Adaptive Conjoint Analysis: What It Is & When To Use It

Adaptive conjoint analysis is a special type of conjoint analysis used to gauge consumer preferences for different product features (similar to standard conjoint).

However, the key difference lies in the “adaptive” nature of the survey. Each survey is customized to the individual respondent — meaning every user receives a unique set of questions, typically administered through a computer.

As the respondent answers, the questionnaire adapts in real time based on their previous responses. This allows the survey to dig deeper into specific preferences, helping researchers gather more detailed feedback tailored to the individual.

This approach is especially useful when the product in question has many different features or applications. Adaptive conjoint surveys can focus in on the features that matter most to the respondent, offering insights into what they value and why.

While incredibly powerful, adaptive conjoint can be complex to implement. That’s why we created this blog: to walk you through what a typical adaptive conjoint project looks like and what goes on behind the scenes.

What Exactly Is Adaptive Conjoint Analysis?

Adaptive conjoint analysis helps researchers determine which product features respondents find most appealing.

Unlike traditional conjoint studies, each survey adapts to the respondent’s input. Questions are tailored in real time, making the experience highly personalized.

A typical project might include a product list with different profiles, each containing features like:

• Price
• Color
• Size
• Brand

Respondents select their preferred options. As they do, the survey drills deeper into specific attributes — for instance, asking more questions about certain colors or sizes — to uncover exactly what they liked most and why.

The level of detail and number of features included is usually decided by the research team. It’s all about balancing what’s valuable to analyze with what respondents are willing to answer — which is why it’s so important to work with experts who know how to manage this balance effectively.

How is it different from traditional conjoint?

If you’re considering a conjoint study, it’s helpful to understand how adaptive conjoint stacks up against other common approaches. Here’s a quick comparison:

Recommended Reading: MaxDiff vs. Conjoint Analysis – Uses and Examples

Benefits of Adaptive Conjoint Analysis

There are several benefits of using adaptive conjoint analysis compared to more traditional approaches — especially when dealing with complex or highly customizable products:

• Personalization increases data accuracy
  Each respondent receives a survey experience tailored to them, which improves engagement and leads to more thoughtful, reliable responses.
• Greater depth of insights per respondent
  Rather than collecting shallow data across many combinations, adaptive conjoint allows for deeper exploration of the features that matter most to each individual.
• Ideal for complex products with many features
  If your product has a long list of attributes (think configurations, components, bundles, etc.), adaptive design helps avoid overwhelming respondents while still collecting meaningful data.
• Efficient in narrowing down top-performing attributes
  By focusing only on what’s relevant to each respondent, the method helps researchers zero in on the most influential features without wasting survey time on irrelevant ones.

These advantages make adaptive conjoint analysis a great fit for brands looking to inform product development, pricing strategies, and go-to-market decisions.

When Would You Use Adaptive Conjoint?

Adaptive conjoint shines in projects that need deeper insights, especially around products or services.

It’s particularly helpful for:

• Product testing
• Concept testing
• Market segmentation

These are the most common use cases we’ve seen with our clients, but the method isn’t limited to them.

You might choose adaptive conjoint when:

• You have many product attributes to test
• You want to explore context-based or “what if” scenarios
• You need to tailor the survey to get the most relevant feedback

For example, it can test how respondents might react to a product if a specific feature were changed or if two features were combined differently.

It’s also valuable for pricing research and marketing strategy projects.

Both rely heavily on product features and can benefit from the customized feedback adaptive conjoint provides.

After data collection, researchers can analyze the results in multiple ways. At Drive Research, we often use custom reporting, but most studies involve reviewing results across all respondents to identify common preferences or predict purchase behavior.

The Main Types of Adaptive Conjoint Analysis

Adaptive conjoint surveys adjust based on respondent input in different ways. Here are the main types used in practice:

Adaptive Choice-Based Conjoint

This type involves multiple stages:

1. Respondents are first shown a list of product features and feature levels.
2. They select their preferred level for each feature.
3. Next, they review product configurations and indicate which ones they would consider.
4. Based on those answers, the survey generates personalized choice tasks.

These tasks repeat several times, with changing combinations of features. The result is rich data on which configurations are most appealing.

Recommended Reading: Explaining Choice-Based Conjoint Analysis

Adaptive Self-Explicated Conjoint

This type focuses on importance ratings.

Respondents first rate how important each feature and feature level is to them. These ratings help identify which features matter most.

Based on the responses, the survey presents follow-up questions tailored to the individual — all aligned with the project’s goals and the respondent’s stated preferences.

Adaptive Menu-Based Choice

In this format, respondents build their ideal product or service using a menu of options.

It’s ideal for products that are sold in a customizable format, like subscription plans or bundled services.

As users make selections, the survey continues to adapt — showing more relevant configurations based on their previous choices. This format is more complex but extremely powerful when used in the right setting.

Real-World Example of Adaptive Conjoint Analysis

Let’s say a consumer electronics company is preparing to launch a new line of smartwatches. The product team is exploring several combinations of features, including screen size, battery life, health tracking capabilities, price points, and strap material. With so many variables, it’s difficult to know which feature sets will drive preference in different customer segments.

To dig into this, the company partners with a market research firm to run an adaptive conjoint analysis. Each respondent sees a survey tailored to their individual responses — if one respondent indicates strong interest in fitness tracking, the survey adjusts to explore preferences for heart rate monitoring, GPS, and workout detection in more detail. Another respondent who focuses more on style might see follow-up questions about band types and colors.

By the end of the study, the brand has a clear sense of which features resonate most with different buyer personas. The results help them prioritize design decisions, set pricing tiers, and align marketing messages with what matters most to customers.

Contact Our Market Research Firm

Looking to run an adaptive conjoint analysis? As a full-service market research company, we specialize in advanced methodologies that uncover exactly what your customers want. Contact Drive Research to learn how we can design a custom conjoint study to support your product development, pricing, or marketing strategy.