Radical Collaboration: how teamwork really can make the dream work

With UX research so closely tied to product success, setting up a dedicated research practice is fast becoming important for many organizations. It’s not an easy process, especially for organizations that have had little to do with research, but the end goal is worth the effort.

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But where exactly are you supposed to start? This article provides 6 key things to keep in mind when setting up a research practice, and should hopefully ensure you’ve considered all of the relevant factors.

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1) Work out what your organization needs

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The first and most simple step is to take stock of the current user research situation within the organization. How much research is currently being done? Which teams or individuals are talking to customers on an ongoing basis? Consider if there are any major pain points with the current way research is being carried out or bottlenecks in getting research insights to the people that need them. If research isn't being practiced, identify teams or individuals that don't currently have access to the resources they need, and consider ways to make insights available to the people that need them.

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2) Consolidate your insights

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UX research should be communicating with nearly every part of an organization, from design teams to customer support, engineering departments and C-level management. The insights that stem from user research are valuable everywhere. Of course, the opposite is also true: insights from support and sales are useful for understanding customers and how the current product is meeting people's needs.

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When setting up a research practice, identify which teams you should align with, and then reach out. Sit down with these teams and explore how you can help each other. For your part, you’ll probably need to explain the what and why of user research within the context of your organization, and possibly even explain at a basic level some of the techniques you use and the data you can obtain.

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Then, get in touch with other teams with the goal of learning from them. A good research practice needs a strong connection to other parts of the business with the express purpose of learning. For example, by working with your organization’s customer support team, you’ll have a direct line to some of the issues that customers deal with on a regular basis. A good working relationship here means they’ll likely feed these insights back to you, in order to help you frame your research projects.

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By working with your sales team, they’ll be able to share issues prospective customers are dealing with. You can follow up on this information with research, the results of which can be fed into the development of your organization’s products.

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It can also be fruitful to develop an insights repository, where researchers can store any useful insights and log research activities. This means that sales, customer support and other interested parties can access the results of your research whenever they need to.

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When your research practice is tightly integrated other key areas of the business, the organization is likely to see innumerable benefits from the insights>product loop.

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3) Figure out which tools you will use

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By now you’ve hopefully got an idea of how your research practice will fit into the wider organization – now it’s time to look at the ways in which you’ll do your research. We’re talking, of course, about research methods and testing tools.

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We won’t get into every different type of method here (there are plenty of other articles and guides for that), but we will touch on the importance of qualitative and quantitative methods. If you haven’t come across these terms before, here’s a quick breakdown:

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• Qualitative research – Focused on exploration. It’s about discovering things we cannot measure with numbers, and often involves speaking with users through observation or user interviews.
• Quantitative research – Focused on measurement. It’s all about gathering data and then turning this data into usable statistics.

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All user research methods are designed to deliver either qualitative or quantitative data, and as part of your research practice, you should ensure that you always try to gather both types. By using this approach, you’re able to generate a clearer overall picture of whatever it is you’re researching.

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Next comes the software. A solid stack of user research testing tools will help you to put research methods into practice, whether for the purposes of card sorting, carrying out more effective user interviews or running a tree test.

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There are myriad tools available now, and it can be difficult to separate the useful software from the chaff. Here’s a list of research and productivity tools that we recommend.

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Tools for research

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Here’s a collection of research tools that can help you gather qualitative and quantitative data, using a number of methods.

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• Treejack – Tree testing can show you where people get lost on your website, and help you take the guesswork out of information architecture decisions. Like OptimalSort, Treejack makes it easy to sort through information and pairs this with in-depth analysis features.
• dScout – Imagine being able to get video snippets of your users as they answer questions about your product. That’s dScout. It’s a video research platform that collects in-context “moments” from a network of global participants, who answer your questions either by video or through photos.
• Ethnio – Like dScout, this is another tool designed to capture information directly from your users. It works by showing an intercept pop-up to people who land on your website. Then, once they agree, it runs through some form of research.
• OptimalSort – Card sorting allows you to get perspective on whatever it is you’re sorting and understand how people organize information. OptimalSort makes it easier and faster to sort through information, and you can access powerful analysis features.
• Reframer – Taking notes during user interviews and usability tests can be quite time-consuming, especially when it comes to analyze the data. Reframer gives individuals and teams a single tool to store all of their notes, along with a set of powerful analysis features to make sense of their data.
• Chalkmark – First-click testing can show you what people click on first in a user interface when they’re asked to complete a task. This is useful, as when people get their first click correct, they’re much more likely to complete their task. Chalkmark makes the process of setting up and running a first-click test easy. What’s more, you’re given comprehensive analysis tools, including a click heatmap.

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Tools for productivity

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These tools aren’t necessarily designed for user research, but can provide vital links in the process.

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• Whimsical – A fantastic tool for user journeys, flow charts and any other sort of diagram. It also solves one of the biggest problems with online whiteboards – finicky object placement.
• Descript – Easily transcribe your interview and usability test audio recordings into text.
• Google Slides – When it inevitably comes time to present your research findings to stakeholders, use Google Slides to create readable, clear presentations.

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4) Figure out how you’ll track findings over time

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With some idea of the research methods and testing tools you’ll be using to collect data, now it’s time to think about how you’ll manage all of this information. A carefully ordered spreadsheet and folder system can work – but only to an extent. Dedicated software is a much better choice, especially given that you can scale these systems much more easily.

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A dedicated home for your research data serves a few distinct purposes. There’s the obvious benefit of being able to access all of your findings whenever you need them, which means it’s much easier to create personas if the need arises. A dedicated home also means your findings will remain accessible and useful well into the future.

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When it comes to software, Reframer stands as one of the better options for creating a detailed customer insights repository as you’re able to capture your sessions directly in the tool and then apply tags afterwards. You can then easily review all of your observations and findings using the filtering options. Oh, and there’s obviously the analysis side of the tool as well.

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If you’re looking for a way to store high-level findings – perhaps if you’re intending to share this data with other parts of your organization – then a tool like Confluence or Notion is a good option. These tools are basically wikis, and include capable search and navigation options too.

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5) Where will you get participants from?

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A pool of participants you can draw from for your user research is another important part of setting up a research practice. Whenever you need to run a study, you’ll have real people you can call on to test, ask questions and get feedback from.

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This is where you’ll need to partner other teams, likely sales and customer support. They’ll have direct access to your customers, so make sure to build a strong relationship with these teams. If you haven’t made introductions, it can helpful to put together a one-page sheet of information explaining what UX research is and the benefits of working with your team.

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You may also want to consider getting in some external help. Participant recruitment services are a great way to offload the heavy lifting of sourcing quality participants – often one of the hardest parts of the research process.

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6) Work out how you'll communicate your research

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Perhaps one of the most important parts of being a user researcher is taking the findings you uncover and communicating them back to the wider organization. By feeding insights back to product, sales and customer support teams, you’ll form an effective link between your organization’s customers and your organization. The benefits here are obvious. Product teams can build products that actually address customer pain points, and sales and support teams will better understand the needs and expectations of customers.

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Of course, it isn’t easy to communicate findings. Here are a few tips:

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• Document your research activities: With a clear record of your research, you’ll find it easier to pull out relevant findings and communicate these to the right teams.
• Decide who needs what: You’ll probably find that certain roles (like managers) will be best served by a high-level overview of your research activities (think a one-page summary), while engineers, developers and designers will want more detailed research findings.

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Continue reading

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• Selling your design recommendations to clients and colleagues – Guest writer Jeff Tang outlines some of his techniques for presenting UX recommendations and answering objections.
• Quantifying the ROI of UX – Ashlea McKay delves into one of the toughest UX questions to answer: “What do we get for our money?”
• How do I explain what UX is? – Ashlea McKay covers how you can explain UX to people who may not necessarily have familiarity with the field.

When Bear Liu was teaching himself design, he struggled remembering concepts since English wasn’t his first language. To help, he started doodling. By drawing pictures that related to what he was learning, he found he could not only remember them better, he could understand and communicate more effectively too. Ever since, he’s used the power of drawings and pictures to relay information in ways people can use.

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Bear gives examples of how visual communication can help design workplaces to relay information in a more memorable and usable way. It may only seem like a minor change, but the difference can be significant.

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Bear’s background 🎤

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Bear Liu is a Product Designer at Xero, an online accounting platform that’s used all over the world. He’s also a Design Mentor at Springboard and CareerFoundry, and an Apple Award-Winning podcast host at BearTalk.

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His background is in science education. As a self-taught designer, Bear has helped a raft of large and small businesses with digital products over the last 16 years. His clients come from diverse backgrounds and industries across the globe. Bear's professional passions also carry over into his hobbies. Outside of work he enjoys reading, drawing, and producing videos & podcasts on tech and design.

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Contact Details:

You can find Bear on LinkedIn, or listen to his podcast, BearTalk.

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Unleash your visual superpower as a communication pro 🦸🏻

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When it comes to addressing business challenges it is important to keep these three aspects in mind: 

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1. Understanding - break down complex problems and solutions so everyone can understand. 
2. Memory - retaining information in your mind is difficult even with note taking.
3. Communication- People relate to words differently, and the meaning of something can easily get lost in translation. This issue is more prevalent with remote work.

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Bear Liu strongly believes that visual communication helps people understand, remember and communicate information more effectively. Why?

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• It helps to focus. Pictures remove distractions and draw attention to where it’s desired.
• It’s a token. A picture is universal - a house or a smiley face means the same thing to people that speak different languages. 
• Most people are visual thinkers. Studies have found humans are hard-wired to process visual information faster. We are better at storing information in images, rather than numbers and letters.

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But what if I can’t draw? This is a common issue Bear finds when talking to people about this. It’s not about the quality of the drawing itself, it’s about what it means. By delivering a message through a picture, it becomes understandable. Many of Bear’s drawings only ever remain in draft form. Even simple doodles can have meanings that make concepts clear.

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In his design work at Xero, Bear has used drawing and sketches to great effect in a range of instances:

• The accessibility tree was a complex, abstract system, but by drawing it (on a literal tree), and adding a few notes alongside it, the terminology became much more understandable.
• Sketching how customers work made it easier to describe how Xero could help them. It was much more memorable than writing it out in paragraphs.
• Wrapping the year in product design. A written summary of a year’s work is long-winded. Instead, Bear drew a tree and pinned key words, quotes and achievements to communicate the highlights.
• UX terminology explanations can be difficult for those outside the industry to comprehend. Bear challenged himself to share 1 minute videos that accompanied simple drawings to help colleagues understand them, and had rave reviews.
• Sketching notes is a great alternative to writing notes at conferences or meetings. Presenters can draw to help audiences follow along, and people in the audience themselves can also sketch their own notes.

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Why it matters  🔥

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Bear has adapted visual thinking to his own product design process and has seen a noticeable improvement in communication as a result.

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People are busy - their brains are packed with all sorts of information, and they’re easily distracted by other things they have on their minds. By delivering information in a way that helps them to focus on it, remember and understand it, designers can achieve their ultimate goals.

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As Bear also notes, drawing is fun. It’s much more rewarding than using words, as well as much more effective.

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Bear used the example of his talk at UX New Zealand 2023 as a great place to use a drawing. Rather than follow along with his message by scribbling notes the whole way through, those in the audience could capture the biggest lessons easily in one simple drawing.

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• First, Bear drew one stick figure to represent himself as a speaker. He drew three speech bubbles, where audience members could write the most notable points he said.
  
• Then he drew another stick figure, which represented the audience member listening to him. They had three thought bubbles, which people could populate with their biggest takeaways from the speech.
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That one simple drawing is a template that can be used in any speech or meeting to remember the key points.

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In the last few years, the influence of AI has steadily been expanding into various aspects of design. In early 2023, that expansion exploded. AI tools and features are now everywhere, and there are two ways designers commonly react to it:

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• With enthusiasm for how they can use it to make their jobs easier
• With skepticism over how reliable it is, or even fear that it could replace their jobs

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Google UX researcher Clara Kliman-Silver is at the forefront of researching and understanding the potential impact of AI on design into the future. This is a hot topic that’s on the radar of many designers as they grapple with what the new normal is, and how it will change things in the coming years.

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Clara’s background 

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Clara Kliman-Silver spends her time studying design teams and systems, UX tools and designer-developer collaboration. She’s a specialist in participatory design and uses generative methods to investigate workflows, understand designer-developer experiences, and imagine ways to create UIs. In this work, Clara looks at how technology can be leveraged to help people make things, and do it more efficiently than they currently are.

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In today’s context, that puts generative AI and machine learning right in her line of sight. The way this technology has boomed in recent times has many people scrambling to catch up - to identify the biggest opportunities and to understand the risks that come with it. Clara is a leader in assessing the implications of AI. She analyzes both the technology itself and the way people feel about it to forecast what it will mean into the future.

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Contact Details:

You can find Clara in LinkedIn or on Twitter @cklimansilver

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What role should artificial intelligence play in UX design process? 🤔

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Clara’s expertise in understanding the role of AI in design comes from significant research and analysis of how the technology is being used currently and how industry experts feel about it. AI is everywhere in today’s world, from home devices to tech platforms and specific tools for various industries. In many cases, AI automation is used for productivity, where it can speed up processes with subtle, easy to use applications.

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As mentioned above, the transformational capabilities of AI are met with equal parts of enthusiasm and skepticism. The way people use AI, and how they feel about it is important, because users need to be comfortable implementing the technology in order for it to make a difference. The question of what value AI brings to the design process is ongoing. On one hand, AI can help increase efficiency for systems and processes. On the other hand, it can exacerbate problems if the user's intentions are misunderstood.

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Access for all 🦾

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There’s no doubt that AI tools enable novices to perform tasks that, in years gone by, required a high level of expertise. For example, film editing was previously a manual task, where people would literally cut rolls of film and splice them together on a reel. It was something only a trained editor could do. Now, anyone with a smartphone has access to iMovie or a similar app, and they can edit film in seconds.

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For film experts, digital technology allows them to speed up tedious tasks and focus on more sophisticated aspects of their work. Clara hypothesizes that AI is particularly valuable when it automates mundane tasks. AI enables more individuals to leverage digital technologies without requiring specialist training. Thus, AI has shifted the landscape of what it means to be an “expert” in a field. Expertise is about more than being able to simply do something - it includes having the knowledge and experience to do it for an informed reason. 

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Research and testing 🔬

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Clara performs a lot of concept testing, which involves recognizing the perceived value of an approach or method. Concept testing helps in scenarios where a solution may not address a problem or where the real problem is difficult to identify. In a recent survey, Clara describes two predominant benefits designers experienced from AI:

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1. Efficiency. Not only does AI expedite the problem solving process, it can also help efficiently identify problems. 
2. Innovation. Generative AI can innovate on its own, developing ideas that designers themselves may not have thought of.

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The design partnership 🤝🏽

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Overall, Clara says UX designers tend to see AI as a creative partner. However, most users don’t yet trust AI enough to give it complete agency over the work it’s used for. The level of trust designers have exists on a continuum, where it depends on the nature of the work and the context of what they’re aiming to accomplish. Other factors such as where the tech comes from, who curated it and who’s training the model also influences trust. For now, AI is largely seen as a valued tool, and there is cautious optimism and tentative acceptance for its application. 

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Why it matters 💡

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AI presents as potentially one of the biggest game-changers to how people work in our generation. Although AI has widespread applications across sectors and systems, there are still many questions about it. In the design world, systems like DALL-E allow people to create AI-generated imagery, and auto layout in various tools allows designers to iterate more quickly and efficiently.

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Like many other industries, designers are wondering where AI might go in the future and what it might look like. The answer to these questions has very real implications for the future of design jobs and whether they will exist. In practice, Clara describes the current mood towards AI as existing on a continuum between adherence and innovation:

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• Adherence is about how AI helps designers follow best practice
• Innovation is at the other end of the spectrum, and involves using AI to figure out what’s possible

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The current environment is extremely subjective, and there’s no agreed best practice. This makes it difficult to recommend a certain approach to adopting AI and creating permanent systems around it. Both the technology and the sentiment around it will evolve through time, and it’s something designers, like all people, will need to maintain good awareness of.

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