and would like to understand the importance of attributes of a vacation destination in order to define its new offer.

The first step in the MaxDiff analysis is done in collaboration with experts in the tourism market. We focus on choosing the important attributes to define a touristic destination. The selected attributes are:

  • Quality beaches
  • Cultural activities
  • Nightlife
  • Luxury hotel offer
  • Shopping around
  • Entertainment
  • Wildlife close by
  • Local cuisine

From these attributes, we want to evaluate which ones are more important for tourists. Max-Diff will present a set of attributes and ask each respondent to choose which one is the most important and which one is the least important.

Second step: Generation of the comparisons

XLSTAT-Conjoint allows you to create sets of attributes to be compared by the respondents. A design of experiments method is used.

Once XLSTAT is started, click on the CJT icon and choose the function Design for Max-Diff analysis.

design MaxDiff

Once the button is clicked, the dialog box appears.

You can then enter the name of the analysis, select the attributes names, enter the number of comparisons (8) and the number of profiles per comparison (4). These values have to be chosen by the user so that it is big enough to obtain significant results but not too long to have respondents focused enough throughout the questionnaire.

dialog box design MaxDiff

In the Output tab, do not activate the individual sheets for this example, they are not necessary. In a comprehensive analysis, they can be very useful in order to get the results filled directly by the individuals in individual Excel worksheets.

dialog box design MaxDiff

Once you click the OK button, the calculations are made, then the results are displayed.

The main table is the table of choice, found in the "Max-Diff" sheet and must be completed after the individuals have been interviewed. The choices are between 1 and 4 for each individual. There are two columns per individual, one for the most important attribute (best) and one for the least important attribute (worst).

design MaxDiff

Step 3: Fill the Max-Diff analysis table

The Max-Diff analysis tables can either be filled directly after interviewing individuals about their choices externally or directly using the individual sheets and automatic referencing of results. This is especially interesting in the context of Max-Diff analysis because completing the overall table can be complex.

design MaxDiff

In that case, individual 1 think Entertainment is the most important attribute and having wildlife around is the least important within the 4 presented attributes.

Step 4: Results of the analysis

As part of this analysis, 5 individuals have been questioned about their preferences in terms of touristic destination. The results are in the MaxDiff sheet.

To start the analysis, click the icon CJT and choose the function max-diff analysis. You can then select the data.

MaxDiff menu

Select the 10 columns of the table of responses completed by individuals as answers. Select the three columns of the attributes to be chosen from (without the names of the selections) as a table of choices.

MaxDiff dialog box

In the option tab, we select the method “Hierarchical Bayes” and we leave all the other values as default.

MaxDiff dialog box

Once you click the OK button, the computations are performed and the results are displayed.

MaxDiff dialog box

The Max-Diff scores are displayed as rescaled coefficients summing up to a 100. We see that Individual 1 thinks entertainment and local cuisine are very important, then shopping around and nightlife are also important. For individual 2, cultural activities, local cuisines, quality beaches and wildlife around are equally important. It seems that respondent 2 is more receptive to cultural holidays.

Then the descriptive statistics are shown. We see that in term of means for the 5 respondents, entertainment, local cuisines, quality beaches and wildlife around are the most important attributes.

 MaxDiff result

We can easily use Excel to represent these scores.

MaxDiff result

We would advise the hotel brand to focus on an hotel with nice sightseeing near a beach with good local foods.

More complex MaxDiff analysis can be done with XLSTAT-Conjoint.

Click here for other tutorials.

About KCS

Kovach Computing Services (KCS) was founded in 1993 by Dr. Warren Kovach. The company specializes in the development and marketing of inexpensive and easy-to-use statistical software for scientists, as well as in data analysis consulting.

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