Background
Dune Analytics is a blockchain research tool that lets anyone query, extract, visualize and share data visualizations. Dune Analytics was created in March 2019 by two founders from Oslo, Norway: Fredrik Haga and Mats Olsen. While the company is only five years old, Dune is valued at over 1 Billion dollars.
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Problem
Statement
In this case, there are two types of personas we are dealing with. Stakeholders (data viewers) and wizards (data analysts) who are the ones querying data.
The data analysts were presented with the most problems so that is what I focussed on.
Dune refers to users who create dashboards and conduct data queries Wizards.
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How might we tailor the dune experience to Wizards* (data analysts) and consumers to better help them accomplish their goals?
Research Objectives
- Uncover usability issues
- Identify patterns in user behavior
- Deepen the understanding of the differences in needs between Wizards and consumers
- Understand the frequency of how often wizards query data
- Which blockchains are people most curious about?
- When do they use Dune?
- Where are they when they use dune?
- What do they wish to accomplish when using dune?
- What are their pain points with dune?
- What other products do they use alongside dune?
- Uncover the needs of wizards
- Uncover the needs of consumers
- What triggered them to start their Dune session?
- Identify the most delightful part of their user journey
- Identify the most frustrating part of their user journey
- How should their success be measured?
- Which features are most used?
Research Findings
Competitive Landscape and Market
Research Plan
Dune Analytics Pain Points
View the Full Discovery Research Presentation Here
Now lets look at what the stakeholders (data viewers) problems were with dune
Recommended actions based on research conducted
Its clear that analysts wanted improvements, but not an entire revamp of the UI they are used too. This made a lot of sense, the focus should be on the work they have to do and make their workflow easier. I did not want to move too many things around that will reduce analysts productivity.
Process, Wireframes, and Lighting Rounds
My main goal was to add components and a few new features that address the address the problems above while keeping development time minimal for the dune team. I designed for maximum impact with minimal developer resources considering dune is a small company that often relies on open-source contribution.
Usability Testing
Participants were recruited directly from the Dune discord and were vetted with the screener linked above. The wireframes were taken into high-fidelity and matched with the dune branding and then tested in figma.
Recommendations based on usability testing Research
Recommendatios
Based on interviews and testing the majority of the changes were positive,although for conclusive evidence we would need to AB test the current version versus this figma prototype to see what the majority of people prefer and how it affects their satisfaction with the product.
Overall, the findings were overwhelmingly positive, but I would want to test with a larger sample size of both non-technical stakeholders and data analysts, about 10 each. After that I would than Look to gain quantitative data through AB tests.
Overall, the findings were overwhelmingly positive, but I would want to test with a larger sample size of both non-technical stakeholders and data analysts, about 10 each. After that I would than Look to gain quantitative data through AB tests.
Next Steps
Conduct further interviews with this prototype to both personas, and conduct an
AB test.
AB test.
Research Ops
User interviews were conducted with a total of 8 people. 5 Data analysts (wizards) and 3 viewers. Many data analysts are also viewers on their on side projects they are working on, and in their free time outside of their main jobs. This means the number of pure viewers is not representative of all the data and insights gained about the viewing experience of dune as almost all the analysts interviewed contributed as well. The interview participants were sourced on Discord from the Dune analytics channel and Metrics DAO.
Demographics
1. People who work with data in any capacity on a daily basis in the crypto space. (Wizard Persona).
Potential roles in include: Data Analyst, Data scientist, Data engineer, Blockchain engineer.
2. People who make decisions based on data and view dashboards and various forms of data visualizations on a regular basis. (Data viewer / stakeholder persona).
Potential roles include: CEO, Founder, Product Manager, marketing teams, senior data professionals, and retail investors.
Potential roles in include: Data Analyst, Data scientist, Data engineer, Blockchain engineer.
2. People who make decisions based on data and view dashboards and various forms of data visualizations on a regular basis. (Data viewer / stakeholder persona).
Potential roles include: CEO, Founder, Product Manager, marketing teams, senior data professionals, and retail investors.
Conclusion
Participants were recruited directly from the Dune discord and were vetted with the screener linked above. The wireframes were taken into high-fidelity and matched with the dune branding and then tested in figma.
Background
Dune Analytics, founded in March 2019 by Fredrik Haga and Mats Olsen in Oslo, Norway, is a blockchain research tool valued at over $1 billion. It enables users to query, extract, visualize, and share data visualizations.
Problem Statement
he platform caters to two main personas: stakeholders (data viewers) and wizards (data analysts). The research focused primarily on the wizards, who are responsible for creating dashboards and conducting data queries to enhance their experience alongside that of the consumers.
Research Objectives
- Identify usability issues and patterns in user behavior.
- Understand the needs and frequency of data querying by wizards.
- Explore which blockchains interest users the most and their usage patterns with Dune.
- Uncover pain points, additional tool usage, triggers for starting a Dune session, and user journey highlights.
Findings
There's a clear distinction between the needs of wizards and consumers.
Key pain points and usage patterns were identified, including when and where users engage with Dune.
Key pain points and usage patterns were identified, including when and where users engage with Dune.
Recommended Actions: Improve the platform by adding components and features addressing identified issues without a complete UI overhaul, to avoid disrupting the wizards' workflow.
Usability Testing: Conducted with participants from the Dune Discord community, using high-fidelity wireframes aligned with Dune branding in Figma.
User Testing: Conducted through iterative sessions to refine the platform based on direct feedback, ensuring alignment with musicians' expectations.
Recommendations: Positive feedback on changes, suggesting the need for A/B testing to compare new designs with the current version for a broader user preference analysis.
Propose further testing with a larger sample size of both non-technical stakeholders and data analysts, followed by quantitative A/B testing.
Propose further testing with a larger sample size of both non-technical stakeholders and data analysts, followed by quantitative A/B testing.
Next Steps: Additional interviews with both user personas using the prototype will be conducted, followed by A/B testing to gather quantitative data.
Research Operations: Interviews were conducted with eight individuals: five data analysts (wizards) and three viewers, sourced from the Dune Analytics Discord channel and Metrics DAO.
Conclusion
The study underscores the importance of making targeted improvements to Dune Analytics that enhance usability for both wizards and stakeholders without overhauling the familiar UI. This approach aims to improve workflow efficiency for analysts while ensuring the platform remains accessible and valuable to all user types. Further research and A/B testing are recommended to validate the proposed changes and assess their impact on user satisfaction.
