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We design and run choice-based conjoint (CBC) studies end-to-end—from attribute and level design through survey programming, sampling, and fieldwork management.
Our analytics team estimates utilities and importance, runs scenario simulations (pricing, feature bundles, competitive sets), and supports segmentation to understand preference differences across audiences.
You receive decision-ready outputs—clear recommendations, supporting charts, and simulation results—so you can prioritize product configurations and pricing with confidence.
We work with you to define the product attributes and levels to test—features, prices, brands, or packages—keeping them realistic and manageable for respondents.
We build an efficient choice design, decide the number of choice tasks per respondent, and program the conjoint exercise into the survey.
We set sample sizes sufficient for stable estimates and segment-level reads, then manage fieldwork with quality checks on responses.
Our analytics team estimates utilities and attribute importance using industry-standard methods, including hierarchical Bayes where appropriate, and runs market simulations for pricing, feature bundles, and competitive scenarios.
You receive utilities and importance scores, preference shares, scenario simulations, and a clear recommendations deck. A simulator file or dashboard can also be provided.
Quantify trade-offs to understand what drives choice.
Measure price sensitivity and willingness-to-pay with rigor.
Run market simulations for feature bundles and positioning scenarios.
Segment preferences to support targeting and product strategy.
Let's get started — Book a 30-minute discovery call.
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Planning a product, pricing, or package decision? Our conjoint specialists can design the study and build simulations that help you choose the best option with confidence.