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Quantitative UX Research Course

Conjoint Analysis and MaxDiff: Choice Modeling for Product Decisions

Course features
Next Cohort Dates
Mar 30 - May 4, 2026
Meeting Time
Mondays, 5-7pm ET US
Course Type
Live Online
Duration
6 weeks
Price
$595

Conjoint Analysis + MaxDiff Course Description

This course teaches UX professionals how to apply choice modeling methods such as Choice-Based Conjoint Analysis and MaxDiff to support product decisions around prioritization, bundling, pricing, and roadmap tradeoffs. You will learn how to move from a real product decision to a complete and defensible choice study, from scoping and study design through interpretation and stakeholder-ready recommendations.

Throughout the course, you will work in small groups of three to frame a critical product decision, determine the appropriate method, design and execute a choice study, and report results in a decision-focused format. This is a hands-on, DIY course focused on practical execution and on avoiding the common pitfalls that undermine choice modeling in product organizations.

Why Learn Conjoint and MaxDiff

UX teams are increasingly asked to support high-stakes product decisions such as what to build next, how to bundle capabilities, how to sequence roadmaps, and how to set pricing and packaging with confidence.

Choice modeling methods like MaxDiff and Conjoint are most valuable when teams need foresight without customer exposure, or when outcomes vary in ways conversion metrics alone cannot explain. These methods model how users make tradeoffs under controlled conditions, allowing teams to evaluate decisions before changes reach production.

When applied well, choice modeling can reduce reliance on costly experiments, reveal inflection points in willingness to pay, and inform packaging and prioritization earlier in the product lifecycle. This course focuses on applying choice modeling in these high-impact moments so you can make and defend concrete product decisions with confidence.

Course Format

This course is structured to reflect how choice modeling is used across the product development lifecycle.

You will work on one continuous product decision while completing two distinct choice modeling projects that build on one another. MaxDiff is used first to inform early prioritization and scope. Conjoint follows to support higher-fidelity decisions around tradeoffs, pricing, or value modeling.

Each small group applies these methods to a different real-world use case, allowing the cohort to learn across applications through shared discussion and comparison.

Week 1: Decision framing and method selection
Weeks 2–3: MaxDiff (design, deploy, and analyze)
Weeks 4–5: Conjoint (design, deploy, and analyze)
Week 6: Readout + roundtable feedback session

Throughout the course, sessions combine short lectures, hands-on workshops, and large group feedback using realistic constraints. Instruction is tool-agnostic, with optional technical depth for those who want to explore modeling further. 

By the end, you will have practical experience applying and sequencing MaxDiff and Conjoint to guide real product decisions.

Skills You'll Learn in the Course

By the end of this course, you will be able to design defensible choice studies, execute them independently, interpret results for real product decisions, and communicate findings with confidence to stakeholders.

Design defensible choice studies
  • Define the decision, select the appropriate method, and determine sampling
  • Draft clear, realistic survey instruments including attributes, levels, and choice tasks that reflect real tradeoffs
  • Anticipate design risks such as topic overlap, respondent comprehension, and bias to ensure results will hold up under scrutiny

Execute choice studies end to end
  • Field choice-based surveys and manage data collection using common research tools
  • Clean, structure, and prepare choice data for analysis
  • Apply advanced analysis and simulations to explore tradeoffs, pricing, and “what-if” scenarios to estimate preferences, importance, and outcomes reliably

Analyze, report, and tell the decision story
  • Evaluate model stability and uncertainty to understand result reliability
  • Translate model outputs into clear visualizations and decision-ready insights
  • Craft persuasive narratives that communicate implications, risks, and recommendations to stakeholders

How will this course help my career?

Lead tradeoff driven product decisions

You’ll be able to guide roadmap, packaging, and pricing decisions using quantified tradeoffs from MaxDiff and Conjoint, framing choices in terms of value, risk, and expected return so stakeholders can make informed investments.

Demonstrate applied choice modeling expertise

You’ll leave with hands-on experience designing, executing, and interpreting choice studies end to end, allowing you to speak concretely about how you’ve used MaxDiff and Conjoint to influence real product decisions.

Strengthen credibility across analytics and data science

You’ll be able to communicate choice model results with clarity and confidence, building trust and alignment across Product, Analytics, and Data Science teams to support informed product decisions.

Who is this choice modeling course for?

This course is best suited for UX professionals who support high-impact product decisions and want to use choice modeling to influence product direction before changes reach production.

This course is a strong fit if you are:
  • A mid–senior UX professional working in quantitative or mixed-methods contexts
  • Supporting decisions in feature prioritization, bundling, packaging, pricing, or roadmap planning
  • A research lead who needs to guide, review, or defend choice modeling work

Prerequisites

Comfort with basic survey research and data interpretation. No coding or advanced statistics experience is required.

Bianca Work

Meet your Instructor
Bianca Work (she/they) is a principal quantitative researcher who helps organizations align teams, improve product performance, and anticipate risk by translating customer experience into measurable, predictive insight. She has led large-scale experience measurement and decision programs at Indeed and Splunk, building in-product platforms that connect trust, satisfaction, and behavior to product and business outcomes. Her work, featured in TechTarget, enables teams to move from fragmented signals to decision-ready understanding, with a focus on complex and AI-native environments.

Learning Outcomes

By course completion, you will confidently:
  • Design defensible Conjoint Analysis and MaxDiff studies by selecting appropriate methods, defining sampling strategies, and crafting survey instruments that reflect realistic product tradeoffs.
  • Interpret MaxDiff and Conjoint outputs to identify meaningful patterns, assess model stability, and translate results into decision-relevant insights.
  • Apply scenario analysis and simulation techniques to explore "what-if" tradeoffs related to feature prioritization, pricing, packaging, and roadmap sequencing.
  • Communicate choice modeling findings through stakeholder-ready narratives and visualizations that frame implications, risks, and concrete product recommendations.
Overview

Conjoint Analysis + MaxDiff Course Syllabus

This course is structured to teach choice modeling as it is actually used in product organizations: as a decision-support tool applied under real constraints, not as a statistical or software exercise.

Students work in small groups of three throughout the course. Each group tackles one MaxDiff study and one Conjoint Analysis study tied to a shared Pilot Product Decision, but applies the methods to a distinct use case (for example: feature prioritization, messaging, pricing, packaging, or value modeling).

Instruction is tool-agnostic. Studies may be executed using common survey platforms, spreadsheets, or R. Optional advanced modeling resources are provided for students who want additional flexibility.

Week 1: Decision Framing and Study Sequencing

This session establishes a decision-first mindset and introduces how MaxDiff and Conjoint are intentionally sequenced across the product lifecycle. Students form groups of three and translate a real product decision into a structured research plan that defines what to test, when, and why.

In class:
  • Lecture: Decision framing, when choice modeling is appropriate, and how MaxDiff and Conjoint support different stages of the same decision
  • Introduction to Survey Monsters as a professional diagnostic framework for common design and interpretation risks
  • Workshop (Groups of Three): Create a MaxDiff & Conjoint research plan for your group’s specific use case.
  • Complete Choice Modeling Study Template & Method Sequencing Template
  • Review & Feedback: Round-robin large group discussion of study plans, focused on decision fit, sequencing logic, and risk anticipation


Students leave with:
  • A documented MaxDiff → Conjoint research plan
  • A clearly defined application focus for their group
  • A stable group of three to work with across the course

Week 2: MaxDiff Design & Programming

This session focuses on designing and programming MaxDiff studies that clarify what matters most before deeper tradeoff modeling begins. Each group applies MaxDiff to a different decision context, enabling cohort-wide comparison later.

In class:

  • Instruction: What MaxDiff is designed to answer, common design failure modes, and how to craft effective MaxDiff survey instruments
  • Workshop (Groups of Three): Draft MaxDiff items, prompts, and sampling aligned to the group’s application
  • Ensure items are distinct, realistic, and decision-relevant
  • Review & Feedback: Structured large group discussion of item lists and task designs


Students leave with:

  • A draft MaxDiff instrument tailored to their specific use case
  • A clear definition of what the study is meant to prioritize and what are the expected outcomes of the study


Week 3: MaxDiff Data Cleaning, Interpretation, & Visualization

This session centers on interpreting MaxDiff results responsibly and deciding what findings to communicate to stakeholders. Groups practice data cleaning, interpretation, and visualization, while comparing how interpretation varies by application.

In class:

  • Instruction: Reading importance patterns, identifying meaningful separation, and recognizing poor data quality
  • Workshop (Groups of Three): Review and visualize MaxDiff results
  • Review & Feedback: Cross-group discussion comparing how different use cases shaped interpretation and findings

Students leave with:

A validated MaxDiff study, including study design, programming, analysis, and interpretation

Week 4: Conjoint Analysis Design & Programming

This session centers on interpreting MaxDiff results responsibly and deciding what findings to communicate to stakeholders. Groups practice data cleaning, interpretation, and visualization, while comparing how interpretation varies by application.

In class:

  • Instruction: Reading importance patterns, identifying meaningful separation, and recognizing poor data quality
  • Workshop (Groups of Three): Review and visualize MaxDiff results
  • Review & Feedback: Cross-group discussion comparing how different use cases shaped interpretation and findings

Students leave with:

A validated MaxDiff study, including study design, programming, analysis, and interpretation

Week 5: Conjoint Analysis Data Cleaning, Interpretation, & Scenario Analysis

This session centers on interpreting Conjoint Analysis results responsibly and using them to explore decision-relevant scenarios. Groups practice data review, interpretation, and scenario analysis, while comparing how conclusions vary across applications.

In class:

  • Instruction: Reading utilities, preference shares, and scenario outputs
  • Identifying unstable estimates, overconfidence risks, and misinterpretation patterns
  • Workshop (Groups of Three): Review and analyze Conjoint outputs using platform or spreadsheet-based results
  • Explore “what-if” scenarios tied directly to the group’s product decision
  • Review & Feedback: Cross-group discussion comparing how different use cases shaped interpretation, scenarios, and recommendations

Students leave with:
  • A validated Conjoint study, including design, programming, analysis, and interpretation
  • Decision-relevant scenario outputs tied to their product decision

Week 6: Decision Readout & Cross-Application Roundtable

This final session focuses on synthesizing insights across MaxDiff and Conjoint and comparing how choice modeling performs across different product decision contexts. Groups present their work, then participate in a facilitated roundtable to share what they learned and learn from others.

In class:
Group Presentations (Groups of Three):
Each group presents their projects, showing:
  • The original product decision and application context
  • How MaxDiff was used to narrow scope and inform Conjoint design
  • How Conjoint scenarios were interpreted to guide the final decision

Facilitated Discussion with cross-team roundtable: Talk with your peers about how MaxDiff and Conjoint can be used across different use cases to learn about other applications of each method.

Synthesis Exercise: Identify shared patterns, decision heuristics, and warning signs that generalize beyond any single project

Students leave with:
  • A complete, decision-ready narrative demonstrating sequenced MaxDiff → Conjoint execution
  • A comparative understanding of how choice modeling applies across multiple product decision contexts
  • A clear framework for selecting, sequencing, and defending choice modeling approaches in real product environments

Frequently asked questions

What is conjoint analysis, and what will I learn in this conjoint analysis course?

Conjoint analysis is a choice-based method that measures how people make tradeoffs between product features, bundles, and price. In this conjoint analysis course, you’ll learn how to design a study (attributes/levels, experimental design), field it, analyze results, and translate the outputs into practical product decisions using simulations.

What is choice modeling (CBC), and how is it used in product decisions?

Choice modeling—often taught as Choice-Based Conjoint (CBC)—models real-world selections to estimate preference weights and predict how changes to features or price affect choice. You’ll learn how to use choice modeling outputs to compare concepts, optimize bundles, and run “what-if” scenarios that support roadmap and pricing decisions.

What is MaxDiff, and what will I learn in the MaxDiff portion of the course?

MaxDiff (best-worst scaling) is a method for prioritizing many items by asking respondents to pick the “most” and “least” important options from small sets. In the MaxDiff portion of the course, you’ll learn how to write items, set up a MaxDiff study, analyze results, and turn priority scores into clear recommendations.

When should I use MaxDiff vs. conjoint analysis?

Use MaxDiff when you need a clear ranking or relative importance across a long list of items (features, messages, benefits) and you’re not modeling bundles or price tradeoffs. Use conjoint analysis when you need to understand tradeoffs between multiple attributes, evaluate packages, or quantify how changes (including price) impact choice.

Is this course beginner-friendly?

Yes. The course is designed for practitioners who want to apply conjoint analysis and MaxDiff to real decisions without requiring advanced statistics. You’ll learn the key concepts, how to avoid common pitfalls, and how to interpret results confidently. (If you do have a stats background, you’ll still benefit from the practical design and decision-focused interpretation.)

Do I need to know how to code to take this course?

No coding is required. The course focuses on method design, interpretation, and practical decision-making. If you want to go deeper technically, you’ll also learn how to evaluate assumptions and data quality so you can collaborate effectively with analysts or data scientists.

What tools or software will I use during the course?

You’ll learn workflows that translate across common survey and analysis tools used for MaxDiff and conjoint/choice modeling. The course emphasizes designing strong studies and making defensible decisions from the outputs, regardless of which platform your team uses. You’ll also learn how to use Sawtooth Software during the course and can earn Sawtooth’s certifications in both Conjoint Analysis and MaxDiff through UXR Institute’s partnership with Sawtooth Software.

What will I be able to do after completing the course?

After completing the course, you’ll be able to:
  • Decide when to use MaxDiff vs. conjoint (choice modeling) for your research question
  • Design strong studies (attributes/levels, tasks, sample considerations)
  • Analyze outputs and validate data quality
  • Run simulations to compare scenarios and support product decisions
  • Communicate results clearly to stakeholders

What kinds of decisions does this course prepare me to support?

This course prepares you to support decisions like feature prioritization, bundling/packaging, concept selection, and pricing strategy—especially when you need evidence about tradeoffs, not just stated preferences.

Does this course cover pricing and willingness-to-pay?

Yes. You’ll learn how pricing can be incorporated into conjoint designs and how to interpret price-related outputs responsibly (including how to avoid over-claiming precision). You’ll also learn how to use simulations to compare options at different price points.

Does this course offer a certification?

Yes, the UXR Institute partners with Sawtooth Software to enable you to receive Sawtooth's certifications in both Conjoint Analysis and MaxDiff.

Is this course appropriate for UX researchers, product managers, and marketers?

Yes. It’s designed for anyone involved in making product decisions who needs rigorous evidence about tradeoffs—common roles include UX researchers, product managers, product marketers, insights teams, and growth or pricing stakeholders.
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