BNY Mellon

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Case Study: Personalization Features

At BNY Mellon, our goal was to enhance user experience by adding new personalization features to the client interface. The initial hypothesis was that users would benefit from the ability to customize their menus, allowing them to pin frequently used actions for easy access. We believed this would provide a more efficient and tailored experience, reducing the time it takes for users to complete tasks. As the problem became apparent certain subsets of users were having to bounce back and forth between repeated actions, and the user knew what information they needed, but there wasn't an easy path for them.

Define the Problem

At BNY Mellon, our goal was to enhance user experience by adding new personalization features to our interface. The initial hypothesis was that users would benefit from the ability to customize their menus, allowing them to pin frequently used actions for easy access. We believed this would provide a more efficient and tailored experience, reducing the time it takes for users to complete tasks.

Research

We began by conducting user interviews and analyzing user behavior data to better understand how users navigated the existing interface. Through this research, we aimed to identify which personalization features would have the most impact. We looked at similar features in the market and considered how our users might differ in their needs due to the specific financial tasks they perform. We looked at other financial services as well as other platforms in media and productivity.

Ideation

Based on our research, we proposed two main ideas: a customizable menu and a list of recently used actions. The customizable menu would allow users to pin specific actions for quick access, while the recent items list would provide a history of recent actions.

Analysis & Planning

The research showed that while personalization options are valuable, many users prefer automated solutions that minimize the effort required to manage preferences. This led us to refine our idea: instead of a fully customizable menu, users needed something more automatic or specifically a list of recently used actions that would persist across sessions. Our planning pivoted from focusing solely on customization to creating a more intuitive, history-driven feature that could provide easy access to recent actions.

Design

Once we identified the core problem, we designed several prototypes, including the initial "pinned actions" menu concept and the alternative "recent items" list. We aimed to make both options user-friendly, with minimal clicks to access key features. The recent items list was designed to be persistent across sessions, so users could easily find their previous actions without manual input, and the pinned actions menu was designed to be persistent across sessions and accounts. This allowed a user to indicate to the system what actions they wanted to be available to them.

Prototyping

I helped lead the prototyping phase, where we developed multiple [design variations](https://uxdesign.cc/whats-next-on-figma-s-mind-redesigning-design-systems-0f287aaabc14) to test the best solution for our users. We used low-fidelity wireframes to visualize the different flows and progressively moved to high-fidelity interactive prototypes. These prototypes were integrated into Maze, [a tool we used to simulate the user experience and capture data](https://maze.co/blog/empathy-mapping/). With Maze, we could track user interactions and measure the effectiveness of each design option. Going into Figma and using our user personas, we set forth making the various paths.

Testing

We conducted A/B testing to compare the performance of the pinned actions menu versus the recent items list. Users were presented with a modal survey after completing their primary tasks, inviting them to participate in the study. The survey gathered free-text/mood feedback on usability, efficiency, and preferences. Maze allowed us to measure user interactions directly and analyze which design led to faster task completion.

The control for the test was the existing menu and how they got to actions their persona would use. The test was split into three groups:

• Group A: The existing menu, where users could navigate to actions using the menu.
• Group B: The recent items list, where users could access recent actions without navigating through menus.
• Group C: The recent items list, but not their recent items as they were on a shared account. This was done to see if a user would understand how those items got there and if they could reliably find their actions.

Results & Launch

The results from the A/B testing indicated that users overwhelmingly preferred the recent items list over the customizable pinned menu. Based on these findings, we integrated the recent items list feature into the BNY Mellon platform. It was initially rolled out to a subset of users for final validation before a broader launch.

Iteration

After launch, we continued to gather feedback and monitor user interactions to refine the feature. While the initial version met user needs, subsequent iterations improved the design based on real-world usage. We added options to filter or clear recent actions and further optimized the space where the list was displayed to ensure it was always easily accessible without cluttering the interface.

Conclusion

The personalization feature for BNY Mellon was a success, with the recent items list becoming a core part of the platform. The user-centered design approach, combined with iterative testing and analysis, led to a feature that improved user experience and efficiency. The component was then codified into a design system component and used across the platform.

Key Takeaways

While the featuring process didn't initially intend to create automation features, it showed how and iterative process can lead to a more intuitive and user-friendly solution. The feature was not initially developed with true automation as it used rather simple logic loops, it was expanded to use a ["Weighted Random" algorithm](https://dev.to/jacktt/understanding-the-weighted-random-algorithm-581p) to determine which actions to display based on user behavior. And as you'd expect this logic could be further expanded and applied to other features.

Future Considerations

This feature is an example of a philosophy of design that I've come to appreciate that combines a feature's usability with ways of testing built in. It provided ways for account administrators to set up the feature for their users and then monitor the usage of the account thereby providing data to the administrators to see what was being used and how it was being used. This can be historically be tough to test for such a seemingly small feature; the use of cookies and session data to track user behavior ended being a simple way to reproduce settings and see how they were being used.

References

• UXPin - Personalization in UX Design
• "Weighted Random" algorithm
• Maze - Empathy Mapping
• Zendesk - Personalization

Tags

#ux #design #research #design-system #design-thinking #design-research #prototyping #user-research #user-experience #user-interface #user-centered-design #heuristics #usability #product-design #product-development #product-management #product-strategy #automation #personalization #user-experience-design #user-experience-research #iteration #user-persona #case-study #financial-services #banking-and-finance

Disclaimer

This is a WORK IN PROGRESS! Everything belonging to in here is in a state of flux. This is a living .doc. I am either aware of the issue or perhaps hit me up here to discuss.

Joel Dombek © X.X.MMXXIV

Dreyfus

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Case Study: Client Onboarding

With looking at how the client onboarding process worked the goal was to create a mobile-first entry that would help automate account creation. Users were guided through a multi-step onboarding form to help distinguish what type of account they were looking to create as well as the sorts of features they might need. The other key feature was the ability to add multiple child account with specific permissions.

Defining the Problem

The client onboarding process up to this point was more-or-less a manual one the a client would need to reach out to an account rep. This process did not provide a standardized data-object and would then require both the client and sys-admin to then have to help setup.

• Complex account determination process
• Multi-step verification requirements
• Manual data verification bottlenecks
• Need for intelligent data seeding

Research

Through our research we aimed to determine how question sets could be used to funnel appropriate information while asking only questions pertinent to the account they were wanting to create.

• Analysis of existing onboarding workflows
• User interviews with clients and internal stakeholders
• Competitive analysis of other financial institutions
• Documentation of pain points in current verification process

Ideation

Smart form logic proved to be a cornerstone of the improved onboarding process. By implementing intelligent field dependencies and progressive disclosure patterns, we created a more intuitive flow that adapts to user inputs in real-time, significantly reducing confusion and error rates during the account setup process.

• Question matrix optimization
• Smart form field dependencies
• Automated verification checkpoints
• Data seeding automation possibilities

Analysis & Planning

Our analysis evolved into a comprehensive strategic framework. The user flow mapping created clear pathways through complex account determination scenarios, while detailed question matrix logic trees enabled sophisticated branching based on user responses. Data validation requirements were meticulously documented to ensure compliance with financial regulations and security standards. Integration points with existing systems were carefully mapped to maintain data consistency across platforms while enabling smooth information flow between legacy and new components.

• User flow mapping
• Question matrix logic trees
• Data validation requirements
• Integration points with existing systems

Design

Design focused on creating an intuitive interface that guides users naturally through complex processes. Progressive disclosure patterns reveal information at optimal moments, reducing cognitive load. Dynamic form fields adapt in real-time to user inputs, showing only relevant options. The status tracking interface provides clear visibility into the onboarding progress, while verification dashboards give administrators powerful oversight tools. The visual system maintains brand consistency while emphasizing clarity and trust.

• Progressive disclosure patterns
• Dynamic form fields
• Status tracking interface
• Verification dashboards

Prototyping

The prototyping brought these concepts to life through working models. The interactive question matrix demonstrated complex routing logic in action, while form validation flows simulated real-world usage patterns. Account type determination logic was refined through multiple iterations based on user feedback. Data seeding simulations verified the accuracy of automated systems and helped optimize performance. Each prototype phase revealed opportunities for enhancement before final implementation.

• Interactive question matrix
• Form validation flows
• Account type determination logic
• Data seeding simulations

Testing

Testing encompassed multiple validation layers to ensure system reliability. User acceptance testing with actual clients revealed practical usage patterns and pain points. Verification process validation confirmed regulatory compliance and security measures. Data accuracy checks ensured consistent reliable information flow. Performance metrics tracked system speed and efficiency under various load conditions. This comprehensive testing approach led to a robust final product ready for production deployment.

• User acceptance testing - Would users understand why they were being asked these questions? Would users be able to easily find the information being requested?
• Verification process validation
• Data accuracy checks - What was the minimal amount of information to setup an account that the verification agents would be able to act on.
• Performance metrics

Results & Launch

The automated data seeding capabilities delivered substantial efficiency gains across the platform. This system intelligently pre-populates relevant fields based on initial user inputs and existing data relationships, cutting down on repetitive data entry while maintaining high accuracy standards through built-in validation checks.

The impact on client experience has been transformative. Users report higher satisfaction with the streamlined process, citing reduced time investment and clearer guidance throughout the onboarding journey. The new system's ability to provide real-time feedback and status updates has particularly resonated with clients, leading to improved completion rates and reduced support queries.

• Streamlined onboarding process
• Reduced manual verification time
• Improved data accuracy
• Higher client satisfaction rates

Key Takeaways

We discovered an optimal balance between automation and manual verification processes. While automation handles routine checks and data validation, strategic manual touchpoints remain for complex cases requiring human judgment. This hybrid approach maintains security and compliance requirements while maximizing processing speed.

• Importance of smart form logic
• Value of automated data seeding
• Balance between automation and manual verification
• Impact on client experience

Future Considerations

Some future considerations would be better understanding of the data-object(s) that the system and thereby what the developers would design to have seed data for Account Creation.

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References

• Client Onboarding
• Data Ingestion: Types, Tools, Challenges & Best Practices
• How to Design Multi-Step Forms that Enhance the User Experience
• Why You Should Create Multi-Step Forms and How They Can Increase Conversions
• Object-oriented UX (OOUX): process, examples, and resources
• Data-Driven Design: Transforming UX Insights into Actions
• Data-Driven Design in UX: From Types to Implementation

Tags

#ux #design #research #design-system #design-thinking #design-research #prototyping #user-research #user-experience #user-interface #user-centered-design #heuristics #usability #product-design #product-development #product-management #product-strategy #automation #personalization #user-experience-design #user-experience-research #iteration #user-persona #case-study #financial-services #banking-and-finance

ConnectiveRX: Outline

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Defining the Problem

The admin dashboard required modernization to handle complex data management and reporting needs. Key challenges included:

• Fragmented data visualization systems
• Manual report generation processes
• Limited user role management
• Need for real-time analytics

Research

Our research focused on understanding how administrators interact with data and manage user permissions:

• Analysis of existing dashboard workflows
• Stakeholder interviews with admin users
• Competitive analysis of admin interfaces
• Documentation of reporting requirements

Ideation

Dashboard modularity emerged as a key solution component. We developed concepts for:

• Customizable dashboard layouts
• Role-based access controls
• Automated reporting systems
• Real-time data visualization

Analysis & Planning

We created a strategic framework focusing on:

• User flow mapping for admin tasks
• Permission hierarchy structures
• Data visualization requirements
• Integration points with existing systems

Design

The design phase prioritized clarity and efficiency:

• Modular dashboard components
• Dynamic data visualization tools
• Role management interface
• Reporting templates system

Prototyping

We developed working prototypes to validate:

• Interactive dashboard layouts
• Permission management flows
• Report generation systems
• Data visualization tools

Testing

Comprehensive testing included:

• Admin user acceptance testing
• Permission system validation
• Report accuracy verification
• Performance benchmarking

Results & Launch

The new admin dashboard delivered significant improvements:

• Streamlined data management
• Automated reporting capabilities
• Enhanced user role control
• Improved system efficiency

Key Takeaways

• Importance of modular design
• Value of automated reporting
• Balance of flexibility and control
• Impact on admin efficiency

Future Considerations

Future development could focus on AI-powered analytics and predictive reporting capabilities.

Vertex: Case Processing

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Research

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Ideation

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Future Considerations

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References

Dick's Sporting Goods

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Defining the Problem

The outdoor retail market needed a cohesive brand campaign that would resonate across digital and print channels. Dick's Sporting Goods required a unified visual language that would showcase their products in authentic outdoor scenarios while maintaining brand consistency.

• Fragmented brand messaging across channels
• Need for authentic lifestyle photography
• Inconsistent product storytelling
• Multi-channel asset requirements

Research

Our research focused on understanding how outdoor enthusiasts interact with sporting goods content across different touchpoints.

• Competitive analysis of outdoor retailers
• Consumer behavior studies
• Social media engagement patterns
• Brand perception surveys
• Current asset usage analysis

Ideation

We developed concepts that would showcase products in their natural environment while telling compelling stories about outdoor lifestyle experiences.

• Mood board development
• Photography style guides
• Copywriting tone frameworks
• Location scouting strategies
• Brand narrative concepts

Analysis & Planning

Created a comprehensive content strategy that mapped out shooting locations, product placement, and copy requirements across all channels.

• Shot list development
• Location mapping
• Product integration planning
• Channel-specific requirements
• Timeline coordination

Design

The design phase focused on creating versatile assets that would work across multiple platforms while maintaining visual consistency.

• Photography direction guidelines
• Typography systems
• Color palette refinement
• Layout templates
• Digital asset specifications

Prototyping

Created sample layouts and test shoots to validate the concept effectiveness.

• Test photo shoots
• Copy variations
• Digital mockups
• Print layout samples
• Social media templates

Testing

Validated assets through multiple channels to ensure effectiveness and brand alignment.

• Focus group feedback
• A/B testing of layouts
• Social media engagement metrics
• Print impact studies
• Digital performance tracking

Results & Launch

The campaign successfully launched across all channels with measurable impact:

• 40% increase in social media engagement
• Improved brand consistency scores
• Higher conversion rates on digital platforms
• Increased foot traffic from print campaigns
• Strong brand recall in post-campaign surveys

Key Takeaways

• Importance of authentic storytelling
• Value of consistent visual language
• Impact of integrated channel strategy
• Power of lifestyle-focused product photography

Future Considerations

Future campaigns could explore seasonal variations, regional customization, and expanded digital platform integration while maintaining the established visual framework.

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References

Tags

#ux #design #research #design-system #design-thinking #design-research #prototyping #user-research #user-experience #user-interface #user-centered-design #heuristics #usability #product-design #product-development #product-management #product-strategy #automation #personalization #user-experience-design #user-experience-research #iteration #user-persona #case-study #financial-services #banking-and-finance