Many of the RFPs we receive from our clients include requests for “conjoint analysis.” Unfortunately, this term/methodology often is ill-defined or not appropriate to meet the objectives of the research request. As researchers, it is our responsibility to help our clients better understand what they need and the best tools to employ to meet those needs.

Conjoint analysis is a powerful tool and can be used to quantify a number of metrics, including product/feature value; trade-offs customers are willing to make; and, in some cases, price elasticity for a product, feature or brand. Clients and researchers have three core conjoint products to choose from:

  • Adaptive Conjoint Analysis (ACA)
    • The original replacement for traditional, card-sort conjoint analysis
  • Choice-Based Conjoint (CBC)
    • The most popular, widely-used conjoint methodology
  • Adaptive Choice-Based Conjoint (ACBC)
    • Combines elements of both ACA and CBC

Adaptive Choice-Based Conjoint ACBC

Adaptive Conjoint Analysis was released by Sawtooth in 1985. The ACA model was designed as a computer-based tool to replace traditional card sort conjoint. It enabled researchers to measure more attributes than they could with traditional conjoint methods, making ACA a popular option due to ease of use and more powerful analysis.

Next, Choice-Based Conjoint was released in the 1990s and quickly became the most popular conjoint analysis. This tool eliminated attribute ratings and rankings, instead showing full “product” profiles from which respondents must choose. This continues to be the most popular model for conjoint analysis today.

Adaptive Choice-Based Conjoint Analysis model is a newer methodology that was introduced around 2010 – although it never became as popular as CBC. ACBC “combines the best aspects of adaptive interviewing with the realism and accuracy of choice data” (Orme, Brian. Getting Started with Conjoint Analysis).

Conjoint Analysis Infographic Adaptive Choice-Based Conjoint ACBC

Still confused as to which methodology is best for you? Give us a call for a more detailed explanation of each. In addition, look for our upcoming post on ACBC for an in-depth explanation of this powerful tool.

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