Discrete choice models for marketing: New methodologies for optional features and bundles

The topic of this Master Thesis is quantitative methodologies for optional features and bundles. The frame is the one of Quantitative Marketing Research, a field whose goal is to give market intelligence in forms of, among others, market shares, population clustering and scenario simulations. The particular problem we have worked on is the one of optional features and bundles i.e. services that can be selected for an extra price when purchasing a product. The technique we have used in our analysis is a discrete choice model, Choicebased Conjoint. The content of this thesis is based on an internship at the international market research company SKIM. The internship was jointly supervised by Senior Methodologist Kees van der Wagt (SKIM) and Prof. Dr. Richard Gill (Mathematisch Instituut Leiden). The two most important results of the thesis are new methodologies to study products with optional features and bundles. These methodologies produce utilities that match the respondent’s...Show moreThe topic of this Master Thesis is quantitative methodologies for optional features and bundles. The frame is the one of Quantitative Marketing Research, a field whose goal is to give market intelligence in forms of, among others, market shares, population clustering and scenario simulations. The particular problem we have worked on is the one of optional features and bundles i.e. services that can be selected for an extra price when purchasing a product. The technique we have used in our analysis is a discrete choice model, Choicebased Conjoint. The content of this thesis is based on an internship at the international market research company SKIM. The internship was jointly supervised by Senior Methodologist Kees van der Wagt (SKIM) and Prof. Dr. Richard Gill (Mathematisch Instituut Leiden). The two most important results of the thesis are new methodologies to study products with optional features and bundles. These methodologies produce utilities that match the respondent’s observed choices. Only knowing the estimated utilities, we are able to answer the questionnaire producing answers similar to the observed ones. The methodologies enjoy all typical properties of conjoint methodologies and can be used to calculate market shares, simulate scenarios etc. Their most interesting feature is that it is possible to tell if offering an option makes a product too complicated. They can also tell if their simple presence makes the product more appealing (halo effect). As far as we know, this is the first study in this promising field. The methodologies we propose are tested on two different datasets arising from studies conducted by SKIM. They have been developed with tests on simulated datasets. The software of choice for the estimation procedure was Sawtooth’s implementation of CBC HB. For reproducibility of experiments we also wrote a package in the open source language R reproducing the same algorithm. This package and Matlab codes used in simulations are found in the Appendix.Show less

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Discrete choice models for marketing: New methodologies for optional features and bundles