You are here:
Home |
Research Services |
Advanced Analytics | Choice Modeling
Choice Modeling
Discrete choice, volumetric choice, and conjoint models are
analytical methods used to simulate real-world consumer purchasing behavior.
Our Advanced Analytics Consultants set up carefully controlled experiments
where consumers are simply asked to choose how many of each product to buy,
given predetermined sets of realistic conditions. The brands are presented
visually (including 3D simulation), if possible, in the context of advertising,
pricing, packaging, features, promotion, and other variables.
Choice modeling techniques can help marketing researchers:
-
Optimize product designs
-
Analyze price sensitivity
-
Bundle product and service features
-
Optimize brand strategy
-
Improve product line planning
The “choice” experimental design is tailored to the
specific objectives, constraints, and variables of the project. Customization
is the key to success because every category/brand has critical idiosyncrasies.
The resulting data are used to create a Marketing Decision Simulator in which
potential sets of marketing variables, product features, and marketing
conditions can be evaluated.
Conjoint Analysis
Conjoint analysis is ideal for optimizing new product designs by
identifying the most appealing sets of features. Conjoint analysis, sometimes
referred to as trade-off analysis, is a multivariate technique that
quantitatively measures the relative importance of different marketing
variables, attributes, or product features related to a brand, product, or
service. The distinguishing feature of this technique is that each
variable’s importance is determined implicitly or indirectly. That is,
the respondent is not consciously aware of what is being measured.
Discrete Choice Modeling
Discrete choice modeling is ideal for (a) product categories where
only one purchase is made over a longer period of time (for example, durable
goods, credit cards, cellular phones, etc.) and (b) complex
products (i.e., products with many different possible features). In these
carefully controlled experiments, current and potential customers are asked
which one product they would buy, given a realistic scenario including all of
the products or services that compete with one another in the marketplace. In
each scenario, the respondent is presented with a different set of marketing
stimuli and asked which brand or product would be purchased. The type of
decision that the respondents make in each scenario is designed to mimic the
real market, and again each variables’ importance is being determined
implicitly.
Volumetric Choice Modeling
Volumetric choice modeling is ideal for product categories where (a)
multiple products are purchased over relatively short periods of time and (b)
repeat purchase volume is an important consideration. In these experiments,
current and potential customers are asked how many of each product they would
buy, given a realistic scenario including all of the products or services that
compete with one another in the marketplace. The type of decision that the
respondents make in each scenario is designed to mimic the real world
marketplace, where varying quantities of multiple brands might be purchased
(including volumetric measures such as units purchased, dollars spent, etc.).
The overriding goal is to create realistic scenarios that properly represent
the buying behavior that we are striving to model. And, the modeling is
designed to implicitly measure the role and importance of each marketing
variable.
Other Advanced Analytic Services include:
Additional Resources from Decision Analyst
If you would like more information on
Advanced Analytics Services,
please contact Dr. John Colias by
email or call 1.800.ANALYSIS (262.5974).
Brochures
Related White Papers
|
