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

A year ago, we looked at the user research market and made a decision.

‍

We saw product teams shipping faster than ever while research tools stayed stuck in time. We saw researchers drowning in manual work, waiting on vendor emails, stitching together fragmented tools. We heard "should we test this?" followed by "never mind, we already shipped."

‍

The dominant platforms got comfortable. We didn't.

‍

Today, we're excited to announce Optimal 3.0, the result of refusing to accept the status quo and building the fresh alternative teams have been asking for.

‍

The Problem: Research Platforms Haven't Evolved

‍

The gap between product velocity and research velocity has never been wider. The situation isn't sustainable. And it's not the researcher's fault. The tools are the problem. They’re: 

‍

• Built for specialists only - Complex interfaces that gatekeep research from the rest of the team
• Fragmented ecosystems - Separate tools for recruitment, testing, and analysis that don't talk to each other
• Data in silos - Insights trapped study-by-study with no way to search across everything
• Zero integration - Platforms that force you to abandon your workflow instead of fitting into it

‍

These platforms haven't changed because they don't have to, so we set out to challenge them.

‍

Our Answer: A Complete Ecosystem for Research Velocity

‍

Optimal 3.0 isn't an incremental update to the old way of doing things. It's a fundamental rethinking of what a research platform should be.

‍

Research For All, Not Just Researchers.

‍

For 18 years, we've believed research should be accessible to everyone, not just specialists. Optimal 3.0 takes that principle further.

‍

Unlimited seats. Zero gatekeeping.

‍

Designers can validate concepts without waiting for research bandwidth. PMs can test assumptions without learning specialist tools. Marketers can gather feedback without procurement nightmares. Research shouldn't be rationed by licenses or complexity. It should be a shared capability across your entire team.

‍

A Complete Ecosystem in One Place.

‍

Stop stitching together point solutions.Optimal 3.0 gives you everything you need in one platform:

‍

Recruitment Built In Access millions of verified participants worldwide without the vendor tag. Target by demographics, behaviors, and custom screeners. Launch studies in minutes, not days. No endless email chains. No procurement delays.

‍

Learn more about Recruitment

‍

Testing That Adapts to You

‍

• Live Site Testing: Test any URL, your production site, staging, or competitors, without code or developer dependencies
• Prototype Testing: Connect Figma and go from design to insights in minutes
• Mobile Testing: Native screen recordings that capture the real user experience
• Enhanced Traditional Methods: Card sorting, tree testing, first-click tests, the methodologically sound foundations we built our reputation on

‍

Learn more about Live Site Testing

‍

AI-Powered Analysis (With Control) Interview analysis used to take weeks. We've reduced it to minutes.

‍

Our AI automatically identifies themes, surfaces key quotes, and generates summaries, while you maintain full control over the analysis.

‍

As one researcher told us: "What took me 4 weeks to manually analyze now took me 5 minutes."

‍

This isn't about replacing researcher judgment. It's about amplifying it. The AI handles the busywork, tagging, organizing, timestamping. You handle the strategic thinking and judgment calls. That's where your value actually lives.

‍

Learn more about Optimal Interviews

‍

Chat Across All Your Data Your research data is now conversational.

‍

Ask questions and get answers instantly, backed by actual video evidence from your studies. Query across multiple Interview studies at once. Share findings with stakeholders complete with supporting clips.

‍

Every insight comes with the receipts. Because stakeholders don't just need insights, they need proof.

‍

A Dashboard Built for Velocity See all your studies, all your data, in one place. Track progress across your entire team. Jump from question to insight in seconds. Research velocity starts with knowing what you have.

‍

Explore the new dashboard

‍

Integration Layer

‍

Optimal 3.0 fits your workflow. It doesn't dominate it. We integrate with the tools you already use, Figma, Slack, your existing tech stack, because research shouldn't force you to abandon how you work.

‍

What Didn't Change: Methodological Rigor

‍

Here's what we didn't do: abandon the foundations that made teams trust us.

‍

Card sorting, tree testing, first-click tests, surveys, the methodologically sound tools that Amazon, Google, Netflix, and HSBC have relied on for years are all still here. Better than ever.

‍

We didn't replace our roots. We built on them.

‍

18 years of research methodology, amplified by modern AI and unified in a complete ecosystem.

‍

Why This Matters Now

‍

Product development isn't slowing down. AI is accelerating everything. Competitors are moving faster. Customer expectations are higher than ever.

‍

Research can either be a bottleneck or an accelerator.

‍

The difference is having a platform that:

‍

• Makes research accessible to everyone (not just specialists)
• Provides a complete ecosystem (not fragmented point solutions)
• Amplifies judgment with AI (instead of replacing it)
• Integrates with workflows (instead of forcing new ones)
• Lets you search across all your data (not trapped in silos)

‍

Optimal 3.0 is built for research that arrives before the decision is made. Research that shapes products, not just documents them. Research that helps teams ship confidently because they asked users first.

‍

A Fresh Alternative

‍

We're not trying to be the biggest platform in the market.

‍

We're trying to be the best alternative to the clunky tools that have dominated for years.

‍

Amazon, Google, Netflix, Uber, Apple, Workday, they didn't choose us because we're the incumbent. They chose us because we make research accessible, fast, and actionable.

‍

"Overall, each release feels like the platform is getting better." — Lead Product Designer at Flo

‍

"The one research platform I keep coming back to." — G2 Review

‍

What's Next

‍

This launch represents our biggest transformation, but it's not the end. It's a new beginning.

‍

We're continuing to invest in:

‍

• AI capabilities that amplify (not replace) researcher judgment
• Platform integrations that fit your workflow
• Methodological innovations that maintain rigor while increasing speed
• Features that make research accessible to everyone

‍

Our goal is simple: make user research so fast and accessible that it becomes impossible not to include users in every decision.

‍

See What We've Built

‍

If you're evaluating research platforms and tired of the same old clunky tools, we'd love to show you the alternative.

‍

Book a demo or start a free trial

‍

The platform that turns "should we?" into "we did."

‍

Welcome to Optimal 3.0.

‍

User interviews have always been one of the most trusted and powerful UX research methods. They give you something beyond dashboards or written surveys: real, in-depth conversations and context.

‍

But they’ve historically come with a cost – time, coordination, and a heavy lift to review recordings and turn videos into insights. Sometimes insights get buried. Recordings sit unused and research becomes challenging to revisit.

‍

In our recent webinar, we explored how that’s changing and how you can reduce the heavy lift of interview review, while building a research repository. 

‍

‍

What is a research repository?

A research repository is a centralized system for storing, analyzing, and reusing research data, especially qualitative data like user interviews. It helps teams answer questions like what users said, what patterns emerged, and how past research can inform future decisions.
‍

For interviews, this means:

• Storing recordings and transcripts
• Organizing insights and themes
• Making research searchable
• Enabling teams to revisit past findings
• Supporting continuous discovery
  ‍

Optimal Interviews brings this to life by automatically capturing recordings, generating transcripts, structuring insights from the start, and making everything searchable so teams can easily revisit, build on, and continuously learn from their research.
‍

So what did we learn? Here are some key takeaways from this webinar, plus answers to the most common questions we heard.
‍
‍

1. The biggest bottleneck isn’t conducting interviews. It’s everything surrounding it.

Running interviews isn’t just about talking to users. It’s everything before and after:

• Recruiting participants
• Coordinating calendars
• Managing reschedules and no-shows
• Setting up emails and reminders
• Transcribing, organizing, and synthesizing findings
  ‍

That overhead adds up quickly. There’s opportunity in automating these workflows and removing the friction around them. Optimal Interviews solves this by:
‍

• Creating a central calendar
• Emailing participants with confirmations and session reminders
• Automatically capturing recordings
• Generating transcripts
• Uploading and generating summaries and insights
• Structuring insights from the start
• Allowing you to explore instantly with AI Chat
  ‍
  ‍

2. Speed matters more than ever (and it’s finally achievable)

Research isn’t slowing down. Product cycles are getting faster, and teams expect insights just as quickly.

What stood out most:

• Interviews can now go from recording → transcript → insights in minutes
• Teams can share highlight reels, clips and findings almost immediately
• Analysis can start while context is still fresh
  ‍

One team told us that a few years ago it took them three weeks to analyze user interviews for an initiative. When they replicated the same study in Optimal Interviews, they were able to generate usable insights in about five minutes.
‍

That shift from lagging insight to near real-time understanding is where the real impact lies.

‍

3. Scheduling should feel effortless

Interview scheduling sounds simple, but it’s often where things break down.
You can use Optimal Interviews to ensure:
‍

• Availability blocks with buffers
• Controlled rescheduling and cancellations
• Video conferencing integrations
• Support for collaborators
• Built-in, secure participant communication & messaging (coming soon)
  ‍

When done right, scheduling fades into the background so teams can focus on conversations, not coordination.
‍
‍

4. AI is reshaping analysis but humans stay in control

AI is already proving its value in the analysis phase:

• Automatic transcription across multiple languages
• Theme and insight extraction across interviews
• Highlight reels and supporting evidence
• Natural language queries over your research
  ‍

But one point came through clearly: AI accelerates analysis but it doesn’t replace human judgment and sensitivity.
‍

Researchers still play a critical role in validating insights, interpreting nuance, and deciding what matters for the business. Think of AI as getting you to 80% faster, while you own the final 20%.

‍

5. The real unlock is continuous, reusable research

Here’s what you can achieve with Optimal Interviews:

• You can ask questions of past interviews using natural language
• Create new custom themes or topics on demand for AI to add new insights into
• Re-analyze old research with fresh context
• Add new interviews to your existing Optimal Interviews study and refresh the insights
• Identify gaps and spin up new studies faster
  ‍

This turns research from static storage into something dynamic, something you can continuously mine and build on.
‍
‍

FAQs from the Webinar

Does the platform synthesize insights or just aggregate data?

Both. You can extract insights from individual interviews, but the real value often comes from patterns across multiple sessions. Aggregation helps surface stronger, more reliable themes, while still preserving standout moments from single participants.
‍

How is sensitive data handled?

Privacy is a core focus and consideration with Optimal Interviews. Some of the key protections include automatic redaction of personally identifiable information (PII) and enterprise-grade AI infrastructure with strict data isolation. We're also looking to expand Optimal Interviews anonymized scheduling and communication and manual redaction controls before analysis.
‍

What if I can’t connect my video conferencing tools?

Integrations are available for Google Meet, Microsoft Teams, and Zoom. 

You can still run everything without integrations:

• Set availability without integrations
• Add conferencing links yourself
• Manage sessions independently
  ‍

Integrations are helpful but not required.
‍

Can I search across multiple studies?

Today, teams often bring relevant interviews into one project for analysis. Looking ahead, the goal is broader. Optimal’s looking into how the platform can search and query across all research, use AI chat to explore insights across studies, and surface insights at a Workspace level.
‍

Can I query transcripts or AI summaries?

Yes. You can search transcripts directly and use AI-powered chat to explore themes, generate summaries, or even turn findings into shareable outputs like Slack posts or reports.

‍

Final thought

Interviews aren’t new. But the way we run them and what we can get out of them is changing fast.

By removing operational overhead and reducing time to insight, teams can talk to users more often, share insights faster, and build a research repository that becomes part of everyday product decision-making.
‍

If you want to experience the full walkthrough, demo, and Q&A from the session, we encourage you to watch the full webinar.
‍

👉 You can watch the full training webinar here.

When evaluating tools for user testing and participant recruitment, Askable often appears on the shortlist, especially for teams based in Australia and New Zealand. But in 2025, many researchers are finding Askable’s limitations increasingly difficult to work around: restricted study volume, inconsistent participant quality, and new pricing that limits flexibility.

‍

If you’re exploring Askable alternatives that offer more scalability, higher data quality, and global reach, here are five strong options.

‍

‍

1. Optimal: Best Overall Alternative for Scalable, AI-Powered Research 

‍

Optimal is a comprehensive user insights platform supporting the full research lifecycle, from participant recruitment to analysis and reporting. Unlike Askable, which has historically focused on recruitment, Optimal unifies multiple research methods in one platform, including prototype testing, card sorting, tree testing, and AI-assisted interviews.

‍

Why teams switch from Askable to Optimal

‍

1. You can only run one study at a time in Askable

‍Optimal removes that bottleneck, letting you launch multiple concurrent studies across teams and research methods.

2. Askable’s new pricing limits flexibility 

Optimal offers scalable plans with unlimited seats, so teams only pay for what they need.

3. Askable’s participant quality has dropped

Optimal provides access to over 100+ million verified participants worldwide, with strong fraud-prevention and screening systems that eliminate low-effort or AI-assisted responses.

‍

Additional advantages

‍

• End-to-end research tools in one workspace
• AI-powered insight generation that tags and summarizes automatically
• Enterprise-grade reliability with decade-long market trust
• Dedicated onboarding and SLA-backed support
  
  

‍

Best for: Teams seeking an enterprise-ready, scalable research platform that eliminates the operational constraints of Askable.

‍

‍

‍

2. UserTesting: Best for Video-Based Moderated Studies

‍

‍UserTesting remains one of the most established platforms for moderated and unmoderated usability testing. It excels at gathering video feedback from participants in real time.

‍

Pros:

• Large participant pool with strong demographic filters
• Supports moderated sessions and live interviews
• Integrations with design tools like Figma and Miro

‍

Cons:

• Higher cost at enterprise scale
• Less flexible for survey-driven or unmoderated studies compared with Optimal
• The UI has become increasingly complex and buggy as UserTesting has been expanding their platform through acquisitions such as UserZoom and Validately.
  ‍

‍

Best for: Companies prioritizing live, moderated usability sessions.

‍

‍

‍

3. Maze: Best for Product Teams Using Figma Prototypes

‍

‍Maze offers seamless Figma integration and focuses on automating prototype-testing workflows for product and design teams.

‍

‍

Pros:

• Excellent Figma and Adobe XD integration
• Automated reporting
• Good fit for early-stage design validation

‍

Cons:

• Limited depth for qualitative research
• Smaller participant pool
  
  

‍

Best for: Design-first teams validating prototypes and navigation flows.

‍

‍

‍

4. Lyssna (formerly UsabilityHub): Best for Fast Design Feedback

‍

‍Lyssna focuses on quick-turn, unmoderated studies such as preference tests, first-click tests, and five-second tests.

‍

Pros:

• Fast turnaround
• Simple, intuitive interface
• Affordable for smaller teams

‍

Cons:

• Limited participant targeting options
• Narrower study types than Askable

‍

Best for: Designers and researchers running lightweight validation tests.

‍

‍

‍

5. Dovetail: Best for Research Repository and Analysis

‍

‍‍Dovetail is primarily a qualitative data repository rather than a testing platform. It’s useful for centralizing and analyzing insights from research studies conducted elsewhere.

‍

Pros:

• Strong tagging and note-taking features
• Centralized research hub for large teams

‍

Cons:

• Doesn’t recruit participants or run studies
• Requires manual uploads from other tools like Askable or UserTesting
  
  

‍

Best for: Research teams centralizing insights from multiple sources.

‍

‍

‍

Final Thoughts on Alternatives to Askable

‍

If your goal is simply to recruit local participants, Askable can still meet basic needs. But if you’re looking to scale research in your organization, integrate testing and analysis, and automate insights, Optimal stands out as the best long-term investment. Its blend of global reach, AI-powered analysis, and proven enterprise support makes it the natural next step for growing research teams. You can try Optimal for free here.

‍