October 1, 2025
4 minutes

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

Product, design and research teams today are drowning in user data while starving for user understanding. Never before have teams had such access to user information, analytics dashboards, heatmaps, session recordings, survey responses, social media sentiment, support tickets, and endless behavioral data points. Yet despite this volume of data, teams consistently build features users don't want and miss needs hiding in plain sight.

It’s a true paradox for product, design and research teams: more information has made genuine understanding more elusive. 

Because with  all this data, teams feel informed. They can say with confidence: "Users spend 3.2 minutes on this page," "42% abandon at this step," "Power users click here." But what this data doesn't tell you is Why. 

The Difference between Data and Insight

Data tells you what happened. Understanding tells you why it matters.

Here’s a good example of this: Your analytics show that 60% of users abandon a new feature after first use. You know they're leaving. You can see where they click before they go. You have their demographic data and behavioral patterns.

But you don't know:

  • Were they confused or simply uninterested?
  • Did it solve their problem too slowly or not at all?
  • Would they return if one thing changed, or is the entire approach wrong?
  • Are they your target users or the wrong segment entirely?

One team sees "60% abandonment" and adds onboarding tooltips. Another talks to users and discovers the feature solves the wrong problem entirely. Same data, completely different understanding.

Modern tools make it dangerously easy to mistake observation for comprehension, but some aspects of user experience exist beyond measurement:

  • Emotional context, like the frustration of trying to complete a task while handling a crying baby, or the anxiety of making a financial decision without confidence.
  • The unspoken needs of users which can only be demonstrated through real interactions. Users develop workarounds without reporting bugs. They live with friction because they don't know better solutions exist.
  • Cultural nuances that numbers don't capture, like how language choice resonates differently across cultures, or how trust signals vary by context.
  • Data shows what users do within your current product. It doesn't reveal what they'd do if you solved their problems differently to help you identify new opportunities. 

Why Human Empathy is More Important than Ever 

The teams building truly user-centered products haven't abandoned data but they've learned to combine quantitative and qualitative insights. 

  • Combine analytics (what happens), user interviews (why it happens), and observation (context in which it happens).
  • Understanding builds over time. A single study provides a snapshot; continuous engagement reveals the movie.
  • Use data to form theories, research to validate them, and real-world live testing to confirm understanding.
  • Different team members see different aspects. Engineers notice system issues, designers spot usability gaps, PMs identify market fit, researchers uncover needs.

Adding AI into the mix also emphasizes the need for human validation. While AI can help significantly speed up workflows and can augment human expertise, it still requires oversight and review from real people. 

AI can spot trends humans miss, processing millions of data points instantly but it can't understand human emotion, cultural context, or unspoken needs. It can summarize what users say but humans must interpret what they mean.

Understanding users has never been easier from a data perspective. We have tools our predecessors could only dream of.  But understanding users has never been harder from an empathy perspective. The sheer volume of data available to us creates an illusion of knowledge that's more dangerous than ignorance.

The teams succeeding aren't choosing between data and empathy, they're investing equally in both. They use analytics to spot patterns and conversations to understand meaning. They measure behavior and observe context. They quantify outcomes and qualify experiences.

Because at the end of the day, you can track every click, measure every metric, and analyze every behavior, but until you understand why, you're just collecting data, not creating understanding.

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1 min read

Measuring the impact of UXR: beyond CSAT and NPS

In the rapidly evolving world of user experience research (UXR), demonstrating value and impact has become more crucial than ever. While traditional metrics like Customer Satisfaction (CSAT) scores and Net Promoter Scores (NPS) have long been the go-to measures for UX professionals, they often fall short in capturing the full scope and depth of UXR's impact. As organizations increasingly recognize the strategic importance of user-centered design, it's time to explore more comprehensive and nuanced approaches to measuring UXR's contribution.

Limitations of traditional metrics

CSAT and NPS, while valuable, have significant limitations when it comes to measuring UXR impact. These metrics provide a snapshot of user sentiment but fail to capture the direct influence of research insights on product decisions, business outcomes, or long-term user behavior. Moreover, they can be influenced by factors outside of UXR's control, such as marketing campaigns or competitor actions, making it challenging to isolate the specific impact of research efforts.

Another limitation is the lack of context these metrics provide. They don't offer insights into why users feel a certain way or how specific research-driven improvements contributed to their satisfaction. This absence of depth can lead to misinterpretation of data and missed opportunities for meaningful improvements.

Alternative measurement approaches

To overcome these limitations, UX researchers are exploring alternative approaches to measuring impact. One promising method is the use of proxy measures that more directly tie to research activities. For example, tracking the number of research-driven product improvements implemented or measuring the reduction in customer support tickets related to usability issues can provide more tangible evidence of UXR's impact.

Another approach gaining traction is the integration of qualitative data into impact measurement. By combining quantitative metrics with rich, contextual insights from user interviews and observational studies, researchers can paint a more comprehensive picture of how their work influences user behavior and product success.

Linking UXR to business outcomes

Perhaps the most powerful way to demonstrate UXR's value is by directly connecting research insights to key business outcomes. This requires a deep understanding of organizational goals and close collaboration with stakeholders across functions. For instance, if a key business objective is to increase user retention, UX researchers can focus on identifying drivers of user loyalty and track how research-driven improvements impact retention rates over time.

Risk reduction is another critical area where UXR can demonstrate significant value. By validating product concepts and designs before launch, researchers can help organizations avoid costly mistakes and reputational damage. Tracking the number of potential issues identified and resolved through research can provide a tangible measure of this impact.

Case studies of successful impact measurement

While standardized metrics for UXR impact remain elusive, some organizations have successfully implemented innovative measurement approaches. For example, one technology company developed a "research influence score" that tracks how often research insights are cited in product decision-making processes and the subsequent impact on key performance indicators.

Another case study involves a financial services firm that implemented a "research ROI calculator." This tool estimates the potential cost savings and revenue increases associated with research-driven improvements, providing a clear financial justification for UXR investments.

These case studies highlight the importance of tailoring measurement approaches to the specific context and goals of each organization. By thinking creatively and collaborating closely with stakeholders, UX researchers can develop meaningful ways to quantify their impact and demonstrate the strategic value of their work.

As the field of UXR continues to evolve, so too must our approaches to measuring its impact. By moving beyond traditional metrics and embracing more holistic and business-aligned measurement strategies, we can ensure that the true value of user research is recognized and leveraged to drive organizational success. The future of UXR lies not just in conducting great research, but in effectively communicating its impact and cementing its role as a critical strategic function within modern organizations.

Maximize UXR ROI with Optimal 

While innovative measurement approaches are crucial, having the right tools to conduct and analyze research efficiently is equally important for maximizing UXR's return on investment. This is where the Optimal Workshop platform comes in, offering a comprehensive solution to streamline your UXR efforts and amplify their impact.

The Optimal Platform provides a suite of user-friendly tools designed to support every stage of the research process, from participant recruitment to data analysis and insight sharing. By centralizing your research activities on a single platform, you can significantly reduce the time and resources spent on administrative tasks, allowing your team to focus on generating valuable insights.

Key benefits of using Optimal for improving UXR ROI include:

  • Faster research cycles: With automated participant management and data collection tools, you can complete studies more quickly, enabling faster iteration and decision-making.

  • Enhanced collaboration: The platform's sharing features make it easy to involve stakeholders throughout the research process, increasing buy-in and ensuring insights are actioned promptly.

  • Robust analytics: Advanced data visualization and analysis tools help you uncover deeper insights and communicate them more effectively to decision-makers.

  • Scalable research: The platform's user-friendly interface enables non-researchers to conduct basic studies, democratizing research across your organization and increasing its overall impact.

  • Comprehensive reporting: Generate professional, insightful reports that clearly demonstrate the value of your research to stakeholders at all levels.

By leveraging the Optimal Workshop, you're not just improving your research processes – you're positioning UXR as a strategic driver of business success. Our platform's capabilities align perfectly with the advanced measurement approaches discussed earlier, enabling you to track research influence, calculate ROI, and demonstrate tangible impact on key business outcomes.

Ready to transform how you measure and communicate the impact of your UX research? Sign up for a free trial of the Optimal platform today and experience firsthand how it can drive your UXR efforts to new heights of efficiency and effectiveness. 

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1 min read

Optimal vs. Maze: Deep User Insights or Surface-Level Design Feedback

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.

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.

Why Choose Optimal instead of Maze?

Platform Depth

Test Design Flexibility

Optimal Offers Comprehensive Test Flexibility: Optimal has a Figma integration, image import capabilities, and fully customizable test flows designed for agile product teams.

Maze has Rigid Question Types: In contrast, Maze's focus on speed comes with design inflexibility, including rigid question structures and limited customization options that reduce overall test effectiveness.

Live Site Testing

Optimal Delivers Comprehensive Live Site Testing: Optimal's live site testing allows you to test your actual website or web app in real-time with real users, gathering behavioral data and usability insights post-launch without any code requirements. This enables continuous testing and iteration even after products are in users' hands.

Maze Offers Basic Live Website Testing: While Maze provides live website testing capabilities, its focus remains primarily on unmoderated studies with limited depth for ongoing site optimization.

Interview and Moderated Research Capabilities

Optimal Interviews Transforms Research Analysis: Optimal's new Interviews tool revolutionizes how teams extract insights from user research. Upload interview videos and let AI automatically surface key themes, generate smart highlight reels, create timestamped transcripts, and produce actionable insights in hours instead of weeks. Every insight comes with supporting video evidence, making it easy to back up recommendations with real user feedback and share compelling clips with stakeholders.

Maze Interview Studies Requires Enterprise Plan: Maze's Interview Studies feature for moderated research is only available on their highest-tier Organization plan, putting live moderated sessions out of reach for small and mid-sized teams. Teams on lower tiers must rely solely on unmoderated testing or use separate tools for interviews.

Prototype Testing Capabilities

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.

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.

Analysis and Reporting Quality

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.

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.

Enterprise Features

Dedicated Enterprise Support

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.

Maze has a Reactive Support Model: Maze provides responsive support primarily for critical issues but lacks the proactive, dedicated support enterprise product teams require.

Enterprise Readiness

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.

Maze is Built for Individuals: Maze was built primarily for individual designers and small teams, lacking the enterprise features, compliance capabilities, and scalability that large organizations need.

Enterprises Need Reliable, Scalable User Insights

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.

Don't let platform limitations compromise your research potential.

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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1 min read

5 ways to measure UX return on investment

Return on investment (ROI) is often the term on everyone’s lips when starting a big project or even when reviewing a website. It’s especially popular with those that hold the purse strings.  As UX researchers it is important to consider the ROI of the work we do and understand how to measure this. 

We’ve lined up 5 key ways to measure ROI for UX research to help you get the conversation underway with stakeholders so you can show real and tangible benefits to your organization. 

1. Meet and exceed user expectations

Put simply, a product that meets and exceeds user expectations leads to increased revenue. When potential buyers are able to find and purchase what they’re looking for, easily, they’ll complete their purchase, and are far more likely to come back. The simple fact that users can finish their task will increase sales and improve overall customer satisfaction which has an influence on their loyalty. Repeat business means repeat sales. Means increased revenue.

Creating, developing and maintaining a usable website is more important than you might think. And this is measurable! Tracking and analyzing website performance prior to the UX research and after can be insightful and directly influenced by changes made based on UX research.

Measurable: review the website (product) performance prior to UX research and after changes have been made. The increase in clicks, completed tasks and/or baskets will tell the story.

2. Reduce development time

UX research done at the initial stages of a project can lead to a reduction in development time of by 33% to 50%! And reduced time developing, means reduced costs (people and overheads) and a speedier to market date. What’s not to love? 

Measurable: This one is a little more tricky as you have saved time (and cost) up front. Aiding in speed to market and performance prior to execution. Internal stakeholder research may be of value post the live date to understand how the project went.

3. Ongoing development costs

And the double hitter? Creating a product that has the user in mind up front, reduces the need to rehash or revisit as quickly. Reducing ongoing costs. Early UX research can help with the detection of errors early on in the development process. Fixing errors after development costs a company up to 100 times more than dealing with the same error before development.

Measureable: Again, as UX research has saved time and money up front this one can be difficult to track. Though depending on your organization and previous projects you could conduct internal research to understand how the project compares and the time and cost savings.

4. Meeting user requirements

Did you know that 70% of projects fail due to the lack of user acceptance? This is often because project managers fail to understand the user requirements properly. Thanks to UX research early on, gaining insights into users and only spending time developing the functions users actually want, saving time and reducing development costs. Make sure you get confirmation on those requirements by iterative testing. As always, fail early, fail often. Robust testing up front means that in the end, you’ll have a product that will meet the needs of the user.

Measurable: Where is the product currently? How does it perform? Set a benchmark up front and review post UX research. The deliverables should make the ROI obvious.

5. Investing in UX research leads to an essential competitive advantage.

Thanks to UX research you can find out exactly what your customers want, need and expect from you. This gives you a competitive advantage over other companies in your market. But you should be aware that more and more companies are investing in UX while customers are ever more demanding, their expectations continue to grow and they don’t tolerate bad experiences. And going elsewhere is an easy decision to make.

Measurable: Murky this one, but no less important. Knowing, understanding and responding to competitors can help keep you in the lead, and developing products that meet and exceed those user expectations.

Wrap up

Showing the ROI on the work we do is an essential part of getting key stakeholders on board with our research. It can be challenging to talk the same language, ultimately we all want the same outcome…a product that works well for our users, and delivers additional revenue.

For some continued reading (or watching in this case), Anna Bek, Product and Delivery Manager at Xplor explored the same concept of "How to measure experience" during her UX New Zealand 2020 – watch it here as she shares a perspective on UX ROI.

Seeing is believing

Explore our tools and see how Optimal makes gathering insights simple, powerful, and impactful.