How Morgan Stanley Transformed Their UX Research with Optimal
American investment bank and financial services company
When you're managing complex wealth management services and trading platforms, getting the user experience right is a differentiator. Morgan Stanley discovered this firsthand and partnered with Optimal to completely transform how they approach user research. The result? A systematic, data-driven approach that enhanced navigation systems, validated investment tools, and improved advisor-client interactions across their entire financial ecosystem.
The Challenge: Making Sense of Financial Complexity
Historically financial services aren't exactly known for being user-friendly and this was true for Morgan Stanley. The financial services giant was facing:
- Navigation Challenges: When you've got complex financial services spread across multiple systems, things get confusing fast. Both advisors and clients were struggling to find what they needed, when they needed it.
- Investment Tool Uncertainty: Rolling out new digital investment platforms is risky business. Without proper validation, there's no guarantee that advisors will actually adopt new tools or that clients will understand how to use them.
- Service Organization Complexity: With so many financial products and services, users were getting lost trying to locate what they were looking for. It was like having a massive library with no catalog system.
- Communication Blind Spots: Understanding how advisors and clients actually interact with platform features? That required digging deeper than surface-level analytics could provide.
- Platform Inconsistencies: When you're managing multiple trading platforms, keeping vocabulary and user experience consistent becomes a real headache.
The Solution: Research That Actually Works
Here's where things get interesting. Instead of guessing what users wanted, Morgan Stanley decided to ask them systematically and at scale. They implemented Optimal's platform to build a comprehensive research program that grew from basic studies into sophisticated user insights:
- Getting the Foundation Right: Morgan Stanley started with the basics but did them thoroughly. They conducted card sorting studies to figure out how users naturally think about financial planning workflows and goal prioritization. Then they implemented extensive tree testing across client information platforms, not just once, but across multiple studies to really nail down the navigation. They also tested different ways to categorize services, because if users can't find what they're looking for, nothing else matters.
- Leveling Up with Advanced Methods: Once they had the foundation solid, Morgan Stanley got more sophisticated. They deployed hybrid card sorting for expense management systems and followed up with targeted tree testing to validate their findings. They ran unmoderated usability tests on investment advisory tools to see how transitions actually worked in real-world scenarios. Plus, they executed extensive surveys to optimize advisor recruitment and onboarding, and implemented vocabulary standardization surveys to make sure everyone was speaking the same language across platforms.
- Going Deep with User Understanding: This is where Morgan Stanley really stepped up their game. They leveraged qualitative insights extensively, conducting interviews about investment portfolios and client holdings to understand the nuanced needs of their users. They managed large-scale studies with hundreds or even thousands of participants when they needed statistical confidence, but also ran focused sessions with just a handful of users when they needed deep behavioral insights. Smart tagging systems helped them organize all this research data for cross-study analysis.
The Results: When Research Pays Off
The systematic approach paid off in ways that directly impacted Morgan Stanley's bottom line:
- Navigation that meets users’ needs: Streamlined information architecture meant advisors and clients could find what they needed faster, reducing frustration and improving task completion rates.
- Smarter Tool Rollouts: Pre-launch testing minimized the risk of expensive flops and helped new investment tools get adopted more quickly by advisors.
- Users Can Help Themselves: Better categorization systems meant more people could find answers on their own, reducing the load on customer support teams.
- Decisions Based on Data: High-volume research studies provided the statistical backing needed for major platform development decisions.
- Faster, Smarter Development: Systematic validation meant fewer costly do-overs after launch and better feature acceptance rates.
The Bigger Picture: Building Something That Lasts
What's really impressive about Morgan Stanley's approach is how they've built research into their DNA. Through their ongoing partnership with Optimal, they've developed research operations that scale, growing from occasional studies to comprehensive programs that support multiple product teams at once. They've gotten smart about combining different research methods, using quantitative approaches like tree testing and card sorting alongside qualitative insights for a complete picture of user needs. Most importantly, they've implemented validation frameworks that test concepts before major development investments, while establishing research-backed standards that keep user experiences consistent across all their diverse financial services.
Ready to transform your financial services user experience through strategic research? Discover how Optimal can help you build a research program that actually drives results.
