Choice Based Conjoint Study - Discrete Choice

Conjoint Analysis is one of the most effective methods for translating consumer behavior into empirical and quantitative measurements. It evaluates products and services in a way no other method can. Traditional rating surveys and analyses are unable to assign importance or value to the different attributes that make up a product or service. Conjoint Analysis helps respondents translate their preferences into quantitative measurements. One of the key strengths of Conjoint Analysis is its ability to develop market simulation models that predict consumer responses to product changes. With Conjoint Analysis, changes in products or markets can be incorporated into simulations to predict how consumers may react.

Choice-based, or Discrete Choice Conjoint, is the most commonly used model for conjoint questionnaires. This is primarily because it closely reflects real-world consumer behavior. Most purchasing decisions today involve trade-offs. Would you choose a $150 ticket with two stops and no reward miles, or a $200 ticket with no stops and 4,000 miles?

Any product or service can be modeled as an entity with a set of attributes. For example, an airline ticket between Seattle and Miami may have the following attributes:

• Price
• Airline
• Stops

Here are some simple steps to help you prepare before beginning your online conjoint survey.

• Attributes: Define the attributes for your market segment. For most studies, try to keep the number of attributes below five. If you have a large number of attributes, try aggregating and combining these attributes into meaningful composite attributes.
• Levels: Define at least two levels for each of the attributes. Try to stick to a maximum of four or five levels per attribute.
• Minimal Respondent Base: Try to figure out if your respondent base is homogeneous. Are you interested in the interaction of the conjoint data between different demographics? For example, are you trying to figure out if Males place a higher value on miles than females in buying an airline ticket? In such a case, your minimum respondent base would be half of all participants (assuming equal distribution of males and females.)
• Minimal Choice Count for statistical validity: Try to come up with a minimum number of times a Level should be shown to the respondents to make a statistically valid sampling. For most conjoint studies, a minimum choice count of 100 to 150 provides reliable results. What this number represents is that all attribute levels should be presented at least 100 to 150 times to make the results of the study statistically significant.

You do not need to come up with both the Minimal Respondent Base and Minimal Choice Count. If you have one, the Concept Simulator can determine the other. More details about the Concept Simulator are provided below.

The goal of any conjoint survey is to assign specific values to the range of options buyers consider when making a purchase decision. Armed with this knowledge, marketers can focus on the most important features of products or services and design messages most likely to strike a chord with target buyers.