When should I use conjoint vs MaxDiff?

When companies need to understand what customers value, which product features matter most, or how people make trade-off decisions, traditional survey questions are not always enough. Two quantitative market research methods that can provide deeper insight are conjoint analysis and MaxDiff analysis.

But when should you use conjoint vs. MaxDiff?

The answer depends on the business decision you are trying to make.

MaxDiff is generally designed to prioritize individual items, such as features, benefits, messages, or attributes. Conjoint analysis is designed to evaluate trade-offs among multiple attributes and attribute levels within a product, service, or offer.

Choosing the right methodology can make a significant difference in the usefulness of your research. A well-designed study can help organizations make more informed decisions about product development, pricing, positioning, messaging, customer experience, and portfolio strategy.

Veridata Insights provides quantitative market research services that include both Conjoint Analysis and MaxDiff, along with survey design, programming, data collection, recruitment, analytics, reporting, and visualization.

Table of Contents

1. What Is MaxDiff Analysis?
2. What Is Conjoint Analysis?
3. What Is the Difference Between Conjoint and MaxDiff?
4. When Should You Use MaxDiff?
5. When Should You Use Conjoint Analysis?
6. Conjoint vs. MaxDiff Comparison Table
7. Can You Use Conjoint and MaxDiff Together?
8. Examples of MaxDiff and Conjoint Research
9. How Veridata Insights Can Help
10. How to Choose Between Conjoint and MaxDiff
11. FAQs About Conjoint vs. MaxDiff
12. Conclusion

What Is MaxDiff Analysis?

MaxDiff, short for Maximum Difference Scaling and also known as Best-Worst Scaling, is a quantitative research methodology used to understand the relative preference for a list of individual items.

In a typical MaxDiff exercise, respondents see a group of items and select:

• The item they consider most important or most appealing
• The item they consider least important or least appealing

Different combinations of items are shown across multiple questions. Statistical analysis can then be used to estimate the relative preference for the items being evaluated.

For example, a software company might want to understand which benefits matter most to potential customers.

A MaxDiff study could evaluate:

• Ease of use
• Security
• Price
• Customer support
• Integrations
• Reporting
• Customization
• Mobile access
• Implementation services
• Automation

Rather than asking respondents to rate every feature independently, MaxDiff forces choices between alternatives.

This can help distinguish the features respondents genuinely prioritize from features that receive similarly high ratings because respondents tend to say that everything is important.

For an additional explanation of how MaxDiff works, see SurveyMonkey’s MaxDiff analysis overview.

What Does MaxDiff Tell You?

MaxDiff is particularly useful for producing a prioritized hierarchy of individual items.

It can help answer questions such as:

• Which product features matter most?
• Which benefits should we emphasize in our advertising?
• Which claims should be included in our messaging?
• Which customer needs deserve the greatest attention?
• Which features should we prioritize for product development?
• Which attributes matter least to our target audience?

MaxDiff is therefore particularly useful when the central research question is:

“Which items matter most and which matter least?”

What Is Conjoint Analysis?

Conjoint analysis is a quantitative market research methodology used to understand how people evaluate products, services, or offers made up of multiple attributes.

Instead of evaluating individual features in isolation, respondents typically evaluate different combinations of attributes and attribute levels.

For example, imagine a company is developing a new subscription service.

The product could vary by:

A conjoint study could present respondents with different combinations and ask them to select the option they would be most likely to choose.

By analyzing these choices, researchers can estimate the relative value associated with different attributes and levels.

Conjoint can therefore help answer questions such as:

• How does price affect product choice?
• Which combination of features is most attractive?
• How much value does a premium feature provide?
• Which product configuration is most appealing?
• What trade-offs do customers make between price and features?
• How might changes to an offering affect preference?
• Which combination of attributes could be most competitive?

The key research question becomes:

“How do customers balance different attributes when choosing among complete alternatives?”

What Is the Difference Between Conjoint and MaxDiff?

Although both methodologies involve trade-offs, they are designed to answer different types of questions.

MaxDiff focuses primarily on prioritizing individual items.

Conjoint focuses primarily on understanding trade-offs among multiple attributes and their levels.

For example, suppose a company wants to evaluate ten potential product features.

If the company wants to know which features customers value most, MaxDiff may be appropriate.

If the company wants to understand how customers trade off price, brand, features, service, and other characteristics when selecting a complete product, conjoint may be more appropriate.

SurveyMonkey’s comparison of MaxDiff and conjoint analysis similarly describes MaxDiff as a way to identify relative preference among individual items, while conjoint evaluates combinations of product attributes and features.

Recent methodology guidance from Conjointly’s comparison of conjoint analysis and MaxDiff also emphasizes that the two methods answer different research questions and should not be treated as interchangeable.

A Simple Way to Think About It

Use MaxDiff to answer:

Which features, benefits, messages, or attributes are most important?

Use conjoint to answer:

How do customers balance different attributes when choosing between complete product or service options?

This distinction is important because the methodologies produce different types of insights.

Conjoint vs. MaxDiff Comparison Table

The choice should ultimately be driven by the business decision, not simply by which methodology appears more sophisticated.

When Should You Use MaxDiff?

MaxDiff is often a strong choice when your research objective is to prioritize a list of items.

1. You Need to Prioritize Product Features

Suppose your product team has identified 15 possible features but has the resources to develop only five.

A conventional rating question might result in many features receiving high scores.

MaxDiff forces respondents to make choices among competing features, helping researchers identify relative priorities.

2. You Need to Prioritize Marketing Messages

Marketing teams may have multiple potential claims, messages, or value propositions.

For example:

• Saves time
• Reduces costs
• Easy to use
• More secure
• Better customer support
• Greater flexibility
• Faster implementation

MaxDiff can help determine which messages deserve greater emphasis.

3. You Have a Long List of Items to Evaluate

MaxDiff can be useful when the research team needs to evaluate numerous individual items without asking respondents to rate every item independently.

This makes it useful for:

• Feature prioritization
• Benefit prioritization
• Message testing
• Needs prioritization
• Product attribute prioritization
• Brand attribute evaluation
• Customer experience drivers

4. You Want Clear Relative Priorities

If the executive question is simply, “What matters most?” MaxDiff may provide a more direct answer than a complex conjoint exercise.

5. You Want a Straightforward Choice Task

MaxDiff asks respondents to identify a best and worst option from a presented set. This can make the task relatively straightforward for participants.

The resulting data can then be modeled to produce preference scores and rankings.

When Should You Use Conjoint Analysis?

Conjoint analysis is generally more appropriate when customers are choosing between complete alternatives that contain multiple attributes.

1. You Are Designing a New Product

If your organization is deciding which combination of features should go into a new product, conjoint can help evaluate how customers respond to different configurations.

For example, an electronics company might evaluate:

• Brand
• Price
• Storage
• Battery life
• Screen size
• Camera capabilities
• Warranty

The goal is not simply to rank the features. The goal is to understand how the attributes work together when customers make a choice.

2. You Need to Understand Pricing Trade-Offs

Pricing is one of the important applications of conjoint research.

A company may want to understand whether customers would prefer:

• A lower-priced product with fewer features
• A mid-priced product with additional features
• A premium product with a broader feature set

Conjoint can help quantify the trade-offs respondents make among price and other attributes.

3. You Are Optimizing a Product or Service Package

Conjoint can be particularly valuable when an organization has multiple decisions to make simultaneously.

For example, a SaaS company could evaluate:

• Subscription price
• Number of users
• Storage
• Support level
• Security features
• Integrations
• Contract length

Rather than asking customers to evaluate each feature independently, conjoint can examine preferences for combinations.

4. You Want to Model Alternative Offerings

If your business wants to compare different configurations of a product or service, conjoint may provide the structure needed to model those alternatives.

Potential applications include:

• New product development
• Product line optimization
• Pricing strategy
• Package design
• Subscription plans
• Service tiers
• Feature bundles
• Competitive positioning
• Portfolio decisions

5. You Need to Understand Attribute-Level Preferences

A major distinction between MaxDiff and conjoint is that conjoint can examine different levels within attributes.

For example:

Price

• $25
• $35
• $45

Support

• Email
• Phone
• Dedicated representative

Contract

• Monthly
• Annual

This makes conjoint useful when the business decision involves more than determining which attributes matter. It involves determining which versions of those attributes customers prefer and how they trade them off against one another.

Can You Use Conjoint and MaxDiff Together?

Yes.

In some research programs, using both methodologies can make sense because they answer complementary questions.

For example, a company could begin with MaxDiff to prioritize a long list of potential features.

Suppose a product team starts with 20 possible features.

A MaxDiff study might identify the six features that customers consider most important.

The research team could then use those priority features in a conjoint study to evaluate how customers trade off:

• Features
• Price
• Service
• Brand
• Other relevant attributes

This creates a potential two-stage research framework:

Stage 1: MaxDiff

Goal: Determine what matters most.

Stage 2: Conjoint

Goal: Determine how those important attributes interact in a purchase decision.

This approach is not appropriate for every research project, but it can be useful when an organization begins with a broad list of potential attributes and then needs to optimize a more focused product or service configuration.

Examples of MaxDiff and Conjoint Research

The best methodology depends on the decision your organization needs to make.

Example 1: Software Product Features

Business question: Which features should we prioritize?

Recommended approach: MaxDiff

A software company has 15 potential product enhancements and needs to determine which ones customers value most.

MaxDiff can help create a prioritized list.

Example 2: New Subscription Package

Business question: Which combination of price, features, and support is most attractive?

Recommended approach: Conjoint

The company wants to understand how customers trade off different subscription configurations.

Conjoint can evaluate those combinations.

Example 3: Advertising Messages

Business question: Which messages should we emphasize?

Recommended approach: MaxDiff

The company has multiple claims and benefits and needs to identify which resonate most strongly.

Example 4: New Product Pricing

Business question: How do customers trade off price and product features?

Recommended approach: Conjoint

The organization needs to understand how changes in price and feature levels influence choice.

Example 5: Product Portfolio

Business question: Which product configurations should we offer?

Recommended approach: Conjoint, potentially supported by MaxDiff

MaxDiff can help prioritize relevant features, while conjoint can help evaluate how those features work together in complete offerings.

Common Business Applications

These are starting points, not rigid rules. The appropriate methodology depends on the research objective, target audience, attributes, study design, sample requirements, and decisions that will be made from the findings.

How Veridata Insights Can Help

Choosing between conjoint and MaxDiff is only one part of a successful quantitative research project.

The quality of the final insight also depends on:

• Clearly defined research objectives
• Appropriate methodology
• Well-designed questionnaires
• Effective survey programming
• High-quality respondent recruitment
• Data quality controls
• Appropriate statistical analysis
• Clear reporting
• Actionable visualization

Veridata Insights provides quantitative market research services that include both Conjoint Analysis and MaxDiff.

Its current quantitative research capabilities include advanced methodologies such as Conjoint Analysis, MaxDiff, segmentation, pricing studies, statistical analysis, simulators, and other analytical approaches. Veridata Insights also supports survey design and programming, respondent recruitment, data collection, real-time monitoring, custom reporting, and data visualization.

The company supports B2B, consumer, healthcare, and specialized audiences, with quantitative research capabilities extending across more than 120 countries.

This makes Veridata Insights a flexible option for organizations that need a research partner capable of supporting both individual research components and broader quantitative market research programs.

Veridata Insights Quantitative Research Capabilities

Organizations can work with Veridata Insights for:

• Conjoint Analysis
• MaxDiff Analysis
• Pricing Research
• Market Segmentation
• Product Concept Testing
• Brand Tracking
• Customer Satisfaction Research
• Competitive Intelligence
• Market Sizing
• Usage and Attitude Studies
• Online Surveys
• Data Processing
• Advanced Analytics
• Reporting and Data Visualization

Veridata Insights also provides multi-source recruitment and supports specialized B2B, healthcare, consumer, and hard-to-reach audiences.

Why Choose Veridata Insights for Conjoint or MaxDiff Research?

Selecting a research partner is about more than choosing a survey platform.

For advanced quantitative research, organizations need a partner that understands the methodology, audience, questionnaire, programming requirements, data quality, and business decision behind the study.

Veridata Insights offers:

Methodology Support

The team can help organizations determine whether Conjoint, MaxDiff, or another quantitative approach is appropriate for the research objective.

Advanced Survey Programming

Veridata Insights supports complex research programming, including Conjoint, Discrete Choice, MaxDiff, and segmentation algorithms.

Diverse Audience Recruitment

Research can be conducted among consumer, B2B, healthcare, and hard-to-reach audiences.

Quality-Focused Data Collection

Veridata Insights uses multiple recruitment sources and quality controls designed to support reliable data collection.

Analytics and Visualization

Research findings can be transformed into reports, dashboards, charts, tables, and other deliverables designed to make the results easier to understand and apply.

Flexible Research Support

Organizations can use Veridata Insights for one component of a research project or for a full-service research program covering consultation, methodology, programming, data collection, processing, analytics, and reporting.

How to Choose Between Conjoint and MaxDiff

Before selecting a methodology, ask these five questions:

1. What decision are we trying to make?

Start with the business decision, not the research technique.

2. Are we prioritizing individual items?

If yes, MaxDiff may be appropriate.

3. Are we evaluating combinations of attributes?

If yes, conjoint may be more appropriate.

4. Do we need to understand different levels within attributes?

If yes, conjoint is often the stronger candidate.

5. Do we need both prioritization and trade-off insights?

If yes, a research design that incorporates both methods may be worth considering.

The most important principle is simple:

Choose the methodology that best answers the business question.

FAQs About Conjoint vs. MaxDiff

Is MaxDiff the same as conjoint analysis?

No. Both are quantitative preference research techniques, but they serve different purposes. MaxDiff generally prioritizes individual items, while conjoint evaluates trade-offs among multiple attributes and attribute levels.

Which is better, conjoint or MaxDiff?

Neither methodology is universally better. The appropriate choice depends on the research objective. MaxDiff is often useful for prioritizing individual items, while conjoint is often better suited to evaluating complete product or service configurations.

When should I use MaxDiff?

Use MaxDiff when you need to understand the relative importance or preference for a list of individual features, benefits, messages, claims, or other items.

When should I use conjoint analysis?

Use conjoint when you need to understand how customers make trade-offs among multiple product or service attributes, particularly when those attributes have different levels such as price points, feature options, service levels, or contract terms.

Can MaxDiff be used for product development?

Yes. MaxDiff can help product teams prioritize potential features or improvements. However, if the decision involves determining how multiple features and price points should be combined into a complete product offering, conjoint may provide more relevant information.

Can conjoint analysis be used for pricing research?

Yes. Pricing can be included as an attribute in many conjoint designs, allowing researchers to evaluate how respondents trade price against other product or service attributes.

Can a company use MaxDiff and conjoint in the same research program?

Yes. In some cases, MaxDiff can be used to prioritize a larger list of potential attributes, followed by conjoint to evaluate trade-offs among the most relevant attributes.

Is conjoint analysis more complex than MaxDiff?

Generally, conjoint studies require more extensive design considerations because respondents evaluate combinations of multiple attributes and levels. The appropriate design depends on the research objectives, number of attributes, levels, target audience, sample, and analytical requirements.

Who can conduct conjoint and MaxDiff research?

Organizations can conduct these studies internally or work with a market research partner that has expertise in research design, survey programming, respondent recruitment, statistical analysis, and reporting.

Veridata Insights provides both Conjoint Analysis and MaxDiff as part of its quantitative market research capabilities.

Conclusion

The question is not simply whether you should use conjoint or MaxDiff. The more important question is what decision does your organization need the research to support?

Choose MaxDiff when you need to prioritize individual features, benefits, messages, or other items.

Choose conjoint analysis when you need to understand how customers trade off multiple attributes and attribute levels within complete product or service alternatives.

And when your research requires both prioritization and optimization, a combined approach may be worth considering.

The right methodology can turn customer preferences into actionable information that supports product development, pricing, messaging, positioning, and strategic decision-making.

Veridata Insights can help your organization determine the right research approach and execute the study from design through reporting.

Whether you need MaxDiff, Conjoint Analysis, another quantitative methodology, or a full-service market research program, Veridata Insights provides flexible research support designed around your objectives.

Ready to determine which methodology is right for your next research project? Contact Veridata Insights to discuss your research objectives and explore a customized market research solution.