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UPCOMING EVENTS:UX, Product & Market Research Afterwork23. Apr.@Packhaus WienDetailsInsights & Research Breakfast16. Mai@Packhaus WienDetailsVibecoding & Agentic Coding for App Development22. Mai@Packhaus WienDetails

Conjoint Analysis

A survey method that reveals how users make trade-offs between product attributes by presenting realistic product concepts with different feature and price combinations.

Definition: A survey method that reveals how users make trade-offs between product attributes by presenting realistic product concepts with different feature and price combinations.

Conjoint analysis answers questions that direct surveys cannot: how much more are customers willing to pay for a longer battery life versus a better camera? Which combination of features and price point maximizes appeal? Instead of asking respondents to evaluate attributes in isolation — where everything is rated as "important" — conjoint presents realistic product concepts with varying attribute levels and asks respondents to choose between them or rate them as a whole. This forces the kind of trade-off thinking that mirrors real purchase decisions.

The method works by decomposing overall preference into the contribution of each attribute. A well-designed conjoint study reveals the hidden utility value that users place on each feature level, including price. This makes it possible to simulate market scenarios: if we add this feature and raise the price by 20%, what happens to preference share? The most common variant, choice-based conjoint (CBC), presents sets of 2-4 product concepts and asks "which would you choose?" — closely mimicking real-world decision contexts.

Conjoint analysis requires specialized tooling (Sawtooth Software, Qualtrics, Conjointly) and larger than simpler methods — typically 200+ respondents for stable part-worth utilities. The experimental design (which attribute combinations to show) is statistically generated, not manually constructed. Despite the higher complexity and cost, conjoint remains the gold standard for product configuration and pricing decisions because it captures trade-off behavior rather than stated importance. For a broader discussion of structured decision methods, see Section 14.3 of UX Research: Building Blocks for Impact in the Age of AI by Marc Busch.

Conjoint Analysis - Definition | UX Research Glossary | Busch Labs