Trading scans
Helping traders to trade more effectively
| Roles | Platform | Year |
|---|---|---|
| 2022 |
The problem
An online brokerage was developing a mobile app for trading and was considering integrating scans as a feature.
Scans are dynamically generated lists of trading instruments that meet specific criteria, used by traders to reduce the need for analysis to find trading opportunities.
Challenges facing traders:
- Widely varying levels of trading ability & knowledge
- Lack of confidence or over-confidence
- Not knowing what to trade or how to trade
- Not knowing the best time to trade a particular instrument
- Developing or evolving a trading strategy for maximum success
How could we help users to trade better through integrating scans?
Background:
- Worked within a team of UX designers; I had to ensure my solution integrated with others' designs.
- A design system was collaboratively being created to facilitate prototyping.
- There would be a “discovery” section in the app for personalised trading opportunities based on user behaviour and interests.
- Project completed within a 4-week timeframe.
The solution
I researched, designed and presented a concept for trading scans in the mobile app.
Benefits to beginner traders
- Simple onboarding: asks jargon-free questions to understand trading interests and style.
- Educational content: provides supplementary content to explain asset classes and trading styles.
- Customised scans feed: offers relevant trading opportunities, continuously refreshed for real-time updates.
- Flexible filters: allows easy adjustment of scan filters and learning more about assets.
- Direct trading: enables trading directly from the view.
- Alerts: users can set alerts for specific scan changes to manage positions effectively.
Benefits to experienced traders
- Immediate trading: skip the first-time experience and start trading right away.
- Personalised content: automatically tailored based on trading behaviour for improved efficiency.
- Quick market assessment: instrument detail screen shows included scans, eliminating the need to interpret charts.
- Easy navigation: pulldown navigator provides quick access to similar instruments within scans.
- Timely alerts: set alerts for scan changes to make timely trading decisions without micro-management.
Understanding the current users & their behaviour
I interviewed three SMEs with experience in trading and client support, and reviewed existing survey data and actual trades.
Survey data indicated that traders predominantly relied on statistical indicators and price movements rather than qualitative data like news and events.
I identified two target cohorts and mapped user journeys for each, focusing on different times or events in a trading day, such as the start of the day, pre-trade, and post-trade.
Experienced traders
- Know what to trade and how to trade
- Trade specific markets or instruments whose dynamics they understand
- Are event-driven (looking for trigger points to trade)
- Perform post-trade analysis to make decisions and improve
- May test their trading strategies against historical data
- Want to be more efficient in their trading
Beginner traders
- Don't know how to trade or what to trade
- Tend to browse for opportunities
- Tend to be driven by what is popular to trade
- Micro-manage their trades and would spend more time in the app
- Perform little analysis
- Want to learn and improve
From this I derived three primary goals for these two cohorts:
To see a variety of instruments that match their trading style
To know what market movements are affecting the instruments they trade and when, so they know when to trade
To understand what scans mean and how they can be used to trade
Understanding how competitors do it
Competitors included trading platforms such as TradingView, and standalone tools for traders such as Autochartist. I also looked at automation tools such as Capitalise.ai.
Notably not all brokers offer scans as an integrated feature (likely due to varying usage by traders).
Analysis also revealed the following insights:
- Sophisticated trading platforms offer powerful and user-friendly systems for signals and alerts.
- Existing scan implementations are often complex and jargon-heavy, making them less intuitive for beginners.
- Some standalone products offer scans but are not comprehensive trading platforms.
- Popular products for scans and alerts use conversational UI patterns, such as “If this, then that,” found in mass-market consumer products.
How to help users to trade better?
The research and discussions with SMEs and other designers led to the identification of key features for the new scans experience:
For each primary user goal:
I came up with ideas to address each primary user goal:
...I came up with ideas to address it:
To see a variety of instruments to trade that fit their trading style
Ideas to address it:
- Display scans by trading style, strategy or timeframe
- Personalise scans based on the user's trading style, strategy, or timeframe
- Provide popular/most useful scans for users who don't have a preferred trading style
- Allow quick navigation between individual instuments on a scan
To know what market movements are affecting the instruments they trade and when, so they know when to trade
Ideas to address it:
- Show when instruments trigger conditions to enter specific scans
- Configure alerts for specific instruments entering or exiting scans
To understand what scans mean and how they can be used to trade
Ideas to address it:
- Provide contextual help to explain what scans mean and how they can be used to trade
Iterating on the solution & integration
I was able to rapidly iterate on the ideas I chose to address the key goals, through information architecture, user flows and high fidelity wireframes using the existing design system and integrating with existing screens.
During iteration, I tested the designs with SMEs, stakeholders and other designers.
Resolving the design details
Though the design process, I resolved the details of my concept for scans:
Displaying scans
A discovery (home) screen had previously been designed but not finalised. This screen was intended to show what is happening in the markets through latest market news, market events and relevant instruments.
I added another tab for scans, which I named “hotlists” to avoid unfamiliar jargon. This would house all the scans and remain open between uses of the app, so traders that prefer can check it quickly.
I enabled the user to filter scans by preferred trading style. I also included a quick filter for asset class, as instruments of different asset classes are traded differently.
Personalisation & contextual help
It was always intended by the design team that the content on the discovery screen be automatically curated based on the user's behaviour and trades over time.
I designed an optional new first-time experience aimed to kick-start personalisation, so:
- All users can immediately start getting useful data to inform their trading
- Beginner traders can figure out how they want to trade by answering a few plain english questions
- Beginner traders can start learning how to trade through contextual help
Quick navigation between instruments
A quick navigation pane had previously been designed for the instrument detail screen, to allow users to quickly jump between instruments they are watching or trading.
As experienced traders prefer instruments similar to their past trades, I extended this navigation to allow quick jumps between related instruments within the same scans.
Showing when instruments trigger scan conditions
An instrument detail screen on which the user can see detailed information about a particular instrument and make trades had already been designed.
I adapted the design to add “hot tags” next to the chart — these tags indicate which scans the instrument currently belongs to. Users can understand at a glance what market conditions have been triggered which might influence them to trade.
Alerts
Extending the instrument detail screen, I designed an alert feature for users to automatically receive notifications when particular instruments enter or exit specific scans, allowing them to execute discretionary trades at the best possible time.
Next steps
Although further development was not possible within the given timeframe, the concept can be broken down into milestones which could potentially be implemented and released independently:
First-time experience: test the effectiveness of this feature for all user cohorts and assess its ability to personalise content.
Scans: test different user journeys to ensure understanding and decision-making.
Alerts: assess the impact on workflow and determine additional information needed for informed decision-making.