If the only tool you have is a hammer, you tend to see every problem as a nail.

Abraham Maslow, 1966

 

DCM - Discrete Choice Modeling

Discrete choice modeling has broad uses in marketing research applications due to its potential to get insight into the perceptions and behavior of customers. The most distinctive advantages of choice-based methods can be summarized as follows:
  • Choice is a natural manifestation of human behavior.
  • Choice is an action, in contrast to a statement.
  • Choice imposes minimal constraints on the response.
  • Choice is scale-free.
  • Choice is non-verbal.
  • Choices are less culturally, conventionally or habitually dependent than ratings or statements.
  • Overstatements or understatements are suppressed.

The general belief is choice-based models can give results much closer to real behavior than ratings based models. However, a choice is less informative than a stated value. More choice data must be collected to obtain an equivalent amount of information. Models for discrete events quite differ from models for metric values and imply different limitations. Results have often a format different from that known from traditional metric approaches. This all leads to uneasiness in marketing project managers who plan marketing research surveys and apply the results.

The objective of these web pages is to provide end-users of marketing research with an overview of selected DCM-related methods, to encourage exploitation of the methods, and to bridge the gap between the academic and commercial approaches to the subject.

The following aspects of DCM are dealt with.
  • Basic assumptions, conditions, properties and prospects.
  • Pros and cons of various approaches.
  • Topics concerning applications.
  • Understanding and use of selected types of results.
  • The described methods make part of the services offered by the g82, s.r.o., a Czech based marketing research and consultation company. 

    The most popular methods thriving on DCM are variants of choice based conjoint that have displaced metric conjoint methods to a large extent. If you would like to get acquainted with the basics of goals and uses of conjoint analysis you might wish to see a lightweight white-boarding video (5'36'') from Sawtooth Software on YouTube.


    Latest additions

    2020-08-07
    Instead of a summary of subjective statements, the importance of image attributes can be derived from the purchase behavior using the standard image questionnaire data and the analytical model of conjoint value analysis. An example is presented.
    2020-04-15
    Handling of the "None" constant alternative in a preference share simulator of substitutables using a simplified two-level nested logit.
    2020-03-02
    A MaxDiff-based method to estimate preferences between product concepts and the concept aspects has been developed. The method can handle a higher number of attributes than a CBC. A description, some results, and a live demo questionnaire are available.
    2019-10-09
    Question for Ranked Grid Analysis (RGA) is designed as a two-dimensional check-box grid with ranking. Ranking is possible in either horizontal or vertical or both dimensions. Any number of exclusive choices can be added. Examples of estimated brand and feature profiles from two market research studies show ranking leads to higher sensitivity and discrimination between brand-feature combinations. Link to a demo questionnaire is available.
    How many CBC tasks should be asked? Two easy rules of thumb and one based on the information entropy are presented.
    2018-03-09
    Estimation of a possible cannibalization maximum using CBC. The multinomial model is extended with a nest containing items involved in cannibalization and set as perfectly correlated.
    2017-12-30
    A relaxed non-compensatory modeling and simulation has been introduced as a compromise between fully non-compensatory and compensatory models. An Excel-based choice simulator with three simulation models is available as download.
    2017-06-29
    A Trial and Repeat Dissipation simulator has been made public. Besides the Excel-based sales simulator, the download includes an enlightening .pdf file.
    2017-01-17
    An example of a non-compensatory modeling and preference simulation, based on estimation of thresholds of acceptability of attribute levels.
    2016-12-19
    A simple comparative example of obtaining preference and acceptability for non-compensatory modeling.
    2016-03-27
    A standalone example of clustering based on relative perceptions obtained by ranking choices with ties from a large scale question battery.
    2016-03-05
    A method for DCM analysis of ranked choices with ties, typically from Q-sort exercises or large scale question batteries.
    2015-11-15
    An example of stated and evoked perceptions of attribute levels obtained by CSDCA method.
    2015-10-30
    Common Scale Discrete Choice Analysis has been amended with estimation of perceptual thresholds and a way to encompass larger number of attributes.
    2015-04-12
    OBIMA - Object Image Analysis, a DCM-based solution, has been introduced. Results from a test of four consumer electronics brands (Apple, Lenovo, Samsung and Sony) are presented. A live updated version of the questionnaire in English is available. 
    2015-01-18
    Based on latest experience the page on Common Scale Discrete Choice Analysis and live questionnaire demo have been updated.
    2014-12-13
    DCM Blog Cz with anonymous acces for DCM sympathizers speaking Czech has been started.
    2014-05-18
    An optimal consideration set at the time of making decision consists of 3 alternatives. A proof is given.
    2014-02-05
    DCM Portfolio Optimization algorithm has been enhanced to obtain a persuasive subset of items by taking account of the confusion due to a too wide range of offers (aka "tyranny of choice").
    2013-12-20
    Overview of the Common Scale Discrete Choice Analysis allowing comparison of level preferences across attributes. A live questionnaire demo is available.
    2013-12-18
    Example of Elasticity of Substitution used as generalized importance of quantitative CBC attributes.
    2013-04-08
    A robust CBC based estimation method of an Optimal Competitive Price.
    2013-01-18
    A live demo of a parametric CBC for a bank loan study.

     

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    g82, s.r.o.
    Žitná 2
    120 00 Praha 2
    Czech Republic
    www.g82.cz
    g82 s.r.o.
    Contact:   Luděk Brož
    Phone: (+420) - 731 652 319
    Fax: (+420) - 222 230 730
    E-mail: ludek.broz@g82.cz

     


    Disclaimer

    Any findings or conclusions expressed on these pages are solely the opinion of the author and may not be necessarily shared by the marketing research company g82, s.r.o.