Conjoint Analysis involves surveying stakeholders about the relative importance of the attributes underpinning a product or outcome of interest.
Conjoint analysis is known as Choice Modelling or Discrete Choice Experiment. (1000Minds is also for Multi-Criteria Decision-Making.)
For example, Conjoint Analysis can be used to discover the preferences of car buyers with respect to ‘purchase price’ versus ‘fuel efficiency’, ‘top speed’, ‘safety features’, etc. Thus, Conjoint Analysis is the main technique used in Marketing Research and for designing new products.
Similarly, Conjoint Analysis can be used to discover the relative importance to patients of the various aspects of hospital services – ‘quality of medical care’ versus ‘waiting times’, ‘physical amenities’ versus ‘crowdedness’, etc.
Conjoint Analysis has its own terminology (different from MCDM):
- Concepts (or Profiles): Combinations of attributes representing particular alternatives (eg. products or services).
- Part-worth utilities: Values (or weights) representing the relative importance of the attributes.
Choice-based conjoint analysis
Applying the PAPRIKA method, 1000Minds estimates part-worth utilities by asking decision-makers to choose from pairs of concepts, involving a trade-off between the attributes. Hence this type of Conjoint Analysis is known as ‘choice-based’.
1000Minds‘ dedicated Conjoint-Analysis service is for:
- Discovering decision-makers’ part-worth utilities, representing the attributes’ relative importance.
- Ranking or prioritizing concepts, including choosing the ‘best’ (top-ranked) concept.
- Ranking or prioritizing all hypothetically possible concepts that might ever be considered.
Part-worth utilities can be easily exported to Excel – where, for example, market simulations can be performed.
Based on multiple decision-makers (consumers), scenarios involving competing product concepts can be evaluated – enabling market shares for each concept to be predicted.
To learn more about Conjoint Analysis, you might like to read the Wikipedia article.
Seminal articles in the Conjoint Analysis ‘Marketing’ literature include:
- PE Green, AB Krieger & Y Wind (2001), “Thirty years of conjoint analysis: reflections and prospects”. Interfaces 31, S56-S73.
- PE Green & V Srinivasan (1990), “Conjoint analysis in marketing: new developments with implications for research and practice”. Journal of Marketing 54, 3-19.
- PE Green & V Srinivasan (1978), “Conjoint analysis in consumer research: issues and outlooks”. Journal of Consumer Research 5, 103-23.
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