Quamnet - Foundational Stock Data Experience
Role
UIUX Designer
Timeline
4 Months
Impact
Established the foundational user experience for Quamnet's core stock analysis product
about.
This project involved designing the first-ever stock detail page for Quamnet, a financial information platform. The challenge was to transform complex, raw financial data feeds into a coherent, intuitive, and actionable interface for a diverse user base of investors. My role encompassed the entire UX process, from initial user research and information architecture to final UI and data visualization design for both equity data and IPO tracking modules.
goal.
📈 Create Intuitive Information Architecture
To logically structure over 30 discrete data points into a scannable hierarchy that aligns with users' mental models, reducing cognitive load and time-to-insight.
🗂️ Prioritize Actionable Data Visualization
To move beyond simple tables and employ clear visualizations that allow for at-a-glance comprehension of market sentiment and performance.
🔍 Build a Foundation for Scalability
To design a flexible system that could not only accommodate current data needs but also scale to include new features like advanced charting, news integration, and personalization in the future.
user journey map.
How might we...
card sorting.
To understand how users mentally categorize financial data points, I conducted an unmoderated, open card sort with 5 daily trading users. Participants were given 28 cards, each labeled with a financial data point and asked to group them in a way that made sense to them and then name those groups. This method was chosen to uncover users' innate mental models without the bias of an existing design.
card sorting result.
The analysis revealed strong consensus, leading to four primary user-defined categories:
Live Trading & Price: Containing real-time data like current price, bid/ask, and daily highs/lows.
Company Fundamentals & Value: Grouping key valuation metrics like P/E ratio, dividend yield, and 52-week high/low.
Charts & Performance: Encompassing all price charts and the volatility metric (Beta).
Market Sentiment & Activity: For advanced data like bull/bear and buyer/seller ratios.
This user-generated taxonomy directly informed the grouped card layout of the final design.Naming Insights: The names participants used were very clear or action-oriented. This influenced my final section headers to be straightforward and scannable.
design features.
💯 User-Validated Grouping
The page is organized into clear, distinct sections based directly on the card sort results, enabling rapid scanning and navigation.
👀 At-a-Glance Visualizations
Key sentiment data is presented using progress bars and pie charts instead of dense tables, allowing users to understand market momentum intuitively and instantly.
😎 Hierarchical Information Disclosure
The design employs a strategic visual hierarchy, presenting the most critical information, eg. Price, Change, Key Stats first, with more advanced data, eg.Ratios, Detailed Metrics available further down the page, catering to both novice and expert users.
😎 Hierarchical Information Disclosure
The page is organized into clear, distinct sections based directly on the card sort results, enabling rapid scanning and navigation.
goal.
📈 Create Intuitive Information Architecture
To logically structure over 30 discrete data points into a scannable hierarchy that aligns with users' mental models, reducing cognitive load and time-to-insight.
🗂️ Prioritize Actionable Data Visualization
To move beyond simple tables and employ clear visualizations that allow for at-a-glance comprehension of market sentiment and performance.
🔍 Build a Foundation for Scalability
To design a flexible system that could not only accommodate current data needs but also scale to include new features like advanced charting, news integration, and personalization in the future.
📈 Create Intuitive Information Architecture
To logically structure over 30 discrete data points into a scannable hierarchy that aligns with users' mental models, reducing cognitive load and time-to-insight.
🗂️ Prioritize Actionable Data Visualization
To move beyond simple tables and employ clear visualizations that allow for at-a-glance comprehension of market sentiment and performance.
🔍 Build a Foundation for Scalability
To design a flexible system that could not only accommodate current data needs but also scale to include new features like advanced charting, news integration, and personalization in the future.
user journey map.
How might we...
goal.
📈 Create Intuitive Information Architecture
To logically structure over 30 discrete data points into a scannable hierarchy that aligns with users' mental models, reducing cognitive load and time-to-insight.
🗂️ Prioritize Actionable Data Visualization
To move beyond simple tables and employ clear visualizations that allow for at-a-glance comprehension of market sentiment and performance.
🔍 Build a Foundation for Scalability
To design a flexible system that could not only accommodate current data needs but also scale to include new features like advanced charting, news integration, and personalization in the future.
user journey map.
How might we...
card sorting.
To understand how users mentally categorize financial data points, I conducted an unmoderated, open card sort with 5 daily trading users. Participants were given 28 cards, each labeled with a financial data point and asked to group them in a way that made sense to them and then name those groups. This method was chosen to uncover users' innate mental models without the bias of an existing design.
card sorting result.
The analysis revealed strong consensus, leading to four primary user-defined categories:
Live Trading & Price: Containing real-time data like current price, bid/ask, and daily highs/lows.
Company Fundamentals & Value: Grouping key valuation metrics like P/E ratio, dividend yield, and 52-week high/low.
Charts & Performance: Encompassing all price charts and the volatility metric (Beta).
Market Sentiment & Activity: For advanced data like bull/bear and buyer/seller ratios.
This user-generated taxonomy directly informed the grouped card layout of the final design.Naming Insights: The names participants used were very clear or action-oriented. This influenced my final section headers to be straightforward and scannable.
design features.
💯 User-Validated Grouping
The page is organized into clear, distinct sections based directly on the card sort results, enabling rapid scanning and navigation.
👀 At-a-Glance Visualizations
Key sentiment data is presented using progress bars and pie charts instead of dense tables, allowing users to understand market momentum intuitively and instantly.
😎 Hierarchical Information Disclosure
The page is organized into clear, distinct sections based directly on the card sort results, enabling rapid scanning and navigation.
The design employs a strategic visual hierarchy, presenting the most critical information, eg. Price, Change, Key Stats first, with more advanced data, eg.Ratios, Detailed Metrics available further down the page, catering to both novice and expert users.