Conjoint Analysis

Conjoint Analysis is a research method in which consumer preference for products or services is measured. A typical characteristic of conjoint analysis is that the product or service is considered to be a combination of different product elements (brand, price, technical features, etcetera). The underlying hypothesis is that by knowing the value of each of the elements, we know the value for the whole product. This knowledge helps to analyze and predict purchase decisions.

Conjoint Analysis helps you to:
- Indicate preferences ('utility values') for each of the product elements that was tested in the interview. These indicators clarify the relevance and preference for each of the elements in a purchase decision.
- Simulate market situations by showing what percentage of the (survey) population would choose for which product, how this percentage would change if products would be changed or if new products would be introduced.

Conjoint analysis is best applied in the following situations:
- Product development,
- Pricing
- In-store communication
- Product or portfolio optimization.
- Needs-based segmentation

There are number of different types of conjoint analysis, for which software is available:
- Choice-based conjoint (CBC) Analysis
- Adaptive conjoint Analysis (ACA)
- Traditional conjoint (CVA)

Industry-specific applications of conjoint analysis
- Optional choice modeling
- ValueCreator
- Feature Value Modelling