November 3, 2024
3 min

Unlocking UX excellence: Practical use cases for Optimal's research platform

In today's digital landscape, delivering exceptional user experiences is no longer optional—it's essential for success. At Optimal, we're committed to empowering UX professionals and organizations with the best-in-class tools and methodologies to create outstanding digital products and experiences. 

In this blog post, we'll explore practical use cases that demonstrate how Optimal's research platform can drive meaningful improvements across various UX scenarios.

Use case 1: Make Collaborative Design Decisions or A/B Test a Design

Whether you're refining an existing product, launching a new website, or rebranding, Optimal's user research and insights platform empowers your team to make informed, collaborative design decisions. Here's how to leverage our tools for impactful results:

1. Qualitative Insights: Establish organizational priorities

  • Use our Qualitative Research tool to develop a comprehensive list of top tasks or goals from your organization's perspective.
  • Engage stakeholders across departments to ensure alignment on key objectives.

2. Surveys: Validate user priorities and pain points

  • Deploy a targeted survey using our Survey tool to confirm users' top tasks and identify existing issues.
  • Gather quantitative data to support or challenge organizational assumptions about user needs.

3. First-click Testing: Conduct preference testing

  • Use our First-Click Testing tool to evaluate the effectiveness of different design options.
  • This method provides valuable insights for A/B testing decisions, ensuring designs resonate with your target audience.

4. Qualitative Insights: Deep dive into user preferences

  • Conduct follow-up interviews or focus groups using our Qualitative Research tool to gain a deeper understanding of user preferences and experiences with different design options.
  • Explore the 'why' behind user choices to inform more nuanced design decisions.

By systematically applying these research methods, your team can collaboratively create designs that not only look great but also deliver exceptional user experiences. Optimal's platform empowers you to make data-driven design decisions, fostering innovation while minimizing the risk of costly missteps.

Remember, the key to successful collaborative design is continuous iteration and testing. Use Optimal's tools throughout your design process to validate decisions, gather feedback, and refine your approach for optimal results.

Use case 2: Developing effective content strategies

Developing a robust content strategy is crucial for intranets, help documents, websites, and product copy. Optimal's user research and insights platform empowers you to create content that resonates with your audience and drives engagement. Here's how to leverage our tools for effective content strategy development:

1. Card Sorting: Organize content intuitively

  • Use our Card Sorting tool to understand how users naturally categorize and group your content.
  • Gain insights into users' mental models to inform your content hierarchy and organization.
  • Apply findings to create a content structure that aligns with user expectations, enhancing findability and engagement.

2. Tree Testing: Validate information architecture

  • Employ our Tree Testing tool to confirm whether information placed within your proposed hierarchy is findable and understandable.
  • Identify areas where users struggle to locate content, enabling you to refine your structure for optimal user experience.
  • Iterate on your information architecture based on concrete user data, ensuring your content is easily accessible.
  • Test different content structures and then compare them with each other using the task comparison tool available in Optimal to understand which structure is most likely to drive users to perform the targeted actions.

3. Qualitative Insights: Analyze language perceptions

  • Leverage our Qualitative Research tool to conduct in-depth interviews or focus groups.
  • Explore user perceptions of terminology, language style, and content tone.
  • Gather rich insights to inform your content voice and style guide, ensuring your messaging resonates with your target audience.

4. Additional Applications of Qualitative Insights

   Expand your content strategy research by using our Qualitative Research tool to:

  • Review internal tools and processes to streamline content creation workflows.
  • Compare content experiences across desktop and mobile devices for consistency.
  • Gather event feedback to inform content for future marketing materials.
  • Analyze customer service and support interactions to identify common issues and FAQs.
  • Conduct usability testing on existing content to identify areas for improvement.

   Key questions to explore:

  • What's working well in your current content?
  • What's not resonating with users?
  • What are users' first impressions of your content?
  • How do users typically interact with your content?
  • How well does your content foster empathy and connection with your audience?

By systematically applying these research methods, you'll develop a content strategy that not only meets your organizational goals but also deeply resonates with your audience. Optimal's platform empowers you to create content that informs, engages, and converts, driving meaningful results for your business.

Remember, content strategy is an ongoing process. Regularly use Optimal's tools to assess the effectiveness of your content, gather user feedback, and iteratively improve your approach for continued success.

Use case 3: Increase website traffic

Empower your team to boost conversion rates by leveraging Optimal's best-in-class user research and insights platform. Here's how you can unlock meaningful improvements:

1. Qualitative Insights & Surveys: Uncover user motivations

  • Conduct in-depth interviews or targeted surveys to gather rich, qualitative feedback about user experiences, motivations, and pain points on your site.
  • Add an intercept snippet to your existing website to survey users as they come to your website to get a clear understanding of user motivations in context.
  • Analyze responses to identify key themes and opportunities for optimization.

2. Tree Testing: Optimize navigation structure

  • Use our Tree Testing tool to evaluate the effectiveness of your site's navigation structure.
  • Identify areas where users struggle to find information, enabling you to streamline pathways to conversion.

3. Card Sorting: Enhance information architecture

  • Leverage our Card Sorting tool to understand how users naturally categorize your site's information.
  • Apply insights to refine the layout of product features or benefits on your landing pages, aligning with user expectations.

4. Prototype Testing: Validate Design Changes

  • Develop prototypes of new landing pages or key conversion elements (like CTAs) using our Prototype Testing tool.
  • Conduct first-click tests to ensure your design changes resonate with users and drive desired actions.

5. Follow-up Qualitative Insights: Iterate and improve

  • After implementing changes, conduct follow-up interviews or surveys to gauge the impact of your optimizations.
  • Gather feedback on the improved user experience and identify any remaining pain points.

By systematically applying these research methods, you'll gain the actionable insights needed to create a more intuitive, engaging, and conversion-friendly website. Optimal empowers you to make data-driven decisions that not only boost conversions but also enhance overall user satisfaction.

Embracing mixed methods research

To truly unlock the power of user research, we recommend a mixed methods approach. By combining quantitative data from surveys and usability tests with qualitative insights from interviews and open-ended responses, you can gain a comprehensive understanding of your users' needs and behaviors.

For more information on mixed methods research and how it can enhance your UX strategy, check out our detailed guide: What is mixed methods research?

And that’s a wrap

Optimal's user research and insights platform provides the tools and methodologies you need to deliver exceptional digital experiences. By leveraging these use cases and adopting a mixed methods approach, you can make data-driven decisions that resonate with your users and drive business success.

Remember, great UX is an ongoing journey. Regularly employ these research methods to stay attuned to your users' evolving needs and preferences. With Optimal as your partner, you're equipped to create digital products and experiences that truly stand out in today's competitive landscape.

Ready to elevate your UX research? Explore Optimal's platform and start unlocking actionable insights today!

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Insight Discovery In Seconds To Take You From Data To Impact Faster

In our Value of UX Research report, nearly 70% of participants identified analysis and synthesis as the area where AI could make the biggest impact.

At Optimal, we're all about cutting the busywork so you can spend more time on meaningful insights and action. That’s why we’ve built automated Insights, powered by AI, to instantly surface key themes from your survey responses. 

No extra tools. No manual review. Just faster insights to help you make quicker, data-backed decisions.

What You’ll Get with Automated Insights

  • Instant insight discovery
    Spot patterns instantly across hundreds of responses without reading every single one. Get insights served up with zero manual digging or theme-hunting.

  • Insights grounded in real participant responses
    We show the numbers behind every key takeaway, including percentage and participant count, so you know exactly what’s driving each insight. And when participants say it best, we pull out their quotes to bring the insights to life.

  • Zoom in for full context
    Want to know more? Easily drill down to the exact participants behind each insight for open text responses, so you can verify, understand nuances, and make informed decisions with confidence.

  • Segment-specific insights
    Apply any segment to your data and instantly uncover what matters most to that group. Whether you’re exploring by persona, demographic, or behavior, the themes adapt accordingly.

  • Available across the board
    From survey questions to pre- and post-study, and post-task questions, you’ll automatically get Insights across all question types, including open text questions, matrix, ranking, and more.


Automate the Busywork, Focus on the Breakthroughs


Automated Insights are just one part of our ever-growing AI toolkit at Optimal. We're making it easier (and faster) to go from raw data to real impact:

  • AI Simplify
    Write better survey questions, effortlessly. Our AI assistant suggests clearer, more effective wording to help you engage participants and get higher-quality data.

  • Qualitative Insights, Supercharged
    Transform free-form feedback into actionable insights. Whether you're analyzing notes or transcripts, our AI helps you uncover patterns and key insights you may have missed.

Ready to level up your UX research? Log into your account to get started with these newest capabilities or sign up for a free trial to experience them for yourselves.

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Efficient Research: Maximizing the ROI of Understanding Your Customers

Introduction

User research is invaluable, but in fast-paced environments, researchers often struggle with tight deadlines, limited resources, and the need to prove their impact. In our recent UX Insider webinar, Weidan Li, Senior UX Researcher at Seek, shared insights on Efficient Research—an approach that optimizes Speed, Quality, and Impact to maximize the return on investment (ROI) of understanding customers.

At the heart of this approach is the Efficient Research Framework, which balances these three critical factors:

  • Speed – Conducting research quickly without sacrificing key insights.
  • Quality – Ensuring rigor and reliability in findings.
  • Impact – Making sure research leads to meaningful business and product changes.

Within this framework, Weidan outlined nine tactics that help UX researchers work more effectively. Let’s dive in.

1. Time Allocation: Invest in What Matters Most

Not all research requires the same level of depth. Efficient researchers prioritize their time by categorizing projects based on urgency and impact:

  • High-stakes decisions (e.g., launching a new product) require deep research.
  • Routine optimizations (e.g., tweaking UI elements) can rely on quick testing methods.
  • Low-impact changes may not need research at all.

By allocating time wisely, researchers can avoid spending weeks on minor issues while ensuring critical decisions are well-informed.

2. Assistance of AI: Let Technology Handle the Heavy Lifting

AI is transforming UX research, enabling faster and more scalable insights. Weidan suggests using AI to:

  • Automate data analysis – AI can quickly analyze survey responses, transcripts, and usability test results.
  • Generate research summaries – Tools like ChatGPT can help synthesize findings into digestible insights.
  • Speed up recruitment – AI-powered platforms can help find and screen participants efficiently.

While AI can’t replace human judgment, it can free up researchers to focus on higher-value tasks like interpreting results and influencing strategy.

3. Collaboration: Make Research a Team Sport

Research has a greater impact when it’s embedded into the product development process. Weidan emphasizes:

  • Co-creating research plans with designers, PMs, and engineers to align on priorities.
  • Involving stakeholders in synthesis sessions so insights don’t sit in a report.
  • Encouraging non-researchers to run lightweight studies, such as A/B tests or quick usability checks.

When research is shared and collaborative, it leads to faster adoption of insights and stronger decision-making.

4. Prioritization: Focus on the Right Questions

With limited resources, researchers must choose their battles wisely. Weidan recommends using a prioritization framework to assess:

  • Business impact – Will this research influence a high-stakes decision?
  • User impact – Does it address a major pain point?
  • Feasibility – Can we conduct this research quickly and effectively?

By filtering out low-priority projects, researchers can avoid research for research’s sake and focus on what truly drives change.

5. Depth of Understanding: Go Beyond Surface-Level Insights

Speed is important, but efficient research isn’t about cutting corners. Weidan stresses that even quick studies should provide a deep understanding of users by:

  • Asking why, not just what – Observing behavior is useful, but uncovering motivations is key.
  • Using triangulation – Combining methods (e.g., usability tests + surveys) to validate findings.
  • Revisiting past research – Leveraging existing insights instead of starting from scratch.

Balancing speed with depth ensures research is not just fast, but meaningful.

6. Anticipation: Stay Ahead of Research Needs

Proactive researchers don’t wait for stakeholders to request studies—they anticipate needs and set up research ahead of time. This means:

  • Building a research roadmap that aligns with upcoming product decisions.
  • Running continuous discovery research so teams have a backlog of insights to pull from.
  • Creating self-serve research repositories where teams can find relevant past studies.

By anticipating research needs, UX teams can reduce last-minute requests and deliver insights exactly when they’re needed.

7. Justification of Methodology: Explain Why Your Approach Works

Stakeholders may question research methods, especially when they seem time-consuming or expensive. Weidan highlights the importance of educating teams on why specific methods are used:

  • Clearly explain why qualitative research is needed when stakeholders push for just numbers.
  • Show real-world examples of how past research has led to business success.
  • Provide a trade-off analysis (e.g., “This method is faster but provides less depth”) to help teams make informed choices.

A well-justified approach ensures research is respected and acted upon.

8. Individual Engagement: Tailor Research Communication to Your Audience

Not all stakeholders consume research the same way. Weidan recommends adapting insights to fit different audiences:

  • Executives – Focus on high-level impact and key takeaways.
  • Product teams – Provide actionable recommendations tied to specific features.
  • Designers & Engineers – Share usability findings with video clips or screenshots.

By delivering insights in the right format, researchers increase the likelihood of stakeholder buy-in and action.

9. Business Actions: Ensure Research Leads to Real Change

The ultimate goal of research is not just understanding users—but driving business decisions. To ensure research leads to action:

  • Follow up on implementation – Track whether teams apply the insights.
  • Tie findings to key metrics – Show how research affects conversion rates, retention, or engagement.
  • Advocate for iterative research – Encourage teams to re-test and refine based on new data.

Research is most valuable when it translates into real business outcomes.

Final Thoughts: Research That Moves the Needle

Efficient research is not just about doing more, faster—it’s about balancing speed, quality, and impact to maximize its influence. Weidan’s nine tactics help UX researchers work smarter by:


✔️  Prioritizing high-impact work
✔️  Leveraging AI and collaboration
✔️  Communicating research in a way that drives action

By adopting these strategies, UX teams can ensure their research is not just insightful, but transformational.

Watch the full webinar here

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Clara Kliman-Silver: AI & design: imagining the future of UX

In the last few years, the influence of AI has steadily been expanding into various aspects of design. In early 2023, that expansion exploded. AI tools and features are now everywhere, and there are two ways designers commonly react to it:

  • With enthusiasm for how they can use it to make their jobs easier
  • With skepticism over how reliable it is, or even fear that it could replace their jobs

Google UX researcher Clara Kliman-Silver is at the forefront of researching and understanding the potential impact of AI on design into the future. This is a hot topic that’s on the radar of many designers as they grapple with what the new normal is, and how it will change things in the coming years.

Clara’s background 

Clara Kliman-Silver spends her time studying design teams and systems, UX tools and designer-developer collaboration. She’s a specialist in participatory design and uses generative methods to investigate workflows, understand designer-developer experiences, and imagine ways to create UIs. In this work, Clara looks at how technology can be leveraged to help people make things, and do it more efficiently than they currently are.

In today’s context, that puts generative AI and machine learning right in her line of sight. The way this technology has boomed in recent times has many people scrambling to catch up - to identify the biggest opportunities and to understand the risks that come with it. Clara is a leader in assessing the implications of AI. She analyzes both the technology itself and the way people feel about it to forecast what it will mean into the future.

Contact Details:

You can find Clara in LinkedIn or on Twitter @cklimansilver

What role should artificial intelligence play in UX design process? 🤔

Clara’s expertise in understanding the role of AI in design comes from significant research and analysis of how the technology is being used currently and how industry experts feel about it. AI is everywhere in today’s world, from home devices to tech platforms and specific tools for various industries. In many cases, AI automation is used for productivity, where it can speed up processes with subtle, easy to use applications.

As mentioned above, the transformational capabilities of AI are met with equal parts of enthusiasm and skepticism. The way people use AI, and how they feel about it is important, because users need to be comfortable implementing the technology in order for it to make a difference. The question of what value AI brings to the design process is ongoing. On one hand, AI can help increase efficiency for systems and processes. On the other hand, it can exacerbate problems if the user's intentions are misunderstood.

Access for all 🦾

There’s no doubt that AI tools enable novices to perform tasks that, in years gone by, required a high level of expertise. For example, film editing was previously a manual task, where people would literally cut rolls of film and splice them together on a reel. It was something only a trained editor could do. Now, anyone with a smartphone has access to iMovie or a similar app, and they can edit film in seconds.

For film experts, digital technology allows them to speed up tedious tasks and focus on more sophisticated aspects of their work. Clara hypothesizes that AI is particularly valuable when it automates mundane tasks. AI enables more individuals to leverage digital technologies without requiring specialist training. Thus, AI has shifted the landscape of what it means to be an “expert” in a field. Expertise is about more than being able to simply do something - it includes having the knowledge and experience to do it for an informed reason. 

Research and testing 🔬

Clara performs a lot of concept testing, which involves recognizing the perceived value of an approach or method. Concept testing helps in scenarios where a solution may not address a problem or where the real problem is difficult to identify. In a recent survey, Clara describes two predominant benefits designers experienced from AI:

  1. Efficiency. Not only does AI expedite the problem solving process, it can also help efficiently identify problems. 
  2. Innovation. Generative AI can innovate on its own, developing ideas that designers themselves may not have thought of.

The design partnership 🤝🏽

Overall, Clara says UX designers tend to see AI as a creative partner. However, most users don’t yet trust AI enough to give it complete agency over the work it’s used for. The level of trust designers have exists on a continuum, where it depends on the nature of the work and the context of what they’re aiming to accomplish. Other factors such as where the tech comes from, who curated it and who’s training the model also influences trust. For now, AI is largely seen as a valued tool, and there is cautious optimism and tentative acceptance for its application. 

Why it matters 💡

AI presents as potentially one of the biggest game-changers to how people work in our generation. Although AI has widespread applications across sectors and systems, there are still many questions about it. In the design world, systems like DALL-E allow people to create AI-generated imagery, and auto layout in various tools allows designers to iterate more quickly and efficiently.

Like many other industries, designers are wondering where AI might go in the future and what it might look like. The answer to these questions has very real implications for the future of design jobs and whether they will exist. In practice, Clara describes the current mood towards AI as existing on a continuum between adherence and innovation:

  • Adherence is about how AI helps designers follow best practice
  • Innovation is at the other end of the spectrum, and involves using AI to figure out what’s possible

The current environment is extremely subjective, and there’s no agreed best practice. This makes it difficult to recommend a certain approach to adopting AI and creating permanent systems around it. Both the technology and the sentiment around it will evolve through time, and it’s something designers, like all people, will need to maintain good awareness of.

Seeing is believing

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