Conjoint Analysis

Conjoint analysis is the optimal market research approach for measuring the value that consumers place on features of a product or service. This commonly used approach combines real-life scenarios and statistical techniques with the modeling of actual market decisions.

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The following are different models of conjoint analysis commonly used today:

  • Choice-based conjoint analysis
  • Adaptive choice-based conjoint analysis
  • Self-explicated conjoint analysis
  • Menu-based conjoint analysis
  • MaxDiff (the cousin of conjoint analysis)

These various types of conjoint analyses assess the evaluations individuals place on the different features of a given product or feature. Additionally, these evaluations are analyzed to yield estimates of product preferences that equate to choice (market) share estimates.

Why conduct conjoint analysis?

Conjoint measurement tasks are very flexible, ranging from evaluation of attributes, to ratings of products, to selection of preferred products from a choice set. Conjoint analysis provides answers to many critical managerial questions like the following:

  • What is the best possible design for a new product?
  • What is our value compared to our competitors?
  • How can an existing product be improved?
  • How important is our brand name?
  • How much market share can a product hold?
  • What is the price sensitivity of the product?
  • What is the price value of each feature?

Menu-based conjoint analysis: in the spotlight

One conjoint analysis model that is gaining momentum in the marketing world is menu-based conjoint analysis. Menu-based conjoint analysis allows each respondent to package their own product or service.

In a survey, the respondent is shown a list of features with associated prices. The respondent then chooses what they want in their ideal product while keeping price as a factor in their decision. For the researcher, key information can be gained by analyzing what was selected and what was left out. If feature A for $100 was included in the menu question but feature B for $100 was not, it can be assumed that this respondent prefers feature A over feature B.

The outcome of menu-based conjoint analysis is that we can identify the trade-offs consumers are willing to make. We can discover trends indicating must-have features versus luxury features.

Add in the fact that menu-based conjoint analysis is a more engaging and interactive process for the survey taker, and one can see why menu-based conjoint analysis is becoming an increasingly popular way to evaluate the utility of features.