Liquidnet (via CMU)
Feb. - Aug. 2019 (7 months)
PM: Emily Gong
Researcher: June Liu, Yingli Sieh
Designer: Nina Yang, Qian Wang
I designed half of the features as one of the two main designers on the team. I also coded the deliverable website.
I was part of most research activities, led by our researchers.
Liquidnet is a FinTech company that provides a dark-pool trading platform for institutional traders and asset managers.
HMW design an alert system that brings traders onto Liquidnet effectively?
Traders' digital and physical work space is extremely busy. 6 monitors is not uncommon. Liquidnet wants its alerting system to draw traders' attention effectively on order updates and new trading opportunities. This way traders don't miss out opportunities on Liquidnet. The goal of this project is to explore best practices for designing this alerting system.
Alert design playbook
After thorough research, we concluded a set of design guidelines for Liquidnet. We composed them into a playbook website along with supporting user research, academic research and prototypes that demos the guidelines.
Alert design proposal
We also developed a set of features to:
1. Get trader's attention
2. Help trader take action on Liquidnet
3. Maintain the engagement even when trader is not trading
Jump to final design
User Research
Secondary Research
Learn about the domain and speak users' language
To quickly get familiar with the domain, we utilized a wide range of resources. We did gorilla research with friends at finance school, watched videos/documentaries/movies about trading and trader, and played games that simulates the trading experience. Through these activities, we quickly learned lots of jargon, which helped us greatly in communicating with interviewees later.
Learn about competitor products and design styles
Through learning about competitors and other domain-specific design paradigms, we realized that in general, the design styles are more traditional, a little dated, and data-heavy. Although later we found out that many users actually prefer a more modern style.
Learn about Liquidnet: alerts are to increase adoption of new features
Through talking with subject matter experts at Liquidnet, we learned that Liquidnet is building more and more analytics features, but not a lot of users discovered and make use of them. That's also one of the main reasons there is an alert system. Through feature mapping and heuristic evaluations, we realized a lot of those features are buried deep under a complex structure, which could be part of the reason.
Primary Research
20 interviews with stakeholders and proxy users
We did multiple rounds of interview with stakeholders and in-house traders to understand traders' work environment and journey. During the interviews, we brought pre-made artifacts for them to iterate on so that we won't get the same information repeatedly from every person.
Shadowing in-house traders
We observed the trading desk in our client’s company during the market opening, mid-day, and market closing time. While observing, we used the AEIOU framework to capture activities (A), events (E), interactions (I), objects (O), and users (U). We discovered several pain points that was not revealed in our interviews.
Insight 1
Everything is about efficiency
• Traders need to consume information efficiently among 6 screens and a fast-pace schedule
• Traders need to collaborate with colleagues efficiently
• "If you can make building report easier, I'll be VERY happy."
Insight 2
The key to be successful is to remain rational in failures, and positive reinforcement helps maintain a healthy and rational trading mindsets
To understand the mindset and emotions of traders, we conducted contextual interviews with online poker players, because online poker is a very similar domain to trading, and is even often used to train young traders. We reviewed our observations on a matrix, which gave us inspiration for potential solutions to the emotional problems of traders. One major insight we got is “Positive reinforcement helps maintain a healthy and rational trading mindset.”
Design Research

After having a holistic understanding of the domain, users, and product, we start to focus more on the alert system design. This section talks about how we generated a set of design guidelines based on analogous domain research and evaluative research.

Analogous Domain Research
We learned about general design principles for alerts and best practices.
We broke down our research question in to 3: how to attracting attention? how to initiative action? and how to gain user trust on the system recommendation? We researched in the academic/design field, and also looked widely into different domains for inspiration (including retail, advertisement, emergencies, gaming, notifications, autonomous driving, etc.),
Research through design
Applied guidelines and build prototypes for Liquidnet
And tested at a simulated trading desk with traders
We setup a simulated trading desk and tested different concepts. We learned a lot expected/unexpected things, like "Animation isn't as effective as we thought in terms of grabbing attention", etc.
Synthesize and conclude design guidelines with feedback grid
For synthesizing, we used the feedback grid method and modified the 4th quadrant to better fit our research. Our feedback grid has four quadrants: “what worked”, “what should be changed”, “new ideas”, and “general behaviors”. This helped us quickly generate design guidelines from each quadrant. For instance, from quadrant 1 and 2, we concluded DOs and DON’Ts, from quadrant 3, we extracted design limits and preferences.
Final Design
Get User Attention
1. Large areas of salient color
After testing different combinations of color, animation, and sound at a simulated trading desk, we discovered that salient colors is the most effective to attract attention on a trader desk, where many parts of the screen might be changing.
Try to focus on the black tables when you play the video, and see if you noticed the alerts
Before applying color
Before applying color
2. Multiple levels of urgency prevent "alert fatigue" and "cognitive blindness".
3. Smaller window, larger impact
Today, many users don't keep Liquidnet visible on their desktop all the time. A minimized view has a higher chance to be kept visible all the time. This way:
  • Users won't miss out important information and has a higher chance to trade on Liquidnet.
  • User won't feel forced to handle every single alert.
  • Eventually, more engagement with Liquidnet can win us more screen property.
Guide user action
1. Feedforward: different color for different alert types
This way, before reading any text on the alert, user can know what is happening and whether they want to switch focus.
2. Progressive disclosure
After getting intrigued to read an alert, traders hardly want to take an action immediately because their decision-making process needs lots of evidence. So we designed a progressive disclosure way to show more evidence and details of the alert when the user expanded it, and provide an action button after that.
3. Grouping
The frequency of the alerts can be high based on users blotter size. Grouped alerts can help users maintain a more manageable alert stream, and easier for user to decide what action to take first.
1. Tweak alert settings more easily
A trader's need for alert can change frequently. Today, Liquidnet has an alert setting page, but users hardly use them. We made two proposals to make settings more easily accessible. One idea is to allow user change settings with a right click when he receives an alert. Another idea is to suggest settings based on user behavior.
Change settings with right click
Suggest settings based on user action
2. Customized alerts
Through user research, we learned that self-defined alert is needed. Some traders prefer to scroll and click when setting, while others prefer to type as if in a command line tool. So both methods are supported in our design.
More engagement
We also identified several untended pain points that can get more engagement from traders.
1. Share alerts with others
When traders need to take a short leave, s/he would want a colleague to get certain alerts.
2. Quickly compile a report
Compile a report is a task traders do everyday repeatedly. Traders expressed strong desire to make it easier during our interviews.
3. Search for relevant information
Traders often need to research on one stock. Provide a way to quickly search for relevant alerts, analytics in Liquidnet was a strong desire.
Things we did correctly 😉
Things we can improve 🤔