Using Conjoint Analysis to Drive Smarter Decision-Making in MedTech

Why Conjoint Analysis Matters in MedTech

New medical technologies must meet both clinical and financial expectations. Decision-makers, like hospital administrators, radiologists, or lab directors, assess products based on a variety of attributes, including performance, cost, workflow impact, and service agreements. Asking these stakeholders about feature importance in isolation often leads to inflated responses where everything appears valuable.

Conjoint analysis addresses this issue by requiring respondents to weigh different attributes against each other, mirroring real-world purchasing decisions. This approach reveals:



• Feature prioritization – Understanding which product attributes influence purchase decisions the most.
• Willingness to pay – Determining price sensitivity and acceptable pricing ranges.
• Competitive positioning – Assessing how a product’s value proposition compares to alternatives.
• Portfolio optimization – Identifying gaps in an existing product lineup and opportunities for differentiation.

How The MarkeTech Group Conducts Preference Simulation Modeling

While many survey platforms offer conjoint as a plug-and-play feature, designing a study that produces reliable and meaningful data requires expertise. A poorly structured conjoint study can lead to misleading results, causing companies to base pricing and product decisions on inaccurate assumptions.



Our team has decades of experience crafting conjoint studies for MedTech firms. Every model we design accounts for competitive realities, market expectations, and cognitive effort required from respondents.

Key Elements of a Strong Conjoint Design

Choice Tasks

Each respondent is presented with multiple sets of product options, selecting the one they prefer in each instance. The number of tasks directly impacts the reliability of the data. Smaller studies with fewer attributes may only require 6-8 tasks per respondent, while more complex studies typically involve 8–12. Our research indicates this range provides the best balance between data robustness and respondent engagement.

Number of Profiles per Task

The number of options shown per choice task influences the quality of the responses. Too few options limit comparative insights, while too many increase cognitive strain. Research suggests that 3 profiles per task are optimal, especially in MedTech, where decision-making involves technical and often unfamiliar product attributes. Our team generally recommends no more than three profiles per screen to maintain engagement.

Attributes and Levels

Attributes represent key product features, such as resolution in an imaging system or turnaround time in a diagnostic test. Levels define the possible variations within each attribute, such as "30-minute scan time" versus "15-minute scan time." A well-structured conjoint study should focus on no more than seven attributes, keeping the analysis targeted while still capturing meaningful differences.



Additionally, attributes must be independent of one another. If two attributes are highly correlated, like engine power and fuel efficiency in a car, responses may be skewed. Thoughtful model design avoids these issues, resulting in more reliable conclusions.

Timing Considerations

The time required to complete a conjoint study varies based on complexity. Respondents typically take longer on the first task as they familiarize themselves with the format. In MedTech studies, the first task often takes 35–45 seconds, with subsequent tasks averaging 15–25 seconds. European respondents tend to require more time than their U.S. counterparts, particularly in the early stages of the exercise. Understanding these timing patterns helps structure the study in a way that maintains respondent engagement while collecting high-quality data.

Introducing simPRO™: Elevate Your Conjoint Data Analysis

Conjoint analysis delivers rich data. However, without the right tools, its strategic potential can remain untapped. That’s why The MarkeTech Group offers simPRO™, an interactive, web-based preference simulation model designed to transform conjoint results into actionable business insights.

simPRO™ empowers teams to explore complex scenarios in real time, enabling stakeholders to:

• Evaluate pricing strategies with precision
  
• Conduct in-depth product configuration and mapping
  
• Assess branding and positioning impacts



By leveraging powerful Voice-of-Customer (VOC) feedback, simPRO™ enables you to test different market scenarios without the need to re-survey, simulating product battles to help predict a product's success in the market. It can be applied across different market segments in a virtually limitless number of "what-if" scenarios, providing fast and easy access to critical insights.

Applying Conjoint Insights to MedTech Strategy

Conjoint analysis provides MedTech companies with data that can shape multiple areas of business strategy:

• Product Development – Aligning R&D priorities with customer needs and market expectations.
• Pricing Strategy – Defining pricing tiers that balance profitability and adoption.
• Competitive Benchmarking – Identifying strengths and gaps relative to competitors.
• Market Segmentation – Understanding how different customer groups prioritize features.

Decisions informed by conjoint analysis lead to stronger market positioning and more confident investments. At The MarkeTech Group, we help clients translate conjoint data into strategic recommendations that drive commercial success.

Looking to leverage conjoint analysis for your next product decision? Submit an RFP today, and let’s discuss how our expertise can provide the insights you need.