How To Perform Conjoint Analysis For Market Research

Conjoint Analysis

Conjoint analysis: a statistical technique used in market research to quantify how consumers value the individual attributes (and attribute levels) of a product or service by presenting respondents with combinations of attributes and analyzing their choices or ratings to infer the relative importance and part-worth utilities of each attribute.

Why Should You Use Conjoint Analysis?

Why use conjoint analysis?

Conjoint analysis reveals real-world preferences and trade-offs, turning subjective feedback into actionable, quantifiable insights you can use to design, price, and position products that sell.

Key benefits

• Quantifies trade-offs: Measures the relative importance of attributes and the part-worth utilities for each level.


• Predicts choice and market share: Simulates purchase decisions and forecasts market share for new concepts and configurations.


• Estimates willingness to pay: Derives marginal value and price sensitivity for features to inform pricing and bundling.


• Prioritizes features effectively: Ranks features by impact on preference to guide product roadmaps and MVP decisions.


• Optimizes product and packaging: Tests combinations to find the most attractive feature set for target segments.


• Improves segmentation: Identifies distinct preference segments for tailored offers and targeted messaging.


• Reduces bias vs. direct rating: Forces trade-off decisions that mirror real purchase behavior, minimizing hypothetical bias.


• Supports competitive benchmarking: Compares your offerings to competitor profiles to find differentiation opportunities.


• Enables revenue-focused decisions: Links utility scores to share and revenue simulations for ROI-driven planning.

When to use it

• Designing new products or variants


• Setting or testing pricing strategies


• Choosing feature sets, bundles, or configurations


• Segmenting customers by preference


• Validating positioning against competitors

Use conjoint analysis whenever you need rigorous, choice-driven evidence on what customers will actually buy.

Conjoint Analysis: 7-Step Workflow from Objective to Implementation

1. Define the objective — Specify the key decision the conjoint study must inform (e.g., pricing, feature prioritization, market segmentation).


2. List product attributes and levels — Select realistic, independent attributes and levels that reflect actual customer choices.


3. Create your survey or choice sets — Design balanced, randomized choice sets or rating tasks that minimize fatigue and reveal trade-offs.


4. Collect data — Recruit a representative sample and monitor quality with attention checks and completion-time thresholds.


5. Analyze the results — Estimate part-worth utilities and importance scores using appropriate models (e.g., HB, MNL) and validate model fit.


6. Derive actionable insights — Translate utilities into recommendations such as optimal feature bundles, price points, and target segments.


7. Apply the results — Implement changes in product, pricing, or marketing, and run A/B tests or pilot launches to measure real-world impact.