OBJECTIVE
Identify customers and
potential customers’ preferences for specific attributes of a product. It can
also be used to define the willingness to pay and the market share of different
products.
DESCRIPTION
Conjoint analysis is a surveying technique used
to identify the preferences of customers or prospective customers. The
respondents are shown several products with varying levels of different
attributes (e.g. color, performance) and are asked to rank the products. This
ranking is then used to calculate the utility of each attribute and product at
the individual level. The results can be used to define the best combination of
attributes and price or to simulate market share variations with competitors
(if competitors’ products are presented).
First of all it is
very important to spend enough time designing the analysis, starting with the
selection of the most important attributes and attributes’ levels.
There are three kinds
of methods:
- - Decompositional methods: the respondents are presented with different product versions, they rank them, and then the utilities are calculated at the attribute level by decomposing the observations;
- - Compositional methods: the respondents are asked to rate the different attributes’ levels directly;
- - Hybrid methods: compositional methods are used in the first phase to present a limited number of product versions in the second phase (they are useful when we have a large combination of attributes and levels).
In addition to the
methods described above, several kinds of adaptive conjoint analysis are used
to increase the efficiency of conjoint analysis, especially when the number of
attributes is large.
In conjoint analyses the
price is usually included as an attribute and the price utility is calculated.
However, this creates several problems:
- - By definition the price has no utility but is used in exchange for the sum of attributes’ utilities of the product;
- - The price ranges, number of levels, and perception of the respondents can bias the answers;
- - The purchase intention is not included, so we do not know whether the respondent would actually buy the product at the presented price (to avoid this problem partially, the respondents are usually asked to define a limit in the ranking below which products are not purchased).
The willingness to pay
is calculated as the exchange rate between price utility and attribute utility.
However, to avoid the abovementioned problems, we should consider a different
approach, for example dividing the analysis into two phases:
- 1- Perform a classic conjoint analysis for non-price attributes to define utilities;
- 2- Ask for the purchase intention of full product profiles with varying prices to define the lower and upper boundaries between which the respondent would agree to purchase the product.
With this information
a linear function can be estimated in which the price is the dependent variable
and the utility is the independent variable.
In the example we
present a classic conjoint analysis that includes the price as an additional
attribute. It includes one three-level attribute, one two-level attribute
(color), and three levels of price. Full-profile products are presented to the
respondents (compositional method), and they are asked to give a preference on a
scale from 0 to 10 (10 being the most preferred product) instead of ranking the
products.
Combinations and Stated Preferences of Conjoint Analysis
The utility of a respondent
is calculated by removing one level for each attribute to perform a multiple
linear regression with dummy variables. The removed variables will have a
utility of “0,” while the attributes included in the regression will have the
utility corresponding to the regression coefficients. After verifying the
significance of each attribute (p-value < 0.05; see 38.
LINEAR REGRESSION), the coefficients can be summed to build the
utility equation.
The utility equation
at the individual level can be used to define the most profitable combination
of attributes and price. It also allows the building of scenarios in which shifts
in the market share are calculated due to changes in the price or products’
attributes compared with the products offered by competitors. Especially for
the market share scenarios, it is important to define the purchase intention by
asking the respondents to state a “limit” beyond which they will not purchase
the product.
In the template a
second sheet is presented in which the price is not included as an additional
attribute but the respondents are asked about it separately, either directly or
by showing them different price–product combinations and asking for their
purchase intention. The last example usually performs better, but if we have numerous
combinations, we cannot show all of them.
Price–Utility Linear Relation
There are two main
approaches when creating surveys for conjoint analysis:
- - Classic conjoint: the respondents are shown all the combinations of attributes’ levels and are asked either to rank them or to define their preferences on a certain scale (e.g. 0 to 10). If the number of combinations is too large, we should either split the combinations and present them several times to the respondents or present only a certain percentage of all the possible combinations (randomly selected). We should also ask for a “limit,” that is, the ranking position or preference level at which the respondent would change his purchase intention.
- - Conjoint in which the price is not an attribute: the process is the same as the classic conjoint analysis, but the price is not included as an attribute. After asking the respondents to rank or set their preferences concerning several combinations of attributes’ levels, they are asked whether they would purchase a specific combination at a specific price. Depending on the response, either the utility or the price is modified to identify the WTP. If the number of combinations is limited, each one can be tested; if the number is large, not all combinations can be tested and the WTP must be calculated for different levels of utility and can then be estimated for all the combinations.
TEMPLATE
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