UX Research: Practical Techniques for Designing Better Products

  • Page 8 Throughout this book you'll find exercises that connect the tasks of research with the act of being in the world. Preface
  • Page 17 We will compare the rigor of research in academic settings with the streamlined and often-accelerated research found in product design.
  • Page 17 Advances in manufacturing and mass production allowed improvements in efficiency and utility to be explored in a scalable and measurable manner.
  • Page 20 who knows the challenges of a task better than those completing them?
  • Page 22 GOMS: Goals, operators, methods, and selection rules measure the intent and process of a system. Conveniently, this approach can apply to both physical and digital spaces.
  • Page 23 Goals asks the question "What do you want to do?" ... This pillar questions participants' frame of mind and clarifies what supporting information might be needed to be successful not just in the moment but also throughout a task. ... Operators seeks to understand "What tools do you have as a person to get the job done?" ... Methods looks at "How can the tools, or operators, be used to complete the task?" ... Selection rules, the final pillar of GOMS, measures the various options an interface or product offers to assist users in accomplishing their goals.
  • Page 25 GOMS in practice: Keystroke-Level Modeling ... At its simplest, KLM is the mathematical study of a tool's efficiency.
  • Page 38 Good research starts with good questions. You must start with an idea of what type of questions you want to ask.
  • Page 39 It's hard to conduct research when you don't know what question needs to be answered. Every research effort starts with you needing to know why something happens, what people do in certain circumstances, and how they perform key tasks.
  • Page 39 we must find people to talk to and phrase our questions effectively to get to the heart of the matter.
  • Page 40 The following factors can lead to misinformed or poor research results. ... Leading questions ... Research participants want to be helpful and want to provide value to your team. Since they are primed to help, if you ask a question that implies the type of answer you want, they are more likely to give you that answer, even if it doesn't really apply to them. ... Shallow questions ... Yes/ no questions are harmful because they give participants an easy out. ... Personal bias ... The less "you" there is in the interview, the better the information that you collect will be. ... "Tell me about your experience with your accounting software" than "I know I always struggle with invoices; what challenges do you have with your software?" ... Knowing When to Break the Rules ... You can even use a participant's personal and unconscious bias to drive to a deeper conversation about how people might use a product. ... You can use leading questions to help build trust with a participant and to validate a previous comment they made that maybe wasn't totally clear. ... When you start a research session, sometimes participants aren't yet comfortable and they need to get used to talking with you and answering your questions. Shallow questions give participants that opportunity and can help ease them into the activity so you can get to the good stuff.
  • Page 43 The Basic Structure of a Question
    The Setup: Every question starts with a purpose, or setup. This takes the form of what (description), why (explanation), how (process), when (situation), and where (context). It gives the participant an idea of the type and, more importantly, the length of response you expect out of them.
  • Page 44 Area of Inquiry: The area of inquiry is what you want to learn about— for example, how your product impacts or influences someone's life.
  • Page 44 Laddering: Some responses to your questions will have an automatic "Why?" behind them. Asking for a participant to go into more detail or to explain the rationale behind their response is known as laddering, and it's an aspect of a question that helps you get to deeper information and potentially impactful stories.
  • Page 44 Segue to Next Question: The best research sessions are focused conversations between you and a participant.
  • Page 45 Every question in your interview guide should tie back to why you're doing research in the first place.
  • Page 45 Example: Learn about how people determine which photos to share with family and friends. Bad question: How do you ensure that you get good composition when you're out taking photos? Revised question: When you're out taking photos, how do you know a particular shot is worth sharing with people?
  • Page 47 Figuring out what we want to learn is the easiest part of my day. The hard part is translating our big research questions into good interview questions. We're often trying to answer abstract questions (like "What's hard about interacting with the government?"), but abstract interview questions aren't fruitful.
  • Page 50 The motto of a good researcher is "there is no such thing as user error." One thing you'll learn is that many users will blame themselves. These are moments of exploration because you can get to the source of why errors are made and what frustrates users when things don't work out for them.
  • Page 50 How to Practice Asking Questions ...It's always a good idea to validate your interview guide internally. From the product owner to the engineering team, these are the folks who are putting their time and energy into building a product, and their feedback helps refine and shift your lines of questioning.
  • Page 56 Quantitative Research by the Numbers Quantitative research is simply defined as the study of what can be measured and observed.
  • Page 56 quantitative research means the results will be consistent and generally agreed on by all parties involved.
  • Page 56 Bounce rates Time on task Conversion rates Order size (number of items or their value) Number of visitors to a site (physical or digital) Average size of group
  • Page 58 While very informative, quantitative research doesn't tell us how to fix things, doesn't tell us why things happen, and doesn't share information that isn't asked for. That being said, quantitative research can act as a benchmark for future studies and for qualitative research.
  • Page 59 Numbers do not consider context of use. ... Insight-driven research seeks to understand what the problem space is, why the problem exists, and where opportunities lie. ... For quantitative research, insight-driven research manifests as benchmarks, often referred to as key performance indicators (KPIs). ... Evaluative research, on the other hand, looks to measure how a design or solution stands up to the KPIs and benchmarks laid out.
  • Page 61 Lastly, generative research methods offer opportunities to create and explore new designs through research. Often called data-driven design, generative research methods balance subjective design recommendations and trends with quantifiable, measurable gains and opportunities.
  • Page 61 System analytics are probably the most common form of quantitative data. Often referred to as site analytics for web-based experiences, analytics provide passive access to a wide array of data points. Analytics are a great example of insight-driven research because of their low cost of entry and, assuming correct tagging on the backend, depth of information. Some of the most common pieces of data include user flows, demographics, and geography.
  • Page 63 Unlike analytics, surveys straddle both evaluative and insight-driven methodologies by providing data around not only how a system is used but also how it might meet or fail to meet expectations.
  • Page 65 Tree Jacking Tree jacking is an example of a generative research method, though it can also be used as an evaluative measure. It is a method of evaluating a system's navigation and terminology. A designer will enter a proposed taxonomy into the system and prompt customers to navigate the information. By clicking through the site map, the designer gathers data on users' expectations and understanding of terms by tracking their path through the tree structure.
  • Page 71 different. Quantitative methods are best used when a large number of participants or customers may be accessed for the most statistically significant outcomes.
  • Page 71 A good question for quantitative research might be "How many users abandon the checkout process when signing up for a product's service?"
  • Page 72 When you are looking to understand a user's motivations or comprehension of a task, qualitative methods, covered in Chapter 4, offer more tangible results. Similarly, if you have access only to a small number of users, analytics may not be statistically significant.
  • Page 77 design. As efficiencies in technology reach a predictable flow, designers seek to do more than streamline tasks. They ask what drives people to do the work they do and what makes it enjoyable. Enter qualitative research.
  • Page 77 is subjective, notably the personal stories and challenges of our customers. Where quantitative research focuses on what can be measured, such as the time to complete a task, qualitative research looks at why customers are completing the task in the first place. Qualitative research seeks to understand customers' motivations and desires by focusing on comprehension and accessibility that might not be numerically measured, but can nevertheless impact usability and desirability of systems.
  • Page 78 Qualitative research has roots in ethnography, anthropology, and psychology. The study of how humans behave is, at its core, qualitative research.
  • Page 78 Projects may have as few as 5-10 participants or, for projects with a broad scope and range of user profiles, upward of 20-40 people.
  • Page 81 For a landscape analysis, designers identify existing products or services that reflect a portion of the new product's functions or customer segmentation. ... identify broad gaps or opportunities
  • Page 84 Contextual inquiry Contextual inquiries— also known by names like think-aloud studies and ride-along studies— are easily the most common version of discovery and exploration.
  • Page 86 Contextual inquiries can be conducted with as few as 5 or as many as 50 participants, depending on the project scope.
  • Page 86 This is a major distinction from quantitative research, where large data pools are the only way to guarantee good data. Contextual inquiries instead rely on trends and the researcher's experience and ability to make judgment calls about what is important.
  • Page 86 as you start to hear the same information again and again, you have conducted enough research.
  • Page 88 Participatory Design Participatory design takes on many shapes and flavors. This may be as simple as a workshop brainstorming ideas and opportunities, or a more formal sketching exercise. Participants may be asked to sketch actual interfaces or adapt their mental model in visual ways.
  • Page 93 Qualitative methods prove effective when there is a small, identifiable population of customers.
  • Page 93 One of the major hurdles qualitative research has is that it is a "soft science." Because it's not based in numbers like its sibling, quantitative research, many business stakeholders don't want to rely on qualitative research alone. To address this, invite stakeholders to observe and participate in qualitative research so they might experience the "aha" moments directly.
  • Page 93 Quantitative and qualitative research methods are equals, not opposites. You cannot have one without the other. The most successful projects balance the two and inform our product designs.
  • Page 94 Personas are fictional customers you create to represent various user types. These may include the call center representative, the tech native, or the Luddite. Traditional market segments are typically focused on the numbers (age, gender, geography) of customers. Similarly, classical personas may be generated from a handful of contextual inquiries with no hard data grounding them.
  • Page 94 Data-driven personas balance this. By combining the analytical data about who's using a system with the data on users' wants, needs, and motivations
  • Page 95 Data-Driven Customer Journeys Customer journeys are often created to illustrate the touchpoints a customer has throughout a process. This may be inclusive of an entire ecosystem, from researching cars online to entering an auto dealership to purchasing the car and making payments. It may also be more specific, such as onboarding for a new piece of technology.
  • Page 101 Qualitative methods are great for small sample sizes, especially when you can travel to participants in their environment. But with products spanning global markets, travel costs and time may become cost-prohibitive. While many qualitative methods can be used remotely, location is one key factor in determining a research approach.
  • Page 103 While a good foundation is important for choosing methods, the best research initiatives borrow from both qualitative and quantitative research methods.