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Data-Driven Design: Quantitative Research for UX

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How This Course Will Help Your Career

What You Will Learn

  • What quantitative research is and how it differs from qualitative

  • Why quantitative research is important

  • Alternatives to quantitative methods

  • Simple statistical analysis

  • Quantitative methods in detail: surveys, early-design testing, web/app analytics and A/B testing

  • Participant recruitment and screening

Quantitative research is about understanding user behavior at scale. In most cases the methods we’ll discuss are complementary to the qualitative approaches more commonly employed in user experience. In this course you’ll learn what quantitative methods have to offer and how they can help paint a broader picture of your users’ experience of the solutions you provide—typically websites and apps.

Since quantitative methods are focused on numerical results, we’ll also be covering statistical analysis at a basic level. You don’t need any prior knowledge or experience of statistics, and we won’t be threatening you with mathematical formulas. The approach here is very practical, and we’ll be relying instead on the numerous free tools available for analysis using some of the most common statistical methods.

In the “Build Your Portfolio: Research Data Project”, you’ll find a series of practical exercises that will give you first-hand experience of the methods we’ll cover. If you want to complete these optional exercises, you’ll create a series of case studies for your portfolio which you can show your future employer or freelance customers.

Your instructor is William Hudson. He’s been active in interactive software development for around 50 years and HCI/User Experience for 30. He has been primarily a freelance consultant but also an author, reviewer and instructor in software development and user-centered design.

You earn a verifiable and industry-trusted Course Certificate once you’ve completed the course. You can highlight it on your resume, your LinkedIn profile or your website.

Gain an Industry-Recognized UX Course Certificate

Use your industry-recognized Course Certificate on your resume, CV, LinkedIn profile or your website.

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Our courses and Course Certificates are trusted by these industry leaders:

Our clients: IBM, HP, Adobe, GE, Accenture, Allianz, Phillips, Deezer, Capgemin, Mcafee, SAP, Telenor, Cigna, British Parliament, State of New York

Is this course right for you?

This is a beginner-level course for anyone who wants to understand and apply quantitative research in user experience settings. This course is particularly valuable for:

  • User researchers and UX practitioners interested in gaining insight into user behavior at scale.
  • Project managers and stakeholders who want to help their team to understand the full range of research tools available to them.
  • Stakeholders who are keen to get involved in and manage the creative process of developing a new product or service.
  • Entrepreneurs looking to use quantitative insights to develop products that fit the market and users’ lives.
  • Anyone who is interested finding out more about how users and interactive systems behave in actual use.

Learn and work with a global community of designers

When you take part in this course, you’ll join a global community and work together to improve your skills and career opportunities. Connect with helpful peers and make friends with like-minded individuals as you push deeper into the exciting and booming industry of creativity and design. You will have the opportunity to share ideas, learn from your fellow course participants and enjoy the social aspects afforded by our open and friendly forum.

Course Overview: What You'll Master

  • Each week, one lesson becomes available.
  • There's no time limit to finish a course. Lessons have no deadlines.
  • Estimated learning time: 28 hours 2 mins spread over 9 weeks .

Lesson 0: Welcome and Introduction

Available once you start the course. Estimated time to complete: 1 hour 38 mins.

Lesson 1: Why Design with Data?

Available once you start the course. Estimated time to complete: 2 hours 8 mins.

Lesson 2: Statistics

Available anytime after May 09, 2025. Estimated time to complete: 5 hours 36 mins.

Lesson 3: Surveys

Available anytime after May 16, 2025. Estimated time to complete: 4 hours 8 mins.

Lesson 4: Early-Design Testing

Available anytime after May 23, 2025. Estimated time to complete: 3 hours 40 mins.

Lesson 5: Web and App Analytics

Available anytime after May 30, 2025. Estimated time to complete: 6 hours 51 mins.

Lesson 6: A/B and Multivariate Testing

Available anytime after Jun 06, 2025. Estimated time to complete: 4 hours 1 min.

Lesson 7: Course Certificate, Final Networking, and Course Wrap-up

Available anytime after Jun 13, 2025.

How Others Have Benefited

Louiselle Morand Salvo

Louiselle Morand Salvo, Switzerland

“Very well structured (overall syllabus + individual lessons), useful tools, and very precise information. The feedback on the questions is detailed; I'm impressed by the work done by the teacher!”

Andrea Wilkins

Andrea Wilkins, United Kingdom

“The instructor is an incredible teacher. He was so engaging and felt so relaxed throughout. You can tell he's done this before. I could listen to him teach all day.”

Norman Laborde

Norman Laborde, Puerto Rico

“William explained complex concepts in a way that was approachable. The resources he offered were valuable and I have a good list of new books and bookmarks that resulted from the course.”

See other reviews

How It Works

  1. Take online courses by industry experts

    Lessons are self-paced so you'll never be late for class or miss a deadline.

  2. Get a Course Certificate

    Your answers are graded by experts, not machines. Get an industry-recognized Course Certificate to prove your skills.

  3. Advance your career

    Use your new skills in your existing job or to get a new job in UX design. Get help from our community.

Start Advancing Your Career Now

Join us to take “Data-Driven Design: Quantitative Research for UX”. Take other courses at no additional cost. Make a concrete step forward in your career path today.

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Data-Driven Design: Quantitative Research for UX
Closes in
01
hr
23
mins
13
secs
13% booked

Data-Driven Design: Quantitative Research for UX

0.1 - Welcome and Introduction

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  1. 00:00:00 --> 00:00:31

    Why even bother designing with data? What are the benefits? What can we expect from it? The big question "Why design with data?" – user research as a field, which stems from usability from back in the 1980s and even earlier – has tended to be very much *qualitative* in focus: focusing on what people say, their attitudes and behaviors,

  2. 00:00:31 --> 00:01:04

    whereas *quantitative* research is much more about hard numbers – counting the outcomes of either *experiments*, which is what we do when we're conducting online tests  or surveys, or perhaps in face-to-face research. But most of what we do tends to be online when it comes to the quantitative side because that's simply the easiest  way of getting hold of respondents. Just having a bag full of numbers or a field full of numbers is not so useful

  3. 00:01:04 --> 00:01:34

    in its own right, so we really need to know what these numbers are telling us. There are a number of benefits, though, to quantitative methods. We can get a better understanding of our design issues because it's a different way of looking at the issue. So, different perspectives often lead to better understanding. We can get greater confidence in our design decisions, and that's really important in some organizations – that we know that we are on the right tracks because we have different conclusions

  4. 00:01:34 --> 00:02:03

    from research that we've done – both  qualitative and quantitative – that tell us that   *yes* – this is the right way to go. And overall that means that we are making much more persuasive justifications for design choices; and if you're working in project teams or within organizations who really don't have a good understanding of *qualitative* methods, then being able to supplement those with quantitative research is very important.

  5. 00:02:03 --> 00:02:32

    It's the way that you're going to get the funding for the kinds of  activities that you're discovering to be important and the kinds of design changes that you want and need to make. So, this last point is particularly relevant. You might be in a big organization that's very technology-focused; you might just be in a little team that's technology-focused, or you might just be working with a developer who just doesn't get qualitative research. So, in all of these cases – big, small and in between –

  6. 00:02:32 --> 00:02:52

    having different tools in your bag that you can call on, you can bring out and apply as required to make persuasive arguments is going to be really, really important. So, understanding about quantitative research and how to do it and what the numbers mean is all going to be an important part of that.

Data-Driven Design: Quantitative Research for UX

4.2 - Early-Design Testing

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  1. 00:00:00 --> 00:00:34

    We're going to be looking at a couple  of testing tools or testing techniques, one called tree testing and the other called first-click testing, which are *admirably suitable* for early design. So, you're working on – you're thinking of how your website should be navigated or you're working on some very rough wireframes or  general ideas about how that navigation should be

  2. 00:00:34 --> 00:01:05

    presented in the context of your project, and you'd like to get some feedback. And these two techniques are really absolutely ideal for that scenario. But, having said that, both of these techniques: tree testing and first-click testing can be used at  *any stage* in project development, so all the way from early design through to final buffing and  polishing, say, of the navigation framework. If you want to just make a tiny change and see  how that affects the site *before* you launch,

  3. 00:01:05 --> 00:01:31

    then something like tree testing may be absolutely ideal. And one of the real strengths of these tools is that they're pretty  isolated in the sense that you're only testing one or two very specific components of your overall solution. So, tree testing in fact is absolutely laser-focused on your navigation; that is all you're presenting, and you're not presenting it with any kind of visual component.

  4. 00:01:31 --> 00:02:02

    It's presented, it's simulated by the testing tool. So, you just upload a navigation tree that you want to test and you give your participants some goals and off they go; and you're testing now  how they understand those words – nothing to distract them; there are no visual distractions at all. But they do lose a little bit of the context that way, as we'll see a bit later on, too. So, early-design testing allows design components to be evaluated *prior* to extensive development efforts.

  5. 00:02:02 --> 00:02:32

    So, you could be doing this in the first week of a new project. There would be no problem at all in that. It might take a little while to *organize*, but certainly you could be seeing results only  a couple of weeks into your project. There are *many* forms of early-design testing. The particular attraction of these is that they are what we call *quantitative* – they produce numbers where we get to  actually see some statistics on how people perform in these particular tasks.

  6. 00:02:32 --> 00:03:01

    Paper prototyping I list as an alternative here. That is not a quantitative process *typically*. We're not actually looking mostly at success when we're talking about paper prototyping. We're looking at a *qualitative* focus, so we're trying to understand what's going through people's minds and we ask them about  why things didn't work and what's going on inside their head. That's very similar to usability testing, and usability testing is predominantly a qualitative process.

  7. 00:03:01 --> 00:03:34

    So, these are almost entirely quantitative; they're done *online*, and that means that we're not really going to be able to get  inside our participants' heads, but that is both a benefit and a drawback. The benefit is that we're going to get some hard numbers out of it and it's very quick to do. We will be typically testing with dozens, scores of participants – certainly, 100 participants wouldn't be difficult to imagine. Whereas in usability testing, a day's work is represented by about seven

  8. 00:03:34 --> 00:04:00

    participants, maybe up to 90-minute sessions, so they are quite different animals from that point of view. And I won't be talking any more about usability testing in this. It was just by way of comparison. And usability testing, of course, as I mentioned is a qualitative technique. The *reasons* that you might consider early-design testing – well, it's relatively quick and inexpensive; done online, primary costs with that are actually *recruitment costs*

  9. 00:04:00 --> 00:04:30

    – getting people to come and take our studies; so, there isn't the renting of a lab for any kind of qualitative research; there isn't the hiring of researchers; You set up the project; you leave it to run; you recruit participants to it, and you check on your results a few days later. It can be as straightforward as that. Only minimal navigation or visual design is needed; you don't have to have thought things through absolutely to the end of the process.

  10. 00:04:30 --> 00:05:01

    You can get some really good feedback about what's working and what it isn't from the very earlier stages, and again that's really one of the main strengths of the whole approach in both of these cases. Very effective for early design, and – as I mentioned  already – can be used at any stage in a project. And I've hinted at this, but I will now put it in very precise terms that it's a *goal-oriented focus*; in all these cases we present our navigation or our visual design along with some tasks

  11. 00:05:01 --> 00:05:32

    – a list of tasks that we would like users to try to pursue. And we're looking at how they *perform*; so, that is the quantitative aspect of it. It is purely *what they do*. There is no element of asking them how they feel about it or why they've made those particular decisions – although those are optional extras in some cases. Certainly, the *why* aspect of it can be; but *predominantly* we're talking about the numbers that come out of the end. And that's why we need at least several score participants

  12. 00:05:32 --> 00:06:00

    – something around the 30–50 mark as a starting point. For existing solutions, you could use early-design testing for identifying problem areas. So, if you've got some problems on a page or with a site in general but you just don't really have a handle on what those problems are, then trying to give people some specific  tasks and then giving them your navigation structure may produce some *really* very straightforward feedback on that issue.

  13. 00:06:00 --> 00:06:31

    You also can use it for collecting data for improving designs, along similar lines; you would try out things that you know people seem to be struggling with or that are really important to your organization's goals with a particular solution and see how people fare. *New solutions* – well, evaluating and improving design elements; it's really more or less exactly the same process, but you might be at the beginning of a new solution, be trying to understand what was good, what was bad about the *old solution*.

  14. 00:06:31 --> 00:07:01

    Certainly, knowing what worked is a good situation to be in when you're setting off to revamp a design. *Alternatives* – well, I already hinted at paper prototyping, and I've already said that that is primarily qualitative; we're talking about very small numbers of people for a fair bit of researcher effort. But it is different and it is qualitative, so we won't be going into detail about that here. Web app or analytics – the problem there is that we know what people do but we don't really know why they've done it.

  15. 00:07:01 --> 00:07:31

    So, we might find that people were bouncing between two pages in a website or a mobile app and not really understand *why*. So, we've got numbers that say "There's something going on here" but no way of finding out. So, if you have suspicions that it's navigation-related or the visual design we test with the first-click testing, then we can try that out pretty quickly and relatively cheaply, compared with some other approaches – particularly the qualitative ones, which do tend to be more expensive.

  16. 00:07:31 --> 00:07:57

    And, finally, card sorting is another technique you might consider. It can be used both qualitatively and quantitatively. And we won't be talking about that in these modules, but  you will find information on card sorting on the Interaction Design Foundation website. There's a very extensive encyclopedia article that I wrote about card sorting several years ago, which you should find pretty useful in that respect.

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