Conjoint Analysis

A statistical methodology that evaluates consumer preferences for product attribute combinations.

Conjoint Analysis is a quantitative research technique that simulates purchase decisions to determine which combination of product attributes (price, size, flavor, design, etc.) generates the highest preference. The most common types are Choice-Based Conjoint (CBC), Adaptive Conjoint, and MaxDiff.

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