April 10, 2022
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5 ways to measure UX return on investment

Header graphic for the article '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.

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Mixed methods research in 2021

User experience research is super important to developing a product that truly engages, compels and energises people. We all want a website that is easy to navigate, simple to follow and compels our users to finish their tasks. Or an app that supports and drives engagement.

We’ve talked a lot about the various types of research tools that help improve these outcomes. 

There is a rising research trend in 2021.

Mixed method research - what is more compelling than these user research quantitative tools? Combining these with awesome qualitative research! Asking the same questions in various ways can provide deeper insights into how our users think and operate. Empowering you to develop products that truly talk to your users, answer their queries or even address their frustrations.

Though it isn’t enough to simply ‘do research’, as with anything you need to approach it with strategy, focus and direction. This will funnel your time, money and energy into areas that will generate the best results.

Mixed Method UX research is the research trend of 2021

With the likes of Facebook, Amazon, Etsy, eBay, Ford and many more big organizations offering newly formed job openings for mixed methods researchers it becomes very obvious where the research trend is heading.

It’s not only good to have, but now becoming imperative, to gather data, dive deeper and generate insights that provide more information on our users than ever before. And you don't need to be Facebook to reap the benefits. Mixed method research can be implemented across the board and can be as narrow as finding out how your homepage is performing through to analysing in depth the entirety of your product design.

And with all of these massive organizations making the move to increase their data collection and research teams. Why wouldn’t you?

The value in mixed method research is profound. Imagine understanding what, where, how and why your customers would want to use your service. And catering directly for them. The more we understand our customers, the deeper the relationship and the more likely we are to keep them engaged.

Although of course by diving deep into the reasons our users like (or don’t like) how our products operate can drive your organization to target and operate better at a higher level. Gearing your energies to attracting and keeping the right type of customer, providing the right level of service and after care. Potentially reducing overheads, by not delivering to expected levels.

What is mixed method research?

Mixed methods research isn’t overly complicated, and doesn’t take years for you to master. It simply is a term used to refer to using a combination of quantitative and qualitative data. This may mean using a research tool such as card sorting alongside interviews with users. 

Quantitative research is the tangible numbers and metrics that can be gathered through user research such as card sorting or tree testing.

Qualitative research is research around users’ behaviour and experiences. This can be through usability tests, interviews or surveys.

For instance you may be asking ‘how should I order the products on my site?’. With card sorting you can get the data insights that will inform how a user would like to see the products sorted. Coupled with interviews you will get the why.

Understanding the thinking behind the order, and why one user likes to see gym shorts stored under shorts and another would like to see them under active wear. With a deeper understanding of how and why users decide how content should be sorted are made will create a highly intuitive website. 

Another great reason for mixed method research would be to back up data insights for stakeholders. With a depth and breadth of qualitative and quantitative research informing decisions, it becomes clearer why changes may need to be made, or product designs need to be challenged.

How to do mixed method research

Take a look at our article for more examples of the uses of mixed method research. 

Simply put mixed method research means coupling quantitative research, such as tree testing, card sorting or first click testing, with qualitative research such as surveys, interviews or diary entry.

Say, for instance, the product manager has identified that there is an issue with keeping users engaged on the homepage of your website. We would start with asking where they get stuck, and when they are leaving.

This can be done using a first-click tool, such as Chalkmark, which will map where users head when they land on your homepage and beyond. 

This will give you the initial qualitative data. However, it may only give you some of the picture. Coupled with qualitative data, such as watching (and reporting on) body language. Or conducting interviews with users directly after their experience so we can understand why they found the process confusing or misleading.

A fuller picture, means a better understanding.

Key is to identify what your question is and honing in on this through both methods. Ultimately, we are answering your question from both sides of the coin.

Upcoming research trends to watch

Keeping an eye on the progression of the mixed method research trend, will mean keeping an eye on these:

1. Integrated Surveys

Rather than thinking of user surveys as being a one time, in person event, we’re seeing more and more often surveys being implemented through social media, on websites and through email. This means that data can be gathered frequently and across the board. This longitude data allows organizations to continuously analyse, interpret and improve products without really ever stopping. 

Rather than relying on users' memories for events and experiences data can be gathered in the moment. At the time of purchase or interaction. Increasing the reliability and quality of the data collected. 

2. Return to the social research

Customer research is rooted in the focus group. The collection of participants in one space, that allows them to voice their opinions and reach insights collectively. This did used to be an overwhelming task with days or even weeks to analyse unstructured forums and group discussions.

However, now with the advent of online research tools this can also be a way to round out mixed method research.

3. Co-creation

The ability to use your customers input to build better products. This has long been thought a way to increase innovative development. Until recently it too has been cumbersome and difficult to wrangle more than a few participants. But, there are a number of resources in development that will make co-creation the buzzword of the decade.

4. Owned Panels & Community

Beyond community engagement in the social sphere. There is a massive opportunity to utilise these engaged users in product development. Through a trusted forum, users are far more likely to actively and willingly participate in research. Providing insights into the community that will drive stronger product outcomes.

What does this all mean for me

So, there is a lot to keep in mind when conducting any effective user research. And there are a lot of very compelling reasons to do mixed method research and do it regularly. 

To remain innovative, and ahead of the ball it remains very important to be engaged with your users and their needs. Using qualitative and qualitative research to inform product decisions means you can operate knowing a fuller picture.

One of the biggest challenges with user research can be the coordination and participant recruitment. That’s where we come in.

Taking the pain out of the process and streamlining your research. Take a look at our Qualitative Research option, Reframer. Giving you an insight into how we can help make your mixed method research easier and analyse your data efficiently and in a format that is easy to understand.

User research doesn’t need to take weeks or months. With our participant recruitment we can provide reliable and quality participants across the board that will provide data you can rely on.

Why not get in deeper with mixed method research today!

Header graphic for the article 'Optimal vs. Maze: Deep User Insights or Surface-Level Design Feedback'
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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.

Header graphic for the article 'Why Understanding Users Has Never Been Easier...or Harder'
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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.