Conjoint Analysis

Also known as: Conjoint, CBC, ACBC, Choice Modeling, Conjoint Study

Statistical methodology evaluating consumer preferences for product attribute combinations, including price.

Conjoint Analysis is a quantitative research technique that simulates real purchase decisions to determine which combination of product attributes (price, size, flavor, design, brand, etc.) generates the greatest preference. It is the gold standard methodology for understanding the relative weight of each attribute in the purchase decision.

Main modalities: Choice-Based Conjoint (CBC) where the respondent chooses between complete product profiles, Adaptive Choice-Based Conjoint (ACBC) that adapts the alternatives shown based on prior responses, and MaxDiff for ranking elements without combinations.

Atlantia powers Conjoint with AI models that accelerate experimental design, optimize sample size, and generate real-time market simulations for pricing, portfolio, and product design decisions.