In May 2021, I took a service and UX re-design consultancy project for a small but growing cryptocurrency exchange with a US MSB license. After a series of co-design workshops with the team aimed at understanding the ecosystem and business goals, I embarked on a user research journey aimed at profiling the existing user base and developing a deep understanding of their goals, pain points and motivations.

As the exchange platform already had data from the CRM system and product analytics platform, I decided to combine quantitative and qualitative analysis methods to create data-driven user personas.

Step 1. Analytics and Clustering

I started by carefully analyzing the data. Working hand-in-hand with data scientists, I combined CRM and product analytics databases, did an exploratory analysis and used K-Means clustering algorithm to come up with 3 distinct user segments.

K-Means clustering is an unsupervised machine learning algorithm that divides the given data into the given number of clusters (the “K” is the given number of predefined clusters, that need to be created). The algorithm takes raw unlabelled data as an input and divides the dataset into clusters. The process is repeated until the best clusters are found. In our case, the most important factors considered were the age bucket, trading volume, trading value, frequency of trading, platforms used.

Some of the interesting insights included the following:

• Male traders aged 20–35 comprised the biggest market sector(~65%) with the highest trading volume.
• While trading volume was higher among traders aged under 40, trading value was higher among traders over 40.
• The use of mobile platforms was more common among female users under 35, while desktop was particularly popular among male users over 40.

Step 2: Contextual Inquiries and Desk Research

Using the explorative data analysis insights as a guide, enriching and validating them with some statistics from the web and previous research, I moved to the qualitative part of the research.

As the project had two objectives: to improve the user experience and to come up with service innovation solutions, I chose contextual inquiries as the primary method for qualitative research. Contextual inquiry is a semi-structured interview method to obtain information about the context of use, where users are first asked a set of questions about their preferences, pain points, motivations, behaviors, context of use and then questioned/observed while interacting with the product, system, or service.

Using the telegram group of the exchange and of one direct competitor, I recruited 28–35 participants with characteristics corresponding to each cluster identified in the first phase (overall, 94 participants).

The contextual inquiry goals were to:

• Understand the goals and motivations of crypto traders from different clusters.
• Understand the pain points that crypto traders face with blockchain products and services.
• Test and understand the usability challenges of the existing platform.
• Understand the media preferences of different user clusters

Some of the key insights gained through the inquiries were:

• Low crypto adoption rate and luck of integrations between different crypto products and services were the biggest challenges faced by users from all clusters.
• The motivations and personalities of users from different clusters varied a lot, however, users from all clusters had growth mindset, passion for technology and open innovation, and certain dissatisfaction with the opportunities provided by the existing monetary system.
• With the existing platforms, users face a trade-off between relatively streamlined user experience and favorable transaction fees.

The specific insights for each of the three market segments were synthesized in separate personas presented below.

Persona #1: Crypto Enthusiast Daniel

The first persona, Daniel represented the biggest market segment of tech savvy, ideology-driven investors. What was particularly interesting about Daniel’s segment was that this people were both the biggest believers and the biggest sceptics when it came to the crypto world. Being technically savvy, these people were less demanding in terms of UX but more demanding in terms of functionalities and well-connected ecosystem.

Crypto Enthusiast Persona

Persona # 2: Ambitious Newbie Charlotte

The second persona, Charlotte, was interesting as she represented not the biggest but the fastest growing sector of the market. High adoption rates among this sector could be crucial for mass adoption of cryptocurrencies. From the UX perspective, people, represented by Charlotte know how to differentiate between good and bad design and are more demanding from the products/services that they use. Although users in this sector, do not spend a lot, they are more open to trying new products and services and feel comfortable using mobile services.

Ambitious Newbie Persona

Persona # 3: Skilled Experimentator Richard

The third persona, Richard, was interesting as even though he did not represent a big market segment but he represented a segment with high trading value, thus could be an interesting target for the exchange. In addition, from the UX perspective, Richard represented a sector that had a distinct preference of desktop application over mobile and luck of technological know-how.

Skilled Experimentator Persona