Simplify Your Workflow with the Interviews Scheduler & Seamless Calendar & Video Integrations

The pace of product development has never been faster, and the cost of building on assumptions has never been higher. At Optimal, we've spent nearly two decades helping teams get closer to their users, and what we're seeing right now is a fundamental shift in how research gets done. More teams are running research than ever before and timelines to act on findings are tighter, while the expectations for what research needs to deliver keep rising. 

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That shift is exactly what's driving Optimal 3.0, our most ambitious reinvention of the platform yet, designed to give every team the speed, depth, and flexibility that modern research demands. Today's release is the next step in that journey.

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Optimal's new mixed-methods research tool tears down the boundaries between methods. It brings prototype testing, live site testing, and surveys into a single, end-to-end study workflow. And grounded in our product principles: speed to insights, access for all, and communication. 
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A Unified Way to Test Usability
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True multi-method research

Optimal’s new Usability Testing tool marks the next step in the evolution of Optimal 3.0, giving teams the flexibility to evaluate experiences in whatever form they exist today.
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• Early-stage ideas and concepts
• Interactive prototypes
• AI-generated or experimental flows
• Live production experiences
• Competitor or benchmark sites
• Surveys and structured feedback
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Combine prototype testing, AI prototype testing, live site testing, and surveys in a single study. Test multiple prototypes side by side, compare different live URLs, or mix prototype and live site tasks together all in one workflow. Research can now mirror how products actually evolve, from early concept to shipped experience.
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Richer qualitative insight collection

New speak-aloud question types, custom message blocks, auto-generated transcripts and insights, citations and highlight clips help you capture the context and reasoning behind every action. AI-assisted analysis then helps you make sense of it all fast and communicate with impact.
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A redesigned results and insights layer

Review a study overview surfacing key themes, pain points, and sentiment analysis combining insights across all your study methods along with detailed results, task analysis and recordings, transcripts, key quotes, and automatically generated citations and video clips. 

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Coming soon: you can also use AI Chat to chat with your data directly, asking questions and pulling new insights and evidence across all your qualitative and quantitative inputs.

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Six ways to put it to work

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1. Compare design variations in a single study, such as multiple navigation layouts, checkout flows, or onboarding concepts
2. Explore early-stage concepts before committing to build
3. Benchmark current live experience vs a redesigned prototype
4. Test staging vs production, or two campaign landing pages
5. Validate end-to-end journeys from concept to live experiences
6. Compare your experience against competitors‍

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Why this matters

Modern product development is no longer linear. Teams continuously move between:
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• Discovery and validation
• Design and iteration
• Prototype and production
• Concept and reality
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Traditional usability testing tools were not built for this fluidity.  Optimal’s Usability Testing brings the flexibility to match how teams actually work today.

By combining multiple methods into a single study and pairing it with AI-powered synthesis, Usability Testing helps teams reduce setup and analysis time, recruit once, capture richer qualitative context, compare experiences more easily, move faster from feedback to action, and tell clearer, more compelling insight stories. 
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Learn how to get started with Usability Testing in Optimal and accelerate your path from idea to insight. Book a meeting, start exploring in your account, or join our live training webinar on June 24th to see it in action.

Collaboration tools like Mural, FigJam, and Miro are staples of how modern teams can brainstorm, map ideas, align on plans, and build together. But a canvas alone can't tell you if you're on the right track or guide you to what comes next when progress stalls. That's where Optimal AI Chat and user insights come in.

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By starting or bringing real user insights into the boards your team already works in, you can reduce ambiguity, ground discussions in real research, and accelerate decision-making. 

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Here are 7 ways to use AI Chat alongside your collaboration boards.

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1. Align on key objectives

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Before your next planning session, use Optimal AI Chat to surface relevant insights from your interview recordings. Add a summary directly into your Mural, Miro, or FigJam board so everyone comes in with the same context and understanding of the objectives. Instead of starting with assumptions, your team can start with real user insights and clear trade-offs to discuss.
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Try this prompt: "Summarize the key considerations for [decision topic] and flag any trade-offs we should discuss as a team."
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2. Create a user journey map

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AI Chat can analyze interview transcripts and video recordings and highlight common jobs to be done, behaviors, and friction points. You can then map those steps visually on your board and identify where the experience breaks down.
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Try these prompts: “Summarize the typical jobs to be done for the people we interviewed.”
“For this job you identified [paste job details], detail the journey steps.” 

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3. Turn pain points into design and product decisions

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AI Chat can analyze recurring themes from your interview recordings and convert them into concrete opportunities your team can explore next. Adding these to your board gives the team a clear starting point rather than a vague list of problems.
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Try this prompt:  "Based on these pain points [paste notes or themes], suggest three product improvements we could explore."

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4. Sharpen your marketing messaging

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Interview insights aren’t just valuable for product, research, and design teams. Marketing teams can also use AI Chat to quickly evaluate messaging, positioning, and customer perception.

When running preference or concept testing interviews, AI Chat can quickly analyze the feedback and suggest positioning directions you can workshop on your board.
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Try this prompt: “Suggest positioning options based on the interview feedback.”

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5. Facilitate workshops

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Running workshops and brainstorming sessions with cross-functional teams can be challenging. Conversations drift, discussions stall, and teams sometimes struggle to focus on the most important issues. 
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AI Chat can help you structure the conversation before the workshop even begins by generating discussion guides based on user insights from your interviews. Add the chat outputs directly to your board to guide the session.
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Try this prompt: “Generate a structured discussion guide based on the pain points of the interviewees.”


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6. Make brainstorming more focused

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Open brainstorming can be valuable. It can also be chaotic without clear direction. By leveraging AI Chat, you can guide your brainstorming sessions with intelligent suggestions, topic generation, and idea organization.
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Try this prompt: “Generate 10 brainstorm ideas based on these user insights and group them into themes we could explore.”

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7. Map complex processes

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Visualizing complex processes and systems is easier with tools like Miro, FigJam, and Mural. AI Chat can help you map out each step. AI Chat can help break down a process step-by-step, highlighting decisions, dependencies, and potential friction points based on your interviews. Your team can then map these steps visually and identify opportunities for improvement.
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Try this prompt: “Create a step-by-step process map for how users complete [task], including key decisions and potential friction points.”

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Using Optimal AI Chat for seamless collaboration

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The best collaboration happens when teams have the right information at the right time. 

Optimal AI Chat gives your team a jumpstart for your interview analysis: clearer inputs, faster synthesis, and smarter outputs that translate directly into what you're building on your boards.

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Whether you're running a workshop, mapping a user journey, or planning a product launch, AI Chat helps you spend less time getting oriented and more time making decisions.
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Ready to see what your team can do with it?
Learn more about best practices for AI Chat or book a demo. 

Nearly 18 years ago, Optimal helped define what UX research could be, pioneering practices and tools that would become industry standard and change how teams worldwide better understand their users. As the industry has evolved, so has Optimal, expanding the platform, advancing participant recruitment, and building Optimal Intelligence AI to accelerate insight to action.
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Now, we’re at the edge of another major shift. With the launch of the Model Context Protocol (MCP), we’re entering a new realm, moving from traditional research workflows to AI-powered intelligence.
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What is MCP (Model Context Protocol)?

Research data is one of the most valuable assets in any organization, but until now, it has been scattered across studies and reports, time-consuming to search and synthesize, and different to search or reuse. MCP now changes that for research teams. 
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Model Context Protocol (MCP) enables you to connect your Optimal research directly to AI tools, like ChatGPT, Claude, or Cursor, to explore and analyze your data seamlessly. Insights can go beyond data downloads, dashboards, or static reports. Access your insights and explore further with natural conversation.
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Get instant insights for questions like: 
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• “Based on all the research I’ve run in Optimal, what are the biggest UX opportunities for our product?” 
• “What usability issues have been identified by studies conducted in the past 3 months?”
• “What themes appear across onboarding studies?”
• “What research already exists about navigation improvements?”
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What MCP Unlocks (Beyond Search)

With MCP-connected tools, you can:
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• Analyze studies: Understand patterns, findings, and trends across research automatically.
• Cross-study synthesis: Identify recurring themes across multiple studies in seconds.
• Pull key insights: Extract findings from individual studies without manual review.
• Search & explore research: Filter studies by creator, title, participant group, or timeframe.
• Analyze transcript insights & sessions: Surface usability issues, pain points, and behavioral patterns.
• Turn insights into deliverables: Automatically format findings into summaries and stakeholder-ready outputs. Get more ideas here.
• Connect with other tools & workflows: Use MCP along with your AI tool's existing integrations to create alerts and automate next steps e.g. create a Slack notification when a participant completes a study, share milestones, create a JIRA ticket and follow-up tasks.
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From Early UX Research to AI-Native Intelligence

The evolution is clear.

We started by helping teams understand users through early UX research methods.
We helped formalize how research is conducted, analyzed, and shared.
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And now, with MCP in Optimal, we’re helping teams move beyond analysis altogether toward conversational, AI-driven research intelligence.
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Log in to Optimal, connect with your AI tools, and get the most value from your research or book a demo to start building your research repository with Optimal.