April 11, 2019
3 min

How to convince others of the importance of UX research

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.

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.

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.

Define user research

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.

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

  • 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.

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.

The early stages

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:

  • 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.

Involve others in your research

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.

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.

Educate others on what research is

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.

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.

Collect user insights across the organization

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.

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

Bring stakeholders along to research sessions

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.

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.

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

Share your findings – consistently

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.

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.

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

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Moderated vs unmoderated research: which approach is best?

Knowing and understanding why and how your users use your product is invaluable for getting to the nitty gritty of usability. Delving deep with probing questions into motivation or skimming over looking for issues can equally be informative. 

Put super simply, usability testing literally is testing how usable your product is for your users. If your product isn’t usable users often won’t complete their task, let alone come back for more. No one wants to lose users before they even get started. Usability testing gets under their skin and really into the how, why and what they want (and equally what they don’t).

As we have been getting used to video calling regularly and using the internet for interactions, usability testing has followed suit. Being able to access participants remotely has allowed us to diversify the participant pool by not being restricted to those that are close enough to be in-person. This has also allowed an increase in the number of participants per test, as it becomes more cost-effective to perform remote usability testing.

But if we’re remote, does this mean it can’t be moderated? No - remote testing, along with modern technology, can mean that remote testing can be facilitated and moderated. But what is the best method - moderated or unmoderated?

What is moderated remote research testing?

In traditional usability testing, moderated research is done in person. With the moderator and the participant in the same physical space. This, of course, allows for conversation and observational behavioral monitoring. Meaning the moderator can note not only what the participant answers but how and even make note of the body language, surroundings, and other influencing factors. 

This has also meant that traditionally, the participant pool has been limited to those that can be available (and close enough) to make it into a facility for testing. And being in person has meant it takes time (and money) to perform these tests.

As technology has moved along and the speed of internet connections and video calling has increased, this has opened up a world of opportunities for usability testing. Allowing usability testing to be done remotely. Moderators can now set up testing remotely and ‘dial in’ to observe participants anywhere they are. And potentially even running focus groups or other testing in a group format across the internet. 

Pros of moderated remote research testing:

- In-depth gathering of insights through a back-and-forth conversation and observing of the participants.

- Follow-up questions don’t underestimate the value of being available to ask questions throughout the testing. And following up in the moment.

- Observational monitoring noticing and noting the environment and how the participants are behaving, can give more insight into how or why they choose to make a decision.

- Quick remote testing can be quicker to start, find participants, and complete than in-person. This is because you only need to set up a time to connect via the internet, rather than coordinating travel times, etc.

- Location (local and/or international) Testing online removes reliance on participants being physically present for the testing. This broadens your ability to broaden the pool, and participants can be either within your country or global. 

Cons of moderated remote research testing:

- Time-consuming having to be present at each test takes time. As does analyzing the data and insights generated. But remember, this is quality data.

- Limited interactions with any remote testing there is only so much you can observe or understand across the window of a computer screen. It can be difficult to have a grasp on all the factors that might be influencing your participants.

What is unmoderated remote research testing?

In its most simple sense, unmoderated user testing removes the ‘moderated’ part of the equation. Instead of having a facilitator guide participants through the test, participants are left to complete the testing by themselves and in their own time. For the most part, everything else stays the same. 

Removing the moderator, means that there isn’t anyone to respond to queries or issues in the moment. This can either delay, influence, or even potentially force participants to not complete or maybe not be as engaged as you may like. Unmoderated research testing suits a very simple and direct type of test. With clear instructions and no room for inference. 

Pros of unmoderated remote research testing:

- Speed and turnaround,  as there is no need to schedule meetings with each and every participant. Unmoderated usability testing is usually much faster to initiate and complete.

- Size of study (participant numbers) unmoderated usability testing allows you to collect feedback from dozens or even hundreds of users at the same time. 


- Location (local and/or international) Testing online removes reliance on participants being physically present for the testing, which broadens your participant pool.  And unmoderated testing means that it literally can be anywhere while participants complete the test in their own time.

Cons of unmoderated remote research testing:

- Follow-up questions as your participants are working on their own and in their own time, you can’t facilitate and ask questions in the moment. You may be able to ask limited follow-up questions.

- Products need to be simple to use unmoderated testing does not allow for prototypes or any product or site that needs guidance. 

- Low participant support without the moderator any issues with the test or the product can’t be picked up immediately and could influence the output of the test.

When should you do moderated vs unmoderated remote usability testing?

Each moderated and unmoderated remote usability testing have its use and place in user research. It really depends on the question you are asking and what you are wanting to know.

Moderated testing allows you to gather in-depth insights, follow up with questions, and engage the participants in the moment. The facilitator has the ability to guide participants to what they want to know, to dig deeper, or even ask why at certain points. This method doesn’t need as much careful setup as the participants aren’t on their own. While this is all done online, it does still allow connection and conversation. This method allows for more investigative research. Looking at why users might prefer one prototype to another. Or possibly tree testing a new website navigation to understand where they might get lost and querying why the participant made certain choices.

Unmoderated testing, on the other hand, is literally leaving the participants to it. This method needs very careful planning and explaining upfront. The test needs to be able to be set and run without a moderator. This lends itself more to wanting to know a direct answer to a query. Such as a card sort on a website to understand how your users might sort information. Or a first click to see how/where users will click on a new website.

Planning your next user test? Here’s how to choose the right method

With the ability to expand our pool of participants across the globe with all of the advances (and acceptance of) technology and video calling etc, the ability to expand our understanding of users’ experiences is growing. Remote usability testing is a great option when you want to gather information from users in the real world. Depending on your query, moderated or unmoderated usability testing will suit your study. As with all user testing, being prepared and planning ahead will allow you to make the most of your test.

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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

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.

Seeing is believing

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