Why Understanding Users Has Never Been Easier...or Harder

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Product teams face an important decision when selecting the right user research platform: do they prioritize speed and simplicity, or invest in a more comprehensive platform that offers real research depth and insights? This choice becomes even more critical as user research scales and those insights directly influence major product decisions.

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Maze has gained popularity in recent years among design and product teams for its focus on rapid prototype testing and design workflow integration. However, as teams scale their research programs and require more sophisticated insights, many discover that Maze's limitations outweigh its simplicity. Platform stability issues, restricted tools and functionality, and a lack of enterprise features creates friction that end up compromising insight speed, quality and overall business impact.

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Why Choose Optimal instead of Maze?

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‍Platform Depth

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Test Design Limitations

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• Maze has Rigid Question Types: Maze's focus on speed comes with design inflexibility, including rigid question structures and limited customization options that reduce overall test effectiveness.
• Optimal Offers Comprehensive Test Flexibility: Optimal has a Figma integration, image import capabilities, and fully customizable test flows designed for agile product teams.

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Prototype Testing Capabilities

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• Maze has Limited Prototype Support: Users report difficulties with Maze's prototype testing capabilities, particularly with complex interactions and advanced design systems that modern products require.
• Optimal has Advanced Prototype Testing: Optimal supports sophisticated prototype testing with full Figma integration, comprehensive interaction capture, and flexible testing methods that accommodate modern product design and development workflows.

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Analysis and Reporting Quality

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• Maze Only Offers Surface-Level Reporting: Maze provides basic metrics and surface-level analysis without the depth required for strategic decision-making or comprehensive user insight.
• Optimal has Rich, Actionable Insights: Optimal delivers AI-powered analysis with layered insights, export-ready reports, and sophisticated visualizations that transform data into actionable business intelligence.

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Enterprise Features

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• Maze has a Reactive Support Model: Maze provides responsive support primarily for critical issues but lacks the proactive, dedicated support enterprise product teams require.
• Optimal Provides Dedicated Enterprise Support: Optimal offers fast, personalized support with dedicated account teams and comprehensive training resources built by user experience experts that ensure your team is set up for success.

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Enterprise Readiness

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• Maze is Buit for Individuals: Maze was built primarily for individual designers and small teams, lacking the enterprise features, compliance capabilities, and scalability that large organizations need.
• Optimal is an Enterprise-Built Platform: Optimal was designed for enterprise use with comprehensive security protocols, compliance certifications, and scalability features that support large research programs across multiple teams and business units. Optimal is currently trusted by some of the world’s biggest brands including Netflix, Lego and Nike. 

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Enterprises Need Reliable, Scalable User Insights

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While Maze's focus on speed appeals to design teams seeking rapid iteration, enterprise product teams need the stability and reliability that only mature platforms provide. Optimal delivers both speed and dependability, enabling teams to iterate quickly without compromising research quality or business impact.Platform reliability isn't just about uptime, it's about helping product teams make high quality strategic decisions and to build organizational confidence in user insights. Mature product, design and UX teams need to choose platforms that enhance rather than undermine their research credibility.

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Don't let platform limitations compromise your research potential.

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Ready to see how leading brands including Lego, Netflix and Nike achieve better research outcomes? Experience how Optimal's platform delivers user insights that adapt to your team's growing needs.

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In the realm of financial services, complexity isn't just a challenge, it's the default state. From intricate investment products to multi-layered insurance policies to complex fee structures, financial services are inherently complicated. But your users don't want complexity; they want confidence, clarity, and control over their financial lives.

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How to keep things simple with good UX research 

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Understanding how users perceive and navigate complexity requires systematic research. Optimal's platform offers specialized tools to identify complexity pain points and validate simplification strategies:

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Uncover Navigation Challenges with Tree Testing

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Complex financial products often create equally complex navigation structures:

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How can you solve this? 

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• Test how easily users can find key information within your financial platform
• Identify terminology and organizational structures that confuse users
• Compare different information architectures to find the most intuitive organization

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Identify Confusion Points with First-Click Testing

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Understanding where users instinctively look for information reveals valuable insights about mental models:

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How can you solve this? 

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• Test where users click when trying to accomplish common financial tasks
• Compare multiple interface designs for complex financial tools
• Identify misalignments between expected and actual user behavior

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Understand User Mental Models with Card Sorting

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Financial terminology and categorization often don't align with how customers think:

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How can you solve this? 

• Use open card sorts to understand how users naturally group financial concepts
• Test comprehension of financial terminology
• Identify intuitive labels for complex financial products

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Practical Strategies for Simplifying Financial UX

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1. Progressive Information Disclosure

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Rather than bombarding users with all information at once, layer information from essential to detailed:

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• Start with core concepts and benefits
• Provide expandable sections for those who want deeper dives
• Use tooltips and contextual help for terminology
• Create information hierarchies that guide users from basic to advanced understanding

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2. Visual Representation of Numerical Concepts

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Financial services are inherently numerical, but humans don't naturally think in numbers—we think in pictures and comparisons.

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What could this look like? 

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• Use visual scales and comparisons instead of just presenting raw numbers
• Implement interactive calculators that show real-time impact of choices
• Create visual hierarchies that guide attention to most relevant figures
• Design comparative visualizations that put numbers in context

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3. Contextual Decision Support

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Users don't just need information; they need guidance relevant to their specific situation.

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How do you solve for this? 

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• Design contextual recommendations based on user data
• Provide comparison tools that highlight differences relevant to the user
• Offer scenario modeling that shows outcomes of different choices
• Implement guided decision flows for complex choices

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4. Language Simplification and Standardization

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Financial jargon is perhaps the most visible form of unnecessary complexity. So, what can you do? 

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• Develop and enforce a simplified language style guide
• Create a financial glossary integrated contextually into the experience
• Test copy with actual users, measuring comprehension, not just preference
• Replace industry terms with everyday language when possible

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Measuring Simplification Success

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To determine whether your simplification efforts are working, establish a continuous measurement program:

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1. Establish Complexity Baselines

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Use Optimal's tools to create baseline measurements:

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• Success rates for completing complex tasks
• Time required to find critical information
• Comprehension scores for key financial concepts
• User confidence ratings for financial decisions

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2. Implement Iterative Testing

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Before launching major simplification initiatives, validate improvements through:

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• A/B testing of alternative explanations and designs
• Comparative testing of current vs. simplified interfaces
• Comprehension testing of revised terminology and content

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3. Track Simplification Metrics Over Time

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Create a dashboard of key simplification indicators:

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• Task success rates for complex financial activities
• Support call volume related to confusion
• Feature adoption rates for previously underutilized tools
• User-reported confidence in financial decisions

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Where rubber hits the road: Organizational Commitment to Clarity

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True simplification goes beyond interface design. It requires organizational commitment at the most foundational level:

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• Product development: Are we creating inherently understandable products?
• Legal and compliance: Can we satisfy requirements while maintaining clarity?
• Marketing: Are we setting appropriate expectations about complexity?
• Customer service: Are we gathering intelligence about confusion points?

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When there is a deep commitment from the entire organization to simplification, it becomes part of a businesses’ UX DNA. 

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Conclusion: The Future Belongs to the Clear

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As financial services become increasingly digital and self-directed, clarity bcomes essential for business success. The financial brands that will thrive in the coming decade won't necessarily be those with the most features or the lowest fees, but those that make the complex world of finance genuinely understandable to everyday users.

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By embracing clarity as a core design principle and supporting it with systematic user research, you're not just improving user experience, you're democratizing financial success itself.

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There’s not much a parent won’t do to ensure their child has the best chance of succeeding in life. Unsurprisingly, things are much the same in product development. Whether it’s a designer, manager, developer or copywriter, everyone wants to see the product reach its full potential.

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Key to a product’s success (even though it’s still not widely practiced) is UX research. Without research focused on learning user pain points and behaviors, development basically happens in the dark. Feeding direct insights from customers and users into the development of a product means teams can flick the light on and make more informed design decisions.

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While the benefits of user research are obvious to anyone working in the field, it can be a real challenge to convince others of just how important and useful it is. We thought we’d help.

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Define user research

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If you want to sell the importance of UX research within your organization, you’ve got to ensure stakeholders have a clear understanding of what user research is and what they stand to gain from backing it.

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In general, there are a few key things worth focusing on when you’re trying to explain the benefits of research:

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• More informed design decisions: Companies make major design decisions far too often without considering users. User research provides the data needed to make informed decisions.
• Less uncertainty and risk: Similarly, research reduces risk and uncertainty simply by giving companies more clarity around how a particular product or service is used.
• Retention and conversion benefits: Research means you’ll be more aligned with the needs of your customers and prospective customers.

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Use the language of the people you’re trying to convince. A capable UX research practice will almost always improve key business metrics, namely sales and retention.

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The early stages

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When embarking on a project, book in some time early in the process to answer questions, explain your research approach and what you hope to gain from it. Here are some of the key things to go over:

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• Your objectives: What are you trying to achieve? This is a good time to cover your research questions.
• Your research methods: Which methods will you be using to carry out your research? Cover the advantages of these methods and the information you’re likely to get from using them.
• Constraints: Do you see any major obstacles? Any issues with resources?
• Provide examples: Nothing shows the value of doing research quite like a case study. If you can’t find an example of research within your own organization, see what you can find online.

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Involve others in your research

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When trying to convince someone of the validity of what you’re doing, it’s often best to just show them. There are a couple of effective ways you can do this – at a team or individual level and at an organizational level.

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We’ll explain the best way to approach this below, but there’s another important reason to bring others into your research. UX research can’t exist in a vacuum – it thrives on integration and collaboration with other teams. Importantly, this also means working with other teams to define the problems they’re trying to solve and the scope of their projects. Once you’ve got an understanding of what they’re trying to achieve, you’ll be in a better position to help them through research.

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Educate others on what research is

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Education sessions (lunch-and-learns) are one of the best ways to get a particular team or group together and run through the what and why of user research. You can work with them to work out what they’d like to see from you, and how you can help each other.

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Tailor what you’re saying to different teams, especially if you’re talking to people with vastly different skill sets. For example, developers and designers are likely to see entirely different value in research.

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Collect user insights across the organization

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Putting together a comprehensive internal repository focused specifically on user research is another excellent way to grow awareness. It can also help to quantify things that may otherwise fall by the wayside. For example, you can measure the magnitude of certain pain points or observe patterns in feature requests. Using a platform like Notion or Confluence (or even Google Drive if you don’t want a dedicated platform), log all of your study notes, insights and research information that you find useful.

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Whenever someone wants to learn more about research within the organization, they’ll be able to find everything easily.

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Bring stakeholders along to research sessions

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Getting a stakeholder along to a research session (usability tests and user interviews are great starting points) will help to show them the value that face-to-face sessions with users can provide.

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To really involve an observer in your UX research, assign them a specific role. Note taker, for example. With a short briefing on best-practices for note taking, they can get a feel for what’s like to do some of the work you do.

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You may also want to consider bringing anyone who’s interested along to a research session, even if they’re just there to observe.

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Share your findings – consistently

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Research is about more than just testing a hypothesis, it’s important to actually take your research back to the people who can action the data.

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By sharing your research findings with teams and stakeholders regularly, your organization will start to build up an understanding of the value that ongoing research can provide, meaning getting approval to pursue research in future becomes easier. This is a bit of a chicken and egg situation, but it’s a practice that all researchers need to get into – especially those embedded in large teams or organizations.

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Anything else you think is worth mentioning? Let us know in the comments.

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Read more

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• Selling your design recommendations to clients and colleagues – Guest writer Jeff Tang outlines some of his techniques for presenting UX recommendations and answering objections.
• Quantifying the ROI of UX – Ashlea McKay delves into one of the toughest UX questions to answer: “What do we get for our money?”
• How to lead a UX team – With user-centered design growing in organizations around the world, we’ll need capable leaders to run UX teams.
• How do I explain what UX is? – Ashlea McKay covers how you can explain UX to people who may not necessarily have familiarity with the field.