Trade-Offs Measured, Decisions Simulated
CFR Solutions designs and fields Conjoint Analysis studies that model how real trade-offs between price, features, and packaging drive choice, giving you part-worth utilities and a market simulator you can run scenarios on.
Every Attribute Weighted, Every Trade-Off Modeled
Attributes and levels are built from your product's real decision points, respondents work through balanced choice tasks, and the resulting part-worth utilities feed a market simulator that scores any combination you want to test.
Conjoint Designs Built Around Your Decision
Whether it's pricing, packaging, or a full feature bundle, we design the choice task around the trade-off you need to measure.
Choice-Based Conjoint (CBC)
Respondents pick between full product profiles, revealing how attributes trade off in a realistic buying scenario.
Learn more →Adaptive Conjoint (ACBC)
A dynamic task that narrows in on each respondent's real preference set for sharper, individual-level utilities.
Learn more →MaxDiff
Ranks features, claims, or priorities against each other to show what matters most, not just what's liked.
Learn more →Price Sensitivity Modeling
Reads the price-value curve for your product and flags the range where demand holds or drops.
Learn more →Feature Trade-Off Analysis
Quantifies exactly what a customer gives up or gains when one feature is swapped for another.
Learn more →Market Simulation
Turns your utilities into a live simulator so you can score new combinations without fielding again.
Learn more →Explore Our Other Essential Services
Every technique is built on the same rigorous, quota-clean data — pick the analysis that matches the question your study needs to answer.
Brand Mapping
Perceptual maps showing how brands sit relative to each other on key attributes.
Learn more →CHAID Analysis
Decision-tree segmentation that splits respondents by the strongest predictors.
Learn more →Cluster Analysis
Groups respondents into natural segments based on shared attitudes or behavior.
Learn more →Conjoint Analysis
Measures the trade-offs respondents make between product features and price.
Learn more →Correlation Analysis
Measures how strongly two or more variables move together.
Learn more →Discriminant Analysis
Classifies respondents into known groups using their strongest predictors.
Learn more →Factor Analysis
Reduces a long list of variables down to the underlying factors driving them.
Learn more →Multidimensional Scaling
Visual maps of how respondents perceive similarity between items or brands.
Learn more →Regression Analysis
Quantifies how much each predictor moves the outcome you care about.
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