A common problem when developing a new product is that you have a general view on what the new product should be but need to refine some of the details, such as the price point, the size or the specific combination of features to offer. Or, you may have an existing product or service and wish to work out how best to improve it. One solution to test multiple versions of a product is to conduct multiple concept tests or choice tasks. The alternative is to use choice modeling, which is essentially the same as choice tasks, except that each respondent completes multiple choice tasks and the descriptions of the alternatives change from task to task.
The basic premise of choice modelling is that rather than researching preferences for concepts, we should instead research preferences for product attributes.
The theoretical assumptions of choice modeling
1. Each product product can be described by its attributes
The first key assumption of choice modeling is that products can be described by their attributes. The table below shows attributes in the packaged eggs market. It describes packaged eggs in terms of seven attributes. Each attribute consists of a series of attribute levels. We can see that the attribute Weight has four levels: 55g, 60g, 65g and 70g.
|Attribute||Level 1||Level 2||Level 3||Level 4|
|Weight||Average Egg Weighs 55g||Average Egg Weights 60g||Average Egg Weights 65g||Average Egg Weights 70g|
|Organic||BLANK [nothing shown]||Antibiotic and hormone free|
|Charity||BLANK [nothing shown]||10% of Revenue donated to RSPCA|
|Quality||Fresh Eggs (Caged)||Barn Raised||Free Range|
|Uniformity||All eggs appear the same||Some eggs appear different (e.g., shell colour)|
|Feed||BLANK [nothing shown]||Fed on grain and fish (high in Omega)||Fed on vegetables|
|Price||Range of price points from $3.35 to $6.50|
2. Attribute levels differ in their appeal
The second key assumption of choice modeling is that different attribute levels have different levels of appeal. Choice modelling studies tend to use the word utility instead of appeal, but they mean the same thing. For example, with the Egg Quality attribute, consumers may have a utility for caged eggs, barn raised eggs and free range eggs, and a purpose of the choice modelling is to estimate these utilities. Choice modeling studies only calculate the relative utility of different attribute levels. For example, we never estimate the actual appeal of free range eggs; rather, we estimate the appeal of free range eggs relative to some other attribute level, such as caged eggs or barn raised eggs. For this reason, we set one of the levels as having a utility of 0, and then the utilities of the other attribute levels are estimated relative to this attribute’s level. Most commonly, the least appealing attribute level is chosen to have a utility of 0.
3. The appeal of a product is the sum of the appeal of the attribute levels
4. People are most likely to choose the alternative with the highest appeal
The final key assumption of choice modeling is that people choose, or are most likely to choose, the product with the highest utility. This assumption can be weakened to deal with differences in distribution.
Choice modeling methods
A large number of techniques have been developed for choice modeling, including:
Most choice modeling methods involve the creation of a set of hypothetical products. This set is called the experimental design. This is the most complicated aspect of choice modeling and creation of an experimental design is typically done by either:
- Hiring an expert.
- Modifying an existing experimental design.
- Using special-purpose software. The main programs used for the design of choice modeling studies are SAS and the various products made by Sawtooth Software.
Various forms of regression are used to calculate the appeal of the different feature levels, working backwards from consumers’ evaluations of the hypothetical products.Cite error: Closing </ref> missing for <ref> tag
- ↑ This is an additive decomposition; the decompositions that involve multiplication are called multiplicative decompositions.