Thinking Like our Clients: UX Research at XTB

In the dynamic world of financial trading, where every second and every click can determine a user's financial future, designing intuitive and secure solutions is crucial. This is an environment where an error in the interface can mean not only frustration, but also real financial loss. This creates a huge responsibility, which I feel strongly as a Head of UX Research at XTB, both as an expert and as a human being. 

I believe that behind every transaction there is a person with their own emotions, expectations, and challenges. This is especially true in the area of personal finance and financial future. That is why I emphasize so strongly in my teams the need to get to know them, understand them, and help them become better investors. To support them in making the right decisions and ensuring the security of their portfolios.

User research is the foundation of our business strategy and the key to understanding the complexity of human nature in the context of investing. In this article, I will talk about how we conduct UX research at XTB, sharing our approach, the tools we use, and best practices. If you are wondering how to conduct user research in the financial sector, looking for practical tips to help you better understand your potential clients, or simply want to get inspired, this article is for you!

What Does UX Research Look Like in Finance?

Before we dive into the details, it is worth explaining what UX Research is. In the simplest terms, it is the systematic study of users in order to understand their needs, behaviors, motivations, and problems related to a product or service. In the context of finance, where the stakes are high, UX Research is not only about ensuring the aesthetics or simplicity of the interface, but above all about the financial security of the user, building trust, and supporting them in making key investment decisions. My goal is to discover what a “trader” really thinks, feels, and needs so that we can create solutions for them that provide real value but also simply bring us business. 

Every Aspect Matters

Financial trading requires precision and trust, but above all, a deep understanding of human psychology. In the world of finance, psychology and decision-making dynamics are of great importance to the user. This translates into the need to examine many aspects of the user's contact with the product and look at its role holistically. This is exactly how I approach research. From understanding the user's environment and context, to their complex decisions, to everything that is happening around them. Why?

Because this is the only way to make key product decisions—based on data. Whether it's simplifying the order placement process, optimizing the market analysis interface, the deposit and withdrawal screen, or finally trying to understand the user's emotions. Because a “trader” who gets lost on a complex platform or whom we “don't understand” becomes not only a competitive “lead,” but a person whom we have not supported on their way to their investment goals or simply whom we have not given real value. And that hurts. And I want to have an impact on that.

That is why, in every research project, I use a start-up approach, which involves looking for answers to the key question:

 “How will this study and its results help our clients, and what will be the benefits for users and the business (financial or image-related)?”

In my opinion, this is a key question that demonstrates research and product maturity. Research cannot be just a source of knowledge and data about users, but should also translate into an increase in business indicators, understood as financial or image indicators for the organization. To put it simply, we must conduct research that influences product usability, helps solve internal problems or achieve organizational goals, and simply pays off for the organization. After all, the goal of every company is its development, financial growth, competitiveness, and sustainability. The research we do at XTB covers every stage of the user's journey combined with an understanding of the business. Even those moments that begin long before the decision to install our application. This is where our product solutions, business scale, and success in many markets come from.  

Different Tools, One Goal: Understanding the User

At XTB, I use an approach that combines quantitative analytics with qualitative research. This combination allows us not only to know “what” users are doing, but above all to understand “why” they make certain decisions. To this end, I use a range of research tools that help us get closer to the user and understand them better, such as: 

Individual interviews

Individual interviews are an important part of our tools. We conduct hundreds of interviews each year with traders at every stage of their contact with our products and services—from their first login to advanced investment strategies. These interviews reveal not only superficial preferences, but also the deep motivations, fears, and aspirations of our clients. We learn about success stories, but also about failures that shape their approach to future investments. This allows me to test both existing products and new ones we are implementing, as well as to respond better to changes.

Key tips on what to look for during individual interviews:

• Define your goal: always clearly define what you want to achieve through the interview and what results you expect, what the business goals are, and what benefits or problems may arise.
• Ask open-ended questions: instead of “yes/no” questions, ask for more detail, e.g., “Tell me more about...,” “What prompted you to...,” “How did you feel when...?”. What made you...,“ ”How did you feel when...?".
• Listen carefully and be flexible: sometimes the best conclusions come when we allow the conversation to flow beyond the set scenario. Be ready to follow up on interesting topics.
• Document: record conversations (with the respondent's consent) and take detailed notes. This will facilitate later analysis.
• Analyze not only words, but also emotions: facial expressions, tone of voice, hesitations – all of these provide valuable information.

Product Analytics – the Voice of Behavioral Data

Product analytics is very important to us. We track user behavior, trying to understand the logic behind their decisions, every moment of hesitation. We analyze not only what works, but above all, where users stop, return, or give up. This data tells the truth about the user experience, often revealing problems that are invisible during traditional testing.

Useful tools and practices in product analytics:

• Behavioral analytics tools: we use tools such as Hotjar, Google Analytics, UXCAM, and Survicate, which allow us to track user paths, exit points, heat maps, and session recordings.
• Defining key metrics: we define metrics such as the conversion rate in the onboarding process, time spent on a specific function, and the number of transactions completed.
• User segmentation: we analyze data broken down into different user groups (e.g., new, advanced, mobile) to discover specific patterns.
• A/B testing: where possible, we conduct A/B testing to empirically verify which changes to the interface or process yield the best results.
• Conversion funnels: we observe funnels for key processes (e.g., registration, deposit, order placement) to visualize where users encounter problems or how to help them make decisions that are beneficial to us.

Ethnography: Stepping Into the User’s World

In the era of AI and increasingly frequent generative conclusions, observations, and recommendations, I believe more strongly than ever in the power of classic ethnography and close observation of users. This contact reveals many hidden needs and contexts that can form the basis for creating new products and business value. As part of ethnographic research, I focus on observing our users in their natural environment (e.g., at home, in the office) to see how they invest in their daily lives, what their rituals are, what tools they use, and how they manage their emotions in order to look for the undiscovered.

And here it is worth enlisting the help of colleagues. 

Employee Survey - Internal Insight into the Ecosystem

In order to understand the entire trading ecosystem and design solutions that support all participants in the process, we involve XTB employees in our research – analysts, brokers, and support teams. Our users are also our team, which creates processes, and these need to be researched in order to optimize them for even better use. For example, we recently studied how our Sales team serves customers live, gathering hundreds of valuable observations and even more insights and conclusions that can help improve their valuable work. 

Why is it worth starting ethnography with your own teams?

• Interviews with internal experts: talk to people who have daily contact with clients (e.g., customer service, advisors) to learn their perspective on the most common user problems. This will give you a chance to understand the problem well and prepare for research. 
• Observation of internal processes: understanding how internal processes work (e.g., account verification, ticket handling) allows you to identify points of friction that may affect the customer experience. It is worth seeing this live. 
• Mapping the employee journey: creating a map of the employee journey, analogous to the customer journey, helps visualize their experiences and identify areas for improvement.
• Team workshops: organize workshops with different teams to jointly identify problems and generate solutions that will optimize both internal work and the customer experience.

Close cooperation within XTB: Atomic Research in Practice

At XTB, research is part of the UCD (User-Centered Design) process. I do not isolate production teams from data and opportunities to gain new insights. In fact, I encourage them to collect data or come up with new research areas myself. We want this to be part of our DNA, which is why, as a research team, we work closely with product managers to define research strategies and product development, with designers to create interfaces, with the business to define user needs, and with compliance teams—because legal regulations in fintech are just as important as UX.

The result of the research is not just a report and not just a classic transfer of results. We are launching an initiative of joint “cross-team” workshops in the spirit of Atomic Research, during which there is an opportunity to clash concepts, co-create solutions, and make real product decisions. We support teams so that they have constant access to research, including in modern forms. For example, we have created our own AI Research Assistant, with whom you can “talk about research.” Because the key to a product's success is for every team member to create solutions based on data and research. 

How to prepare and conduct an Atomic Research workshop?

Atomic Research is a methodology that helps structure research results into small, atomic particles (observations), which we then combine into larger conclusions, then insights, and finally specific recommendations. This allows us to create a universal knowledge base about users and use it in future projects. Here's how I approach it:

• Aggregation of research data: before we sit down to the workshop, we collect all the raw data from the research conducted - interview transcripts, session recordings, analytical data, observation notes. It is important that this data is available to all workshop participants.
• Identification of observations: we determine the scale of the problems and classify the observations as negative, positive, neutral, but also those that offer an opportunity to create something innovative. 
• Formulating insights: we describe what a deeper understanding of the observation means in the form of a conclusion that results from this behavior, so that the product team clearly understands not only what the problem is, but also what consequences it may have. 
• Generating recommendations and experiments: based on insights, we jointly generate recommendations—specific ideas for solutions or improvements. These could be: “Move the language change button to a visible place in the header” or “Add an introductory tutorial to the initial settings.” In the spirit of Atomic Research, each recommendation can become the basis for an experiment that we will verify with data.
• Decision-making and planning: at the end of the workshop, the team decides which recommendations are a priority and are included in the product backlog. This is the moment when research translates into concrete actions.

Atomic Research allows us to build a shared, easily accessible knowledge base that is alive and evolves with each new study. Most importantly, it engages the entire product team in the research process, increasing awareness of user needs and building a shared understanding of the issues.

AI-powered Research: New Horizons in UX Research

At XTB Research Ops, we are working intensively on implementing artificial intelligence in research automation processes. AI already helps us in many product data analysis processes and operational tasks, such as creating automatic transcripts, summaries, and simple recommendations (the aforementioned internal AI assistant). I see real opportunities in the changing world of UX research in the context of AI—many benefits, but also barriers to implementing new tools. I am testing and observing their effects, e.g., in the context of creating recommendations based on synthetic personas (Synthetic Users), digital twins, or conducting automatic interviews by artificial moderators (Outset, Versive). These areas are interesting for me to analyze, but not all of them are ready to deliver the expected results. This is a topic for another, very interesting article. However, we certainly want to be pioneers in the implementation of AI-driven research solutions.

I remember, though, that technology is only a tool. People are still at the center of our research.

What Lies Ahead?

There are many interesting projects on the horizon that aim to comprehensively map the daily lives of traders. We want to understand not only their behavior during trading sessions, but also the full context - how investing affects their family and professional relationships, how it shapes their emotions and life decisions. I believe this will allow us to discover ways to support traders that go beyond traditional financial products.

I see the growing importance of personalization, but also the critical need to maintain user control over the automation of their lives. This is evidenced by numerous studies and trends that point to the growing importance of a hybrid model of financial customer service. This is an extremely interesting area to explore, one that will definitely define our research roadmap for the coming years.

In a nutshell. Our vision for the future is trade that is more technologically intelligent, but still deeply rooted in the human context and in a healthy, sustainable approach.

Research is the Best Investment... in Relationships

I believe that the best UX is not about working with abstract personas, but about solving and understanding the real and authentic needs and emotions of people. And, of course, this cannot be done without user research.

That's why we do so much research - we want our company to be not only a provider of financial tools, but also a partner who understands the everyday life of the user.

Every study, every interview, every analysis is an investment in long-term relationships with our clients. It's an approach that transforms transactional interactions into lasting partnerships based on trust and a real understanding of needs. We want to be like our clients. Because that changes everything!