Conjoint Analysis - Technical Implementation FAQ

Conjoint Analysis is one of the most effective models in extracting consumer behavior into an empirical or quantitative measurement. It evaluates products/services in a way no other method can. Traditional ratings surveys and analysis do not have the ability to place the "importance" or "value" on the different attributes, a particular product or service is composed of. Conjoint Analysis guides the end user into extrapolating his or her preference to a quantitative measurement. One of the most important strengths of Conjoint Analysis is the ability to develop market simulation models that can predict consumer behavior to product changes. With Conjoint Analysis, changes in markets or products can be incorporated into the simulation, to predict how consumers would react to changes.

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:-

Attributes:
• Price
• Airline
• Stops

Each of the attributes may have one or more levels. A level can be defined as any value the attribute can take. In the examples above, the attributes can have the following levels: -

1. Price
   • $100
   • $150
   • $200
2. Airline
   • Delta
   • Northwest
   • AA
3. Stops
   • None
   • 1
   • 2

It is also assumed that each of the levels is mutually exclusive. The levels should also have concrete and unambiguous meanings. For example - "Very Expensive" vs. "Cost of $500"

Choice based or Discrete Choice Conjoint is by far the most preferred model for a conjoint questionnaire. This is primarily because it models after consumer behavior in real-life. Most purchases that consumers make today are basically trade-off based. Will you buy a $150 ticket with 2 flight stops and No miles or a 200$ ticket with no stops and 4000 miles?