UX Research at Scale: Surveys, Analytics, Online Testing

U-M Free Access Enrollment Options

What You'll Learn

Understand survey methodology from the UX perspective
Learn techniques to gaining UX insights from large numbers of users, including web analytics, A/B testing, and remote unmoderated studies

8 Modules

16 Hours

2 hrs per module (approx.)

Rating

About UX Research at Scale: Surveys, Analytics, Online Testing

This UX course will provide an overview of survey methodology from the perspective of UX research. UX surveys typically focus on uncovering user needs, connecting needs to user characteristics, and gaining insight into user attitudes towards systems they use. In this course, learners will learn the basics of UX survey research and conduct a survey of their own design!

Learners will be introduced to techniques for gaining UX insights from large numbers of users, including web analytics, A/B testing, and remote unmoderated studies. We will discuss how these techniques work, when they can be applied, and what can be learned by using them.

What You’ll Learn:
-Learn how web analytics works and how to analyze analytics data
-Understand how to develop A-B tests, before/after, and multivariate experiments
-Learn how to set up and analyze remote unmoderated testing studies
-Analyze and report on large scale user experience studies Learn about the different types and uses of surveys in UX research
-Understand the survey population: when to sample, when to recruit
-Develop a survey instrument that meets your requirements
-Analyze and report on surveys
-Learn to critique user surveys

Skills You'll Gain

What You'll Earn

Certificate of Completion: Certificates of completion acknowledge knowledge acquired upon completion of a non-credit course or program.

Experience Type: 100% Online
Format: Self-Paced
Series: User Experience Research and Design
Subject: Information Technology
Platform: Coursera

Welcome Message

Welcome to UX Research at Scale: Surveys, Analytics, Online Testing, a course focused on quantitative and mixed-method UX research techniques used across the product lifecycle. Learners explore survey design, sampling, analytics, remote usability testing, and preference testing to support evidence-based design decisions at scale.
This abbreviated syllabus description was created with the help of AI tools and reviewed by staff. The full syllabus is available to those who enroll in the course.

Course Schedule

Module 1 – When and How to Use Surveys

Reading: Welcome Announcement
Reading: Course Syllabus
Reading: Help Us Learn More about You!
Video: Course Introduction
Video: The Basics of UX Research
Video: Ethics and UX Research
Video: Survey Terms
Video: Understanding Error
Video: Four Sources of Error
Discussion Prompt: Optional Discussion: Participate in a Survey
Graded: Quiz: Survey Time

Module 2: Asking the Right People (Coverage Error)

Video: Defining Your Population
Video: Probability vs Non-Probability
Video: Non-Probability Samples
Video: Non-Probability Samples: Panels
Video: Survey Modes
Graded: Quiz: Assessing Your Survey Knowledge

Module 3: Getting Answers (Nonresponse error)

Video: Nonresponse: The Respondent Mindset
Video: Nonresponse: Increasing Benefits
Video: Nonresponse: Reducing Cost
Video: Nonresponse: Establishing Trust
Graded: Quiz: Getting Responses

Module 4: Writing Questions (Measurement Error)

Video: Questions: The Respondent State of Mind
Video: Defining Your Concept
Video: Anatomy of a Survey Question
Video: Basic Guidelines for Writing Questions
Video: Open-Ended Questions
Video: Closed-Ended Questions
Video: Designing Nominal Questions
Video: Designing Ordinal Questions
Video: Common UX Survey Questions
Discussion Prompt: Discussion: Uncommon Survey Questions
Video: Visual Design of Survey Questions
Reading: Writing Survey Questions - Best Practices
Video: Ethics of Survey Research
Discussion Prompt: Discussion: Surveys and Your Work!
Graded: Writing Questions Quiz 1
Graded: Writing Questions Quiz 2
Graded: Peer Assessment: Writing Survey Questions

Module 5: About Research at Scale

Reading: Introduction to About Research at Scale
Video: What is UX Research at Scale?
Reading: How Giant Websites Design for You (and a billion others, too)
Video: A Maturity Model
Reading: UX Maturity Models, A Collection
Video: Findings versus Reports
Video: Interview: How Do People Practice UX Research at Scale Now?
Graded: Quiz: About Research at Scale

Module 6: Behavioral Analytics

Reading: Introduction to Behavioral Analytics
Video: Website Analytics for UX
Video: All About Metrics
Video: Research Questions and Website Analytics
Video: Search Analytics
Video: Let's Talk: The Practice of User Research
Reading: Analytics Dataset: Peer Assignment Setup
Reading: Metrics Glossary
Reading: Suggestions for Further Exploration
Graded: Analytics Dataset

Module 7: Remote Testing

Reading: Introduction to Remote Testing
Video: Remote Testing
Video: Remote Moderated Testing
Video: Remote Unmoderated Testing
Reading: Download Data
Video: Example Remote Unmoderated Test
Reading: Example Remote Test Script
Reading: Informed Consent Form
Reading: Analyzing Moderated Tests
Discussion Prompt: Discussion: Remote Testing
Reading: Suggestions for Further Exploration
Graded: Remote Testing

Module 8: A/B Testing and Preference Testing

Video: About A/B Testing
Video: A/B Testing vs Preference Testing
Video: Conducting Preference Testing
Video: Conducting an A/B Study
Video: Between vs. Within Subjects
Video: Ethics of A/B Testing
Reading: Preference Test: Peer Review Assignment Setup Part 1
Discussion Prompt: Preference Test Discussion
Reading: Preference Test: Peer Assignment Setup Part 2
Reading: Preference Test: Example Survey Questions
Reading: Final Thoughts
Reading: Suggestions for Further Exploration
Reading: Course Feedback
Reading: Keep Learning with Michigan Online
Graded: Preference Test: Assignment

Grading Policy

Learners must earn an overall grade of 80%. There are seven quizzes and three peer-graded assignments in the course.

Lija Hogan

Director of Enterprise Research Strategy, UserTesting

Clifford Lampe

Associate Professor, School of Information

Course content developed by U-M faculty and managed by the university. Faculty titles and affiliations are updated periodically.

Beginner Level

No prior experience required

Individuals

This experience is available to individual learners on the following platforms:

U-M Community

Free access is only available to current U-M students, alumni, faculty, and staff.

Organizations

Special pricing and tailored programming bundles available for organizational partners.

4.4

178 Ratings from Coursera

Most Recent Reviews

Read all reviews

September 18, 2025

good

June 19, 2025

July 25, 2024

The content was rich but the organisation of content can be improved.

July 23, 2024

Awesome!

January 01, 2024

There were a few issues with the ability to turn projects in, such as the prompt asking you to include a spreadsheet, but you can only upload one document, so your pdf report has to take priority. Look, the class itself was great - I'm rating 2 stars due to the value, mostly thanks to the course's over-reliance on peer review for grades. Though this may just be the only reason I am aware of the real problem. This class essentially allows cheating. I can't even begin to tell you how frustrating it was to "grade" multiple assignments that were either gibberish or literally a blank document. And many of these people uploaded word docs, which required me to download the doc first, only to open it and find it was not taken seriously at all. Some assignments are even titled "help me" as a request to others to rubber stamp their grade. Honestly, it devalues the entire certificate, wastes my time as a serious learner, and is just plain annoying. The fact it, I paid money for this, and I probably paid more than these others since I actually took the time to do the assignments and there is a monthly payment while taking the course. And while I did get value from it - after all, the class itself was great, the laziness/cheating of others (both from those who turn in the fake assignment and from those who grade them at 100% anyway) makes me not want to take any more classes of this kind. And as an employer, it makes me take these certificates less seriously. These types of courses punish those who do the work while rewarding those who don't. And it is literally my own work ethic that is forcing me to finish the specialization lol, even though I probably shouldn't.

October 21, 2023

This course should be redone. I was confused most of the time (about conflicting or incomplete instructions and terminology used but not explained). I did appreciate the instructor's slow rate of speaking.

September 09, 2023

Deffinitely the worst course in the whole specialisation. The instructors don't really bother to explain UX metrics (which doesn't stop them from asking about them in the course assignments), but instead go for lengthy (lengthy as in 45 minutes length) videos, which are way too vague. Importantly, this slopiness (it seems nobody reviewed the course content, much as they promised to do so) doesn't apply to the course participants who have to carry out a 20-people survey and sumbit a report in the last week. Unless you run a research agency, recruiting 20 people takes much longer than a week and I strongly recommend working on it well in advance. That is if you want to earn a specialisation certificate because otherwise I don't see any reason why you'd take this course. Better get yourself a book on UX metric. PS If learning basic statistics is what you are after, then sorry to disappoint you, but for some reason they don't even mention that. though some people might think it proves useful for research at scale

July 11, 2023

An assignment for week 6 is too difficult. No examples of the process of metrics usage or working with spreadsheets were given. Some glossary was given only at the end of the week, after an assignment. The info was presented too vaguely.

March 13, 2023

One of the awesome courses from Michigan UN, It's so helpful for me.

May 14, 2019

The second instructor, Hogan, really needs to work on her slides, as well as explain concepts thoroughly. The 5th quiz was extremely difficult, as it seemed none of the content was discussed by her. Also, the interview in week was a complete waste of my time, seemed like Hogan was just winging it and gained no valuable information. The modules with Hogan truly need work.

UX Research at Scale: Surveys, Analytics, Online Testing

What You'll Learn