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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 Limitations

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

Prototype Testing Capabilities

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

Analysis and Reporting Quality

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

Enterprise Features

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

Enterprise Readiness

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

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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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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1 min read

Optimal vs Lyssna: Why Enterprise Teams Need Enterprise-Ready Platforms

The choice between comprehensive research platforms and tools designed for smaller teams becomes increasingly critical as research and product teams work to scale their user insight capabilities. This decision impacts not only immediate research outcomes but also long-term strategic planning and organizational growth. While platforms like Lyssna focus on rapid feedback collection and quick turnaround times which are valuable for teams needing fast validation, Optimal delivers the depth, reliability, and enterprise features that the world's biggest brands require to make strategic product decisions.

Why do teams choose Optimal instead of Lyssna?

Speed vs. Comprehensive Insights

  • Lyssna's Speed Focus: Lyssna optimizes for quick feedback collection with simple testing workflows, but lacks AI-powered analysis, advanced reporting, and the sophisticated insights enterprise research programs require for strategic decision-making.
  • Optimal's Comprehensive Approach: Optimal combines speed with depth, delivering rapid study launch alongside AI-powered analysis, detailed reporting, and enterprise-grade insights that transform user feedback into actionable business intelligence.
  • Limited Enterprise Features: Lyssna operates as a testing tool rather than an enterprise platform, lacking the compliance, security, and support infrastructure global brands require for mission-critical research programs.
  • Trusted by Global Brands: Optimal serves enterprise clients including Lego, Nike, and Amazon with SOC 2 compliance, global security protocols, and dedicated enterprise support that meets Fortune 500 requirements.

Participant Quality and Global Reach

  • Limited Panel Reach: Lyssna's approximately 700,000 participant panel restricts targeting options and geographic coverage, particularly for niche audiences or international research requirements.
  • Global Participant Network: Optimal's 100+ million verified participants across 150+ countries enable sophisticated audience targeting, global market research, and reliable recruitment for any demographic or geographic requirement.
  • Quality Control Issues: Users report that Lyssna participants often don't match requested criteria, compromising study validity and requiring additional screening overhead.
  • Verified Participant Quality: Optimal implements comprehensive fraud prevention, advanced screening protocols, and quality assurance processes that ensure participant authenticity and criteria matching for reliable research results.

Advanced Features and Platform Capabilities

  • Manual Analysis Required: Lyssna provides basic reporting without integrated AI tools, requiring teams to manually analyze results and generate insights from raw data.
  • AI-Powered Insights: Optimal includes sophisticated AI analysis tools that automatically generate insights, identify patterns, and create actionable recommendations from research data.
  • Self-Service Only: Lyssna operates exclusively as a self-service platform without managed recruitment options for teams requiring specialized audience targeting or complex demographic requirements.
  • Full-Service Flexibility: Optimal provides both self-service and white-glove managed recruitment services, accommodating varying team resources and research complexity with dedicated support for challenging recruitment scenarios.
  • Simple but Limited: While Lyssna offers a straightforward interface, this simplicity comes with functional limitations that restrict test design flexibility and advanced research capabilities.
  • Sophisticated Yet Accessible: Optimal balances powerful functionality with intuitive design, providing guided templates and automation features that enable complex research without overwhelming users.

When to Choose Lyssna

Lyssna may suffice for teams with:

  • Basic testing needs without strategic implications
  • Limited budgets prioritizing low cost over comprehensive features
  • Simple research requirements without compliance needs
  • Acceptance of limited participant quality and geographic reach

When to Choose Optimal

Optimal becomes essential for:

  • Strategic Research Programs: When user insights drive business strategy
  • Global Organizations: Requiring international research capabilities
  • Quality-Critical Studies: Where participant verification and data integrity matter
  • Enterprise Compliance: Organizations with security and compliance requirements
  • Advanced Analysis Needs: Teams requiring AI-powered insights and sophisticated reporting
  • Scalable Research Operations: Growing programs needing comprehensive platform capabilities

Why Enterprises Need to Prioritize Enterprise Research Excellence

While Lyssna serves basic testing needs, enterprise research requires the depth, reliability, and global reach that only comprehensive platforms provide. Optimal delivers speed without sacrificing the sophisticated capabilities enterprise teams need for strategic decision-making. Don't compromise research quality for simple, quick tools.

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

Optimal vs Askable: Why an All-in-One Platform is a Better Choice than Niche Tools

When selecting user research and insight tools, product and design teams must decide between two distinct approaches: investing in multiple niche tools that address specific parts of the user research workflow, such as Askable for participant recruitment, or choosing a comprehensive platform like Optimal that supports the entire product development lifecycle from research planning through to insight.

Why choose Optimal instead of Askable?

Recruitment-Only Tools vs. Comprehensive User Research Platforms

Platform Scope and Capabilities

  • Askable's Limitations: Askable specializes exclusively in participant recruitment, requiring teams to integrate multiple third-party tools for testing, analysis, and insight generation. This fragmented approach creates workflow friction and increases project complexity.
  • Optimal's Advantage: Optimal delivers recruitment, testing, and analysis within a single platform. Teams can recruit participants, conduct UX tests, analyze results, and generate insights without switching between tools or managing multiple vendor relationships.

Global Reach and Participant Quality

  • Regional Limitations: Askable's participant panel concentrates heavily in Australia and New Zealand, limiting global research capabilities. For enterprises requiring international insights, this geographic constraint becomes a significant bottleneck.
  • Worldwide Coverage: Optimal partners with 100+ million verified participants across 150+ countries, enabling global research at scale. Advanced fraud prevention and screening protocols ensure participant quality regardless of location.

Pricing Structure and Cost Predictability

  • Variable Costs: Askable employs credit-based pricing that scales with session length, making long-form research sessions increasingly expensive and budget planning difficult.
  • Transparent Pricing: Optimal offers flat-rate pricing regardless of session duration, eliminating hidden fees and enabling predictable research budgets for extended studies.

Why Enterprises Choose Optimal Over Askable

  1. Operational Efficiency. Teams using Askable must coordinate between recruitment services and separate testing platforms, creating project management overhead. Optimal eliminates this complexity by providing integrated recruitment and testing capabilities.
  2. Advanced Research Capabilities. While Askable focuses on participant recruitment, Optimal includes: Built-in UX testing tools, AI-powered analysis and insights, Automated reporting and visualization, Survey and prototype testing capabilities
  3. Enterprise-Grade Support. Optimal provides dedicated account management and comprehensive fraud prevention assurance, whereas Askable offers standard support options without the specialized enterprise features global brands require.
  4. Scalability for Growing Teams. Askable's recruitment-only model doesn't scale with research program maturity. As teams need more sophisticated testing and analysis capabilities, they must invest in additional tools. Optimal grows with research programs from basic recruitment through advanced insight generation.

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.

Seeing is believing

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