Radical Collaboration: how teamwork really can make the dream work
Natalie and Lulu have forged a unique team culture that focuses on positive outputs (and outcomes) for their app’s growing user base. In doing so, they turned the traditional design approach on its head and created a dynamic and supportive team.
Natalie, Director of Design at Hatch, and Lulu, UX Design Specialist, recently spoke at UX New Zealand, the leading UX and IA conference in New Zealand hosted by Optimal Workshop, on their concept of “radical collaboration”.
In their talk, Nat and Lulu share their experience of growing a small app into a big player in the finance sector, and their unique approach to teamwork and culture which helped achieve it.
Background on Natalie Ferguson and Lulu Pachuau
Over the last two decades, Lulu and Nat have delivered exceptional customer experiences for too many organizations to count. After Nat co-founded Hatch, she begged Lulu to join her on their audacious mission: To supercharge wealth building in NZ. Together, they created a design and product culture that inspired 180,000 Kiwi investors to join in just 4 years.
Radical Collaboration - How teamwork makes the dream work 💪💪💪
Nat and Lulu discuss how they nurtured a team culture of “radical collaboration” when growing the hugely popular app Hatch, based in New Zealand. Hatch allows everyday New Zealanders to quickly and easily trade in the U.S. share market.
The beginning of the COVID pandemic spelled huge growth for Hatch and caused significant design challenges for the product. This growth meant that the app had to grow from a baby startup to one that could operate at scale - virtually overnight.
In navigating this challenge, Nat and Lulu coined the term radical collaboration, which aims to “dismantle organizational walls and supercharge what teams achieve”. Radical collaboration has six key pillars, which they discuss alongside their experience at Hatch.
Pillar #1: When you live and breathe your North star
Listening to hundreds of their customers’ stories, combined with their own personal experiences with money, compelled Lulu and Nat to change how their users view money. And so, “Grow the wealth of New Zealanders” became a powerful mission statement, or North Star, for Hatch. The mission was to give people the confidence and the ability to live their own lives with financial freedom and control. Nat and Lulu express the importance of truly believing in the mission of your product, and how this can become a guiding light for any team.
Pillar #2: When you trust each other so much, you’re happy to give up control
As Hatch grew rapidly, trusting each other became more and more important. Nat and Lulu state that sometimes you need to take a step back and stop fueling growth for growth’s sake. It was at this point that Nat asked Lulu to join the team, and Nat’s first request was for Lulu to be super critical about the product design to date - no feedback was out of bounds. Letting go, feeling uncomfortable, and trusting your team can be difficult, but sometimes it’s what you need in order to drag yourself out of status quo design. This resulted in a brief hiatus from frantic delivery to take stock and reprioritize what was important - something that can be difficult without heavy doses of trust!
Pillar #3: When everyone wears all the hats
During their journey, the team at Hatch heard lots of stories from their users. Many of these stories were heard during “Hatcheversery Calls”, where team members would call users on their sign-up anniversary to chat about their experience with the app. Some of these calls were inspiring, insightful, and heartwarming.
Everyone at Hatch made these calls – designers, writers, customer support, engineers, and even the CEO. Speaking to strangers in this way was a challenge for some, especially since it was common to field technical questions about the business. Nevertheless, asking staff to wear many hats like this turned the entire team into researchers and analysts. By forcing ourselves and our team outside of our comfort zone, we forced each other to see the whole picture of the business, not just our own little piece.
Pillar #4: When you do what’s right, not what’s glam
In an increasingly competitive industry, designers and developers are often tempted to consistently deliver new and exciting features. In response to rapid growth, rather than adding more features to the app, Lulu and Nat made a conscious effort to really listen to their customers to understand what problems they needed solving.
As it turned out, filing overseas tax returns was a significant and common problem for their customers - it was difficult and expensive. So, the team at Hatch devised a tax solution. This solution was developed by the entire team, with almost no tax specialists involved until the very end! This process was far from glamorous and it often fell outside of standard job descriptions. However, the team eventually succeeded in simplifying a notoriously difficult process and saved their customers a massive headache.
Pillar #5: When you own the outcome, not your output.
Over time Hatch’s user base changed from being primarily confident, seasoned investors, to being first-time investors. This new user group was typically scared of investing and often felt that it was only a thing wealthy people did.
At this point, Hatch felt it was necessary to take a step back from delivering updates to take stock of their new position. This meant deeply understanding their customers’ journey from signing up, to making their first trade. Once this was intimately understood, the team delivered a comprehensive onboarding process which increased the sign-up conversion rate by 10%!
Pillar #6: When you’re relentlessly committed to making it work
Nat and Lulu describe a moment when Allbirds wanted to work with Hatch to allow ordinary New Zealanders to be involved in their IPO launch on the New York stock exchange. Again, this task faced numerous tax and trade law challenges, and offering the service seemed like yet another insurmountable task. The team at Hatch nearly gave up several times during this project, but everyone was determined to get this feature across the line – and they did. As a result, New Zealanders were some of the few regular investors from outside the U.S that were able to take part in Albirds IPO.
Why it matters 💥
Over four years, Hatch grew to 180,000 users who collectively invested over $1bn. Nat and Lulu’s success underscores the critical role of teamwork and collaboration in achieving exceptional user experiences. Product teams should remember that in the rapidly evolving tech industry, it's not just about delivering the latest features; it's about fostering a positive and supportive team culture that buys into the bigger picture.
The Hatch team grew to be more than team members and technical experts. They grew in confidence and appreciated every moving part of the business. Product teams can draw inspiration from Hatch's journey, where designers, writers, engineers, and even the CEO actively engaged with users, challenged traditional design decisions, and prioritized solving actual user problems. This approach led to better, more user-centric outcomes and a deep understanding of the end-to-end user experience.
Most importantly, through the good times and tough, the team grew to trust each other. The mission weaved its way through each member of the team, which ultimately manifested in positive outcomes for the user and the business.
Nat and Lulu’s concept of radical collaboration led to several positive outcomes for Hatch:
It changed the way they did business. Information was no longer held in the minds of a few individuals – instead, it was shared. People were able to step into other people's roles seamlessly.
Hatch achieved better results faster by focusing on the end-to-end experience of the app, rather than by adding successive features.
The team became more nimble – potential design/development issues were anticipated earlier because everyone knew what the downstream impacts of a decision would be.
Over the next week, Lulu and Nat encourage designers and researchers to get outside of their comfort zone and:
Visit customer support team
Pick up the phone and call a customer
Challenge status quo design decisions. Ask, does this thing solve an end-user problem?
Simply put, ResearchOps is about making sure your research operations are robust, thought through and managed.
Having systems and processes around your UX research and your team keep everyone (and everything) organized. Making user research projects quicker to get started and more streamlined to run. And robust sharing, socializing, and knowledge storage means that everyone can understand the research insights and findings and put these to use - across the organization. And even better, find these when they need them.
Using the same tools across the team allows the research team to learn from each other, and previous research projects and be able to compare apples with apples, with everyone included. Bringing the team together across tools, research and results.
We go into more detail in our ebook ResearchOps Checklist about exactly what you can do to make sure your research team is running at its best. Let’s take a quick look at 5 way to ensure you have the grounding for a successful ResearchOps team.
1. Knowledge management 📚
What do you do with all of the insights and findings of a user research project? How do you store them, how do you manage the insights, and how do you share and socialize?
Having processes in place that manage this knowledge is important to the longevity of your research. From filing to sharing across platforms, it all needs to be standardized so everyone can search, find and share.
2. Guidelines and process templates 📝
Providing a framework for how to run research projects is are important. Building on the knowledge base from previous research can improve research efficiencies and cut down on groundwork and administration. Making research projects quicker and more streamlined to get underway.
3. Governance 🏛
User research is all about people, real people. It is incredibly important that any research be legal, safe, and ethical. Having effective governance covered is vital.
4. Tool stack 🛠
Every research team needs a ‘toolbox’ that they can use whenever they need to run card sorts, tree tests, usability tests, user interviews, and more. But which software and tools to use?
Making sure that the team is using the same tools also helps with future research projects, learning from previous projects, and ensuring that the information is owned and run by the organization (rather than whichever individuals prefer). Reduce logins and password shares, and improve security with organization-wide tools and platforms.
5. Recruitment 👱🏻👩👩🏻👧🏽👧🏾
Key to great UX research is the ability to recruit quality participants - fast! Having strong processes in place for screening, scheduling, sampling, incentivizing, and managing participants needs to be top of the list when organizing the team.
Wrap Up 💥
Each of these ResearchOps processes are not independent of the other. And neither do they flow from one to the other. They are part of a total wrap around for the research team, creating processes, systems and tools that are built to serve the team. Allowing them to focus on the job of doing great research and generating insights and findings that develop the very best user experience.
Afterall, we are creating user experiences that keep our users engaged and coming back. Why not look at the teams user experience and make the most of that. Freeing time and space to socialize and share the findings with the organization.
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.
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:
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
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.
Clara’s background
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.
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.
What role should artificial intelligence play in UX design process? 🤔
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.
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.
Access for all 🦾
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.
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.
Research and testing 🔬
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:
Efficiency. Not only does AI expedite the problem solving process, it can also help efficiently identify problems.
Innovation. Generative AI can innovate on its own, developing ideas that designers themselves may not have thought of.
The design partnership 🤝🏽
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.
Why it matters 💡
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.
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:
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
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.
