How to convince others of the importance of UX research
There’s not much a parent won’t do to ensure their child has the best chance of succeeding in life. Unsurprisingly, things are much the same in product development. Whether it’s a designer, manager, developer or copywriter, everyone wants to see the product reach its full potential.
Key to a product’s success (even though it’s still not widely practiced) is UX research. Without research focused on learning user pain points and behaviors, development basically happens in the dark. Feeding direct insights from customers and users into the development of a product means teams can flick the light on and make more informed design decisions.
While the benefits of user research are obvious to anyone working in the field, it can be a real challenge to convince others of just how important and useful it is. We thought we’d help.
Define user research
If you want to sell the importance of UX research within your organization, you’ve got to ensure stakeholders have a clear understanding of what user research is and what they stand to gain from backing it.
In general, there are a few key things worth focusing on when you’re trying to explain the benefits of research:
More informed design decisions: Companies make major design decisions far too often without considering users. User research provides the data needed to make informed decisions.
Less uncertainty and risk: Similarly, research reduces risk and uncertainty simply by giving companies more clarity around how a particular product or service is used.
Retention and conversion benefits: Research means you’ll be more aligned with the needs of your customers and prospective customers.
Use the language of the people you’re trying to convince. A capable UX research practice will almost always improve key business metrics, namely sales and retention.
The early stages
When embarking on a project, book in some time early in the process to answer questions, explain your research approach and what you hope to gain from it. Here are some of the key things to go over:
Your objectives: What are you trying to achieve? This is a good time to cover your research questions.
Your research methods: Which methods will you be using to carry out your research? Cover the advantages of these methods and the information you’re likely to get from using them.
Constraints: Do you see any major obstacles? Any issues with resources?
Provide examples: Nothing shows the value of doing research quite like a case study. If you can’t find an example of research within your own organization, see what you can find online.
Involve others in your research
When trying to convince someone of the validity of what you’re doing, it’s often best to just show them. There are a couple of effective ways you can do this – at a team or individual level and at an organizational level.
We’ll explain the best way to approach this below, but there’s another important reason to bring others into your research. UX research can’t exist in a vacuum – it thrives on integration and collaboration with other teams. Importantly, this also means working with other teams to define the problems they’re trying to solve and the scope of their projects. Once you’ve got an understanding of what they’re trying to achieve, you’ll be in a better position to help them through research.
Educate others on what research is
Education sessions (lunch-and-learns) are one of the best ways to get a particular team or group together and run through the what and why of user research. You can work with them to work out what they’d like to see from you, and how you can help each other.
Tailor what you’re saying to different teams, especially if you’re talking to people with vastly different skill sets. For example, developers and designers are likely to see entirely different value in research.
Collect user insights across the organization
Putting together a comprehensive internal repository focused specifically on user research is another excellent way to grow awareness. It can also help to quantify things that may otherwise fall by the wayside. For example, you can measure the magnitude of certain pain points or observe patterns in feature requests. Using a platform like Notion or Confluence (or even Google Drive if you don’t want a dedicated platform), log all of your study notes, insights and research information that you find useful.
Whenever someone wants to learn more about research within the organization, they’ll be able to find everything easily.
Bring stakeholders along to research sessions
Getting a stakeholder along to a research session (usability tests and user interviews are great starting points) will help to show them the value that face-to-face sessions with users can provide.
To really involve an observer in your UX research, assign them a specific role. Note taker, for example. With a short briefing on best-practices for note taking, they can get a feel for what’s like to do some of the work you do.
You may also want to consider bringing anyone who’s interested along to a research session, even if they’re just there to observe.
Share your findings – consistently
Research is about more than just testing a hypothesis, it’s important to actually take your research back to the people who can action the data.
By sharing your research findings with teams and stakeholders regularly, your organization will start to build up an understanding of the value that ongoing research can provide, meaning getting approval to pursue research in future becomes easier. This is a bit of a chicken and egg situation, but it’s a practice that all researchers need to get into – especially those embedded in large teams or organizations.
Anything else you think is worth mentioning? Let us know in the comments.
Product, design and research teams today are drowning in user data while starving for user understanding. Never before have teams had such access to user information, analytics dashboards, heatmaps, session recordings, survey responses, social media sentiment, support tickets, and endless behavioral data points. Yet despite this volume of data, teams consistently build features users don't want and miss needs hiding in plain sight.
It’s a true paradox for product, design and research teams: more information has made genuine understanding more elusive.
Because with all this data, teams feel informed. They can say with confidence: "Users spend 3.2 minutes on this page," "42% abandon at this step," "Power users click here." But what this data doesn't tell you is Why.
The Difference between Data and Insight
Data tells you what happened. Understanding tells you why it matters.
Here’s a good example of this: Your analytics show that 60% of users abandon a new feature after first use. You know they're leaving. You can see where they click before they go. You have their demographic data and behavioral patterns.
But you don't know:
Were they confused or simply uninterested?
Did it solve their problem too slowly or not at all?
Would they return if one thing changed, or is the entire approach wrong?
Are they your target users or the wrong segment entirely?
One team sees "60% abandonment" and adds onboarding tooltips. Another talks to users and discovers the feature solves the wrong problem entirely. Same data, completely different understanding.
Modern tools make it dangerously easy to mistake observation for comprehension, but some aspects of user experience exist beyond measurement:
Emotional context, like the frustration of trying to complete a task while handling a crying baby, or the anxiety of making a financial decision without confidence.
The unspoken needs of users which can only be demonstrated through real interactions. Users develop workarounds without reporting bugs. They live with friction because they don't know better solutions exist.
Cultural nuances that numbers don't capture, like how language choice resonates differently across cultures, or how trust signals vary by context.
Data shows what users do within your current product. It doesn't reveal what they'd do if you solved their problems differently to help you identify new opportunities.
Why Human Empathy is More Important than Ever
The teams building truly user-centered products haven't abandoned data but they've learned to combine quantitative and qualitative insights.
Combine analytics (what happens), user interviews (why it happens), and observation (context in which it happens).
Understanding builds over time. A single study provides a snapshot; continuous engagement reveals the movie.
Use data to form theories, research to validate them, and real-world live testing to confirm understanding.
Different team members see different aspects. Engineers notice system issues, designers spot usability gaps, PMs identify market fit, researchers uncover needs.
Adding AI into the mix also emphasizes the need for human validation. While AI can help significantly speed up workflows and can augment human expertise, it still requires oversight and review from real people.
AI can spot trends humans miss, processing millions of data points instantly but it can't understand human emotion, cultural context, or unspoken needs. It can summarize what users say but humans must interpret what they mean.
Understanding users has never been easier from a data perspective. We have tools our predecessors could only dream of. But understanding users has never been harder from an empathy perspective. The sheer volume of data available to us creates an illusion of knowledge that's more dangerous than ignorance.
The teams succeeding aren't choosing between data and empathy, they're investing equally in both. They use analytics to spot patterns and conversations to understand meaning. They measure behavior and observe context. They quantify outcomes and qualify experiences.
Because at the end of the day, you can track every click, measure every metric, and analyze every behavior, but until you understand why, you're just collecting data, not creating understanding.
It’s a chicken and egg situation when it comes to securing funding for a large transformation program in government. On one hand, you need to submit a business case and, as part of that, you need to make early decisions about how you might approach and deliver the program of work. On the other hand, you need to know enough about the problem you are going to solve to ensure you have sufficient funding to understand the problem better, hire the right people, design the right service, and build it the right way.
Now imagine securing hundreds of millions of dollars to design and build a service, but not feeling confident about what the user needs are. What if you had the opportunity to change this common predicament and influence your leadership team to carry out alignment activities, all while successfully delivering within the committed time frames?
Meera Pankhania, Design Director and Co-founder of Propel Design, recently spoke at UX New Zealand, the leading UX and IA conference in New Zealand hosted by Optimal Workshop, on traceability and her learnings from delivering a $300 million Government program.
In her talk, Meera helps us understand how to use service traceability techniques in our work and apply them to any environment - ensuring we design and build the best service possible, no matter the funding model.
Background on Meera Pankhania
As a design leader, Meera is all about working on complex, purpose-driven challenges. She helps organizations take a human-centric approach to service transformation and helps deliver impactful, pragmatic outcomes while building capability and leading teams through growth and change.
Meera co-founded Propel Design, a strategic research, design, and delivery consultancy in late 2020. She has 15 years of experience in service design, inclusive design, and product management across the private, non-profit, and public sectors in both the UK and Australia.
Meera is particularly interested in policy and social design. After a stint in the Australian Public Service, Meera was appointed as a senior policy adviser to the NSW Minister for Customer Service, Hon. Victor Dominello MP. In this role, she played a part in NSW’s response to the COVID pandemic, flexing her design leadership skills in a new, challenging, and important context.
From funding to delivery: ensuring alignment from start to finish 🏁🎉👏
Meera’s talk explores a fascinating case study within the Department of Employment Services (Australia) where a substantial funding investment of around $300 million set the stage for a transformative journey. This funding supported the delivery of a revamped Employment Services Model, which had the goal of delivering better services to job seekers and employers, and a better system for providers within this system. The project had a focus on aligning teams prior to delivery, which resulted in a huge amount of groundwork for Meera.
Her journey involved engaging various stakeholders within the department, including executives, to understand the program as a whole and what exactly needed to be delivered. “Traceability” became the watchword for this project, which is laid out in three phases.
Phase 1: Aligning key deliverables
Phase 2: Ensuring delivery readiness
Phase 3: Building sustainable work practices
Phase 1: Aligning key deliverables 🧮
Research and discovery (pre-delivery)
Meera’s work initially meant conducting extensive research and engagement with executives, product managers, researchers, designers, and policymakers. Through this process, a common theme was identified – the urgent (and perhaps misguided) need to start delivering! Often, organizations focus on obtaining funding without adequately understanding the complexities involved in delivering the right services to the right users, leading to half-baked delivery.
After this initial research, some general themes started to emerge:
Assumptions were made that still needed validation
Teams weren’t entirely sure that they understood the user’s needs
A lack of holistic understanding of how much research and design was needed
The conclusion of this phase was that “what” needed to be delivered wasn’t clearly defined. The same was true for “how” it would be delivered.
Traceability
Meera’s journey heavily revolved around the concept of "traceability” and sought to ensure that every step taken within the department was aligned with the ultimate goal of improving employment services. Traceability meant having a clear origin and development path for every decision and action taken. This is particularly important when spending taxpayer dollars!
So, over the course of eight weeks (which turned out to be much longer), the team went through a process of combing through documents in an effort to bring everything together to make sense of the program as a whole. This involved some planning, user journey mapping, and testing and refinement.
Documenting Key Artifacts
Numerous artifacts and documents played a crucial role in shaping decisions. Meera and her team gathered and organized these artifacts, including policy requirements, legislation, business cases, product and program roadmaps, service maps, and blueprints. The team also included prior research insights and vision documents which helped to shape a holistic view of the required output.
After an effort of combing through the program documents and laying everything out, it became clear that there were a lot of gaps and a LOT to do.
Prioritising tasks
As a result of these gaps, a process of task prioritization was necessary. Tasks were categorized based on a series of factors and then mapped out based on things like user touch points, pain points, features, business policy, and technical capabilities.
This then enabled Meera and the team to create Product Summary Tiles. These tiles meant that each product team had its own summary ahead of a series of planning sessions. It gave them as much context (provided by the traceability exercise) as possible to help with planning. Essentially, these tiles provided teams with a comprehensive overview of their projects i.e. what their user needs, what certain policies require them to deliver, etc.
Phase 2: Ensuring delivery readiness 🙌🏻
Meera wanted every team to feel confident that we weren’t doing too much or too little in order to design and build the right service, the right way.
Standard design and research check-ins were well adopted, which was a great start, but Meera and the team also built a Delivery Readiness Tool. It was used to assess a team's readiness to move forward with a project. This tool includes questions related to the development phase, user research, alignment with the business case, consideration of policy requirements, and more. Ultimately, it ensures that teams have considered all necessary factors before progressing further.
Phase 3: Building sustainable work practices 🍃
As the program progressed, several sustainable work practices emerged which Government executives were keen to retain going forward.
Some of these included:
ResearchOps Practice: The team established a research operations practice, streamlining research efforts and ensuring that ongoing research was conducted efficiently and effectively.
Consistent Design Artifacts: Templates and consistent design artifacts were created, reducing friction and ensuring that teams going forward started from a common baseline.
Design Authority and Ways of Working: A design authority was established to elevate and share best practices across the program.
Centralized and Decentralized Team Models: The program showcased the effectiveness of a combination of centralized and decentralized team models. A central design team provided guidance and support, while service design leads within specific service lines ensured alignment and consistency.
Why it matters 🔥
Meera's journey serves as a valuable resource for those working on complex design programs, emphasizing the significance of aligning diverse stakeholders and maintaining traceability. Alignment and traceability are critical to ensuring that programs never lose sight of the problem they’re trying to solve, both from the user and organization’s perspective. They’re also critical to delivering on time and within budget!
Traceability key takeaways 🥡
Early Alignment Matters: While early alignment is ideal, it's never too late to embark on a traceability journey. It can uncover gaps, increase confidence in decision-making, and ensure that the right services are delivered.
Identify and audit: You never know what artifacts will shape your journey. Identify everything early, and don’t be afraid to get clarity on things you’re not sure about.
Conducting traceability is always worthwhile: Even if you don’t find many gaps in your program, you will at least gain a high level of confidence that your delivery is focused on the right things.
Delivery readiness key takeaways 🥡
Skills Mix is Vital: Assess and adapt team member roles to match their skills and experiences, ensuring they are positioned optimally.
Not Everyone Shares the Same Passion: Recognize that not everyone will share the same level of passion for design and research. Make the relevance of these practices clear to all team members.
Sustainability key takeaways 🥡
One Size Doesn't Fit All: Tailor methodologies, templates, and practices to the specific needs of your organization.
Collaboration is Key: Foster a sense of community and collective responsibility within teams, encouraging shared ownership of project outcomes.
If there’s one universal truth in user research, it’s that at some point you’re going to need to find people to actually take part in your studies. Be it a large number of participants for quantitative research or a select number for in-depth, in-person user interviews. Finding the right people (and number) of people can be a hurdle.
With the right strategy, you can source exactly the right participants for your next research project.
We share a practical step-by-step guide on how to find participants for user experience research.
The difficulties/challenges of user research recruiting 🏋️
It has to be acknowledged that there are challenges when recruiting research participants. You may recognize some of these:
There are so many channels and methods you can use to find participants, different channels will work better for different projects.
Repeatedly using the same channels and methods will result in diminishing returns (i.e. burning out participants).
It’s a lengthy and complex process, and some projects don’t have the luxury of time.
Offering the right incentives and distributing them is time-consuming.
It’s hard to manage participants during long-term or recurring studies, such as customer research projects.
We’ll simplify the process, talk about who the right participants are, and unpack some of the best ways to find them. Removing these blocks can be the easiest way to move forward.
Who are the right participants for different types of research? 🤔
1. The first step to a successful participant recruitment strategy is clarifying the goals of your user research and which methods you intend to use. Ask yourself:
What is the purpose of our research?
How do we plan to understand that?
2. Define who your ideal research participant is. Who is going to have the answers to your questions?
3. Work out your research recruitment strategy. That starts by understanding the differences between recruiting for qualitative and quantitative research.
Recruiting for qualitative vs. quantitative research 🙋🏻
Quantitative research recruiting is a numbers game. For your data analysis to be meaningful and statistically significant, you need a lot of data. This means you need to do a lot of research with a lot of people. When recruiting for quantitative research, you first have to define the population (the entire group you want to study). From there, you choose a sampling method that allows you to create a sample—a randomly selected subset of the population who will participate in your study.
Qualitative recruiting involves far fewer participants, but you do need to find a selection of ‘perfect’ participants. Those that fit neatly into your specific demographic, geographic, psychographic, and behavioral criteria relevant to your study. Recruiting quality participants for qualitative studies involves non-random sampling, screening, and plenty of communication.
How many participants do you need? 👱🏻👩👩🏻👧🏽👧🏾
How many participants to include in a qualitative research study is one of the most heavily discussed topics in user research circles. In most cases, you can get away with 5 people – that’s the short answer. With 5 people, you’ll uncover most of the main issues with the thing you’re testing. Depending on your research project there could be as many as 50 participants, but with each additional person, there is an additional cost (money and time).
Quantitative research is obviously quite different. With studies like card sorts and tree tests, you need higher participant numbers to get statistically meaningful results. Anywhere from 20 - 500 participants, again coming back to the purpose of your test and your research budget. These are usually easier and quicker to implement therefore the additional cost is lower.
User research recruitment - step by step 👟
Let’s get into your research recruitment strategy to find the best participants for your research project. There are 5 clear steps to get you through to the research stage:
1. Identify your ideal participants
Who are they? What do they do? How old are they? Do they already use your product? Where do they live? These are all great questions to get you thinking about who exactly you need to answer your research questions. The demographic and geographic detail of your participants are important to the quality of your research results.
2. Screen participants
Screening participants will weed out those that may not be suitable for your specific project. This can be as simple as asking if the participants have used a product similar to yours. Or coming back to your key identified demographic requirements and removing anyone that doesn’t fit these criteria.
3. Find prospective participants
This is important and can be time-consuming. For qualitative research projects, you can look within your organization or ask over social media for willing participants. Or if you’re short on time look at a participant recruitment service, which takes your requirements and has a catalog of available persons to call on. There’s a cost involved, but the time saving can negate this. For qualitative surveys, a great option can be a live intercept on your website or app that interrupts users and asks them to complete a short questionnaire.
4. Research incentives
In some cases you will need to provide incentives. This could be offering a prize or discount for those who complete online qualitative surveys. Or a fixed sum for those that take part in longer format quantitative studies.
5. Scheduling with participants
Once you have waded through the emails, options, and communication from your inquiries make a list of appropriate participants. Schedule time to do the research, either in person or remotely. Be clear about expectations and how long it will take. And what the incentive to take part is.
Tips to avoid participant burnout 📛
You’ve got your participants sorted and have a great pool of people to call on. If you keep hitting the same group of people time and time again, you will experience the law of diminishing returns. Constantly returning to the same pool of participants will eventually lead to fatigue. And this will impact the quality of your research because it’s based on interviewing the same people with the same views.
There are 2 ways to avoid this problem:
Use a huge database of potential participant targets.
Use a mixture of different recruitment strategies and channels.
Of course, it might be unavoidable to hit the same audience repeatedly when you’re testing your product development among your customer base.
Wrap up 🌯
Understanding your UX research recruitment strategy is crucial to recruiting quality participants. A clear idea of your purpose, who your ideal participants are, and how to find them takes time and experience.
And to make life easier you can always leave your participant recruitment with us. With a huge catalog of quality participants all at your fingertips on our app, we can recruit the right people quickly.
