Adaptive Conjoint Analysis (ACA), launched in 1985, can be considered the driver of the market acceptance of conjoint analysis. It is a pairwise, ratings-based conjoint approach that adapts the concepts shown to the research participants based on previous answers. It tries to maximize the information gathered from each choice by formulating the concepts such that they are equal in preference. However, not all attributes/features are shown at the same time.
What are the advantages and disadvantages of Adaptive Conjoint analysis?
There are a few advantages that you can benefit from when doing an Adaptive Conjoint analysis:
- It allows for the use of more attributes thanks to the use of partial profiles
- The data collection is more convenient due to its staged approach
- ACA computes respondent-level utilities on the fly, enabling collection of additional diagnostics during interviews
And some disadvantages to keep in mind:
- It is less realistic for not all attributes/features are shown at the same time (research participants may not be able to assume attributes not shown are held “constant”)
- Often not good at pricing research (tends to understate the importance of price)
- Must be computer-administered (PC or Web)
- Interactions cannot be calculated (it assumes equal price elasticities for all brands / respondent)
When do I use Adaptive Conjoint analysis?
- To forecast the likely acceptance of a new to the world product
- To measure the attractiveness of specific product features
- To model high involvement purchases
- To (re)design a (new) product
Adaptive Choice-based Conjoint: The derivative of Adaptive Conjoint analysis
Adaptive Choice-based Conjoint (ACBC) is the latest approach to preference modeling that leverages the best aspects of CBC (Choice-Based Conjoint) and ACA (Adaptive Conjoint Analysis). Different from traditional CBC, the interview process of ACBC is staged. First the research participant builds its optimal product configuration; then must-haves and unacceptables are assessed; thirdly tradeoffs are explored by systematically varying remaining product configurations.
What are the advantages and disadvantages of Adaptive Choice-Based Conjoint analysis?
There are a few advantages that you can benefit from when doing a Adaptive Choice-Based Conjoint analysis:
- It is able to process more attributes than CBC
- The interview is more pleasant to the research participant, compared to CBC
- It is less subject to assumptions about the use of a compensatory decision rule
However, ACBC is more complicated to execute than standard CBC.
When do I use Adaptive Choice-Based Conjoint analysis?
- For (durable) consumer products: to define the optimal product
- For financial service providers: to optimize product/portfolio configurations
- In telecom industries: to optimize your products or product bundles