Optimal Blog

We recently hosted a live webinar introducing Optimal's new Usability Testing tool which combines multiple research methods into one study so you can get better insights, faster. 

‍

‍

‍

What is Usability Testing?

‍

‍

Optimal's new Usability Testing tool is a mixed-methods research tool that brings Prototype Testing, Live Site Testing, and Surveys into a single, end-to-end study workflow. Instead of treating each method as its own initiative, you can combine them inside a single study to allow participants to move naturally between tasks, experiences, and questions.

‍

With this tool, you can compare multiple prototypes side by side, benchmark a current live experience against a redesigned concept, evaluate a competitor's experience, and more. And researchers get everything analyzed in one place with AI-powered summaries, task results, video clips, and evidence-backed insights surfaced automatically.

‍

These are some of the top questions we heard at our recent live training as a recap in case you missed it!

‍

‍

‍

FAQs from the Webinar

‍

Is Usability Testing supported for mobile testing?

‍

Yes, participants can complete Usability Testing studies on mobile devices using their mobile browser or the Optimal Participant App. If screen recording is required, participants are prompted to download the Optimal Participant App, available for both iOS and Android. 

‍

Do you have to use multiple methods, or can you run just one?

‍

You can keep it simple and run a single survey, a standalone prototype test, or a live site session on its own. Or, mix methods or run multiple of the same method, such as multiple prototypes or live website tests in one study. The tool supports however your study needs to be shaped.

‍

Can you run bilingual studies?

‍

Usability Testing currently supports over 30 languages enabling what participants see and guiding how AI models interpret responses, generate summaries, identify themes, and surface insights. Today, studies are configured around a single language, so participants are expected to respond in the chosen language. That said, multilingual study support is something we're exploring for our roadmap.

‍

Are participants recruited once across all methods, or separately for each?

‍

Just once. From the participant's perspective, this looks and feels like a single study regardless of how many methods are included. They move through the experience naturally from start to finish.

‍

To what extent can sections and questions be randomized?

‍

Section-level randomization shuffles the order of any sections, while question-level randomization works within a specific section, shuffling the order of tasks and follow-up questions. Both are supported, giving researchers the flexibility to reduce order bias, particularly useful when comparing multiple experiences.

‍

Can you test multiple prototypes within the same study?

‍

Yes, with no limitations on the number of prototypes you can link to a single study so you can add multiple Figma prototype sections and connect a different prototype to each one.

‍

Can you reorder sections and questions in a study?

‍

Given that Usability Testing studies can grow complex, the ability to reorder things quickly was a priority. You can reorder individual tasks and questions within a section, and sections themselves by dragging them in the Build panel.

‍

How effectively can Usability Testing scale across a business?

‍

Scaling research isn't just about running more studies, it's about helping more people across the business access insights, understand them, and use them to make decisions. With Usability Testing, product managers, designers, and stakeholders can quickly understand what happened and why without having to see hours of recording through the automatically generated highlight reels, key quotes, and transcripts.

‍

Watch the full webinar

‍

If you want to experience the full walkthrough, demo, and Q&A, watch the recording to see Usability Testing in action and pick up tips and best practices straight from the session.

👉 Watch the full webinar here.

‍

Coordinating user interviews shouldn’t feel like a full-time job. Between juggling calendars, chasing confirmations, and sending reminders, scheduling can be the hidden bottleneck in research velocity and quietly consume the time you actually want to spend talking to customers. 
‍

If you want to run more interviews and generate insights more consistently, simplifying your scheduling process is one of best ways to remove friction and streamline your workflow.
‍

‍

‍

Save time and streamline your workflow

‍

What does a simpler workflow look like? 

With a tool like Optimal’s Interviews Scheduler, you can:
‍

• Invite participants via a booking link or email
• View upcoming and completed sessions in one place
• Connect with tools you already use like Google Calendar, Microsoft Outlook, Google Meet, Zoom, and Microsoft Teams.
• Let participants reschedule themselves. No back-and-forth emails.
• Add collaborators and automatically notify everyone of changes.
• Set session limits and calendar buffers.
• Automate email invites, reminders, confirmations, and thank-you messages.
  ‍

It’s everything you need to manage interviews without the chaos.
‍
‍

‍

Calendar integrations: Avoid conflicts and save time

With the Interviews Scheduler, you can sync your availability with Google Calendar and Microsoft Outlook in real time. Connect your own calendar or your team’s to ensure every busy slot is accounted for. Avoid double bookings, block out busy times, and keep everything in one place. 

Once set up, your availability automatically updates, and participants can book directly into open slots, eliminating the back-and-forth. Plus, depending on your preferences, your sessions will either sync directly to your calendar or come through as an .ics file in the confirmation email, saving you one more step.
‍

‍
‍

Seamless video conferencing integrations

The Interviews Scheduler integrates directly with Zoom, Microsoft Teams, and Google Meet.

When someone books a session:

• A video link is automatically generated
• It’s added to the calendar invite
• Everyone receives confirmation details
• Sessions can be automatically recorded

No copying links. No switching between tools.
‍

‍
‍

Built for research teams

‍

The Interviews Scheduler isn’t just about booking time slots. It’s about removing friction from your research workflow.

‍

With integrations at its core, you can:

• Keep your calendar, video tools, and participants in sync
• Reduce manual coordination
• Eliminate scheduling errors
• Focus on insights instead of admin

‍

Whether you’re running one-off interviews or managing weekly research sprints, the Interviews Scheduler helps you move faster and stay organised.

‍

Ready to give it a try? Log in to your Optimal account and get started or book a demo to learn more.

‍

So, you’re ready to run a study. It’s designed, you’ve planned your questions, your methodology is sound. Your discussion guide is carefully crafted to avoid leading questions and dig into real user motivations…then you start recruiting participants.

‍

Suddenly, you’ve hit a massive bottleneck. Your perfect study depends entirely on finding the right people, getting them to show up, and hoping they provide thoughtful responses rather than one-word answers and distracted multitasking. You’ve now hit the crunch point that every researcher faces: your insights are only as good as your participants. What happens when participant quality isn’t great? 

‍

‍

‍

The hidden cost of "good enough"

‍

‍

Let's be honest about what typically happens with recruitment. You need a minimum number of participants to get statistically significant results (depending on study type). You’ve got a time limit in which you need to get results so they’re still relevant to your product development lifecycle. You start reaching out through your usual channels: customer lists, screening surveys, panel providers, social media posts, begging colleagues to connect you with people who fit your criteria. 

‍

After a week of this, you've got a few confirmed participants, but not enough. Some people have expressed interest but haven't confirmed times and it’s teeming more and more like your study is going to launch late, and you’re going to miss product deadlines. 

‍

So you make compromises.

‍

You accept the participant who sort of fits your criteria but isn't quite in the target demographic. You take the person who can only do a 30-minute session instead of the planned 60 minutes. You keep the flaky participant who's rescheduled twice because you need the numbers. 

‍

Then the sessions happen.

‍

One person no-shows. Another is clearly distracted, giving minimal responses while probably checking email. A third seems to have misunderstood the screening criteria entirely and doesn't actually use the type of product you're researching. The two good participants provide valuable insights, but now you're making conclusions based on a sample size of two.

‍

This isn't research. This is educated guessing with extra steps.

‍

‍

‍

What bad participants cost you

‍

‍

1. Quality  In, Quality Out. Poor participant quality isn't just annoying. It has real consequences that ripple through everything that comes after. The worst outcome isn't getting no data. It's getting bad data that you treat as good data. A participant who doesn't match your target users provides feedback, but that feedback doesn't represent your actual users. If you act on it, you're optimizing for the wrong people. Bad data doesn't just waste research time. It sends product decisions in the wrong direction. 
2. Wasted team time. You spend hours recruiting, scheduling, conducting sessions, and analyzing results. When the research is based on poor-quality participants, all of that time is wasted. Or worse, it's spent acting on misleading information. One bad research study doesn't just cost the time invested in that study. It costs the time spent implementing the wrong solutions based on faulty insights.
3. Damaged credibility. Research teams build credibility over time by providing insights that prove valuable. Stakeholders learn to trust research because it leads to better decisions. But credibility is fragile. When research based on poor participants leads to recommendations that don't pan out, stakeholders start questioning whether research is worth the investment. 
4. Slower velocity. Settling for mediocre participants to move faster actually slows you down. You run your study quickly with whoever you can find. The insights are muddy. You're not quite sure what to conclude. So you run a follow-up study to clarify. Or you make a decision with low confidence and have to course-correct later when it doesn't work. Meanwhile, teams that spend time getting quality participants upfront get clear insights the first time. They make decisions confidently and move forward quickly because they trust what they learned. The bottleneck isn't the time spent recruiting quality participants. It's the back-and-forth that comes from unclear results based on poor participants.

‍

‍

‍

What do we really mean by quality participants? 

‍

‍

When you're under pressure to deliver research quickly, it's tempting to view participants as interchangeable. You need 8 people. Any 8 people who vaguely fit the criteria will do. But that’s not actually the case at all. The whole point of user research is to understand your specific users. Their context, their mental models, their workflows, their pain points. Generic "users" don't exist. There are only specific people with specific needs trying to accomplish specific things. If the participants in your study don't actually represent your target users, you're not doing research. You're doing work that looks like research but doesn't provide real insights. When we say quality participants we mean: 

‍

1. They match your target criteria.  This seems obvious, but it's where most compromises happen. Every compromise in targeting dilutes the relevance of your insights. Quality participants don't just technically qualify. They deeply represent the actual people you're designing for.
2. They're engaged and thoughtful. A quality participant shows up prepared, gives full attention during the session, thinks carefully about questions, and provides detailed responses based on real experience. Engagement matters as much as targeting. A perfectly targeted participant who phones it in provides almost no value.
3. They show up. Seems basic, but no-shows are a massive problem. Quality participants honor their commitments. Consistent show rates mean you can actually plan research without padding your schedule with backup participants and hoped-for reschedules.
4. They're honest. Participants who tell you what they think you want to hear are worse than useless. You need people who'll be direct about confusion, frustration, and problems. Quality participants don't try to be nice or avoid hurting feelings. They give genuine feedback even when it's critical.

‍

‍

‍

The panel problem

‍

‍

Many teams rely on user research panels, databases of people willing to participate in studies for compensation,  which are often limited by the platform that they’ve purchased to one, proprietary panel for their research. Panels solve the recruitment problem by providing quick access to participants. But panels come with significant limitations.

‍

1. You're limited to who's in the panel. Need product managers at Series B startups in fintech? Need parents of children with specific developmental needs? If they're not in the panel, you can't reach them. You end up compromising your targeting to fit who's available rather than finding who you actually need.
2. Professional participants. Some people do user research studies regularly, almost as a side job. They're good at interviews. They know what researchers want to hear. They've done enough studies to unconsciously game the process. These "professional participants" might give you data, but they don't represent typical users. Their feedback is shaped by their experience participating in dozens of studies.
3. Quality inconsistency.  Panel quality varies dramatically. Some panels carefully vet participants and maintain high standards. Others will provide anyone who roughly matches your screener to hit the numbers you've requested. 

‍

When you're locked into a single panel provider, you're stuck with whatever quality standards they maintain.

‍

‍

‍

The panel ecosystem approach

‍

‍

The alternative to depending on a single panel is having access to multiple sources for participants. This means you're not limited by one panel's database. When you need specific, hard-to-reach audiences, you can access specialized panels that focus on those groups. When you need B2B professionals, you use networks that focus on business users. When you need consumers with specific characteristics, you access consumer panels with better targeting. The ecosystem model provides flexibility, better matching, and higher quality because you're not forcing every recruitment need through the same funnel. By the way, this is the way Optimal has intentionally chosen to offer participant recruitment via our platform for our customers (a panel ecosystem approach). 

‍

‍

‍

What changes when recruitment isn't the constraint

‍

‍

Imagine recruitment takes two days instead of two weeks. Imagine you can specify exactly the targeting you need and trust you'll get quality participants who match. How does your research change?

‍

1. You run more studies. When recruitment isn't a weeks-long process, research becomes more viable for smaller questions. More research means more informed decisions across the board.
2. You're more rigorous about targeting. When getting participants is easy, you don't have to compromise on criteria. You can be specific about exactly who you need and actually get them. Your insights become more reliable because they're based on truly representative participants.
3. You test more variations. Instead of showing 5 participants one design and hoping it works, you can test multiple variations with appropriate sample sizes for each. You can run A/B comparisons. You can validate results across different user segments. Better participant access enables more sophisticated research.
4. You move faster. Your timeline shrinks dramatically when recruitment isn't the bottleneck. Research becomes a viable input for time-sensitive decisions, not just long-term strategic work.

‍

Poor participant quality isn't a minor annoyance. It's the difference between research that drives confident decisions and research that creates false confidence in bad decisions. Quality in, quality out isn't just a principle. It's the foundation that determines whether your research is worth doing at all. 

‍

The recruitment bottleneck is real. But it's solvable. Teams that solve it don't just do more research. They do research that's actually worth acting on.

‍

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.

We spent Research Week in San Francisco listening, taking notes, and talking with the UX and market researchers, research managers, human factors engineers, research operations program managers, and product designers who gathered coast to coast. Sessions covered Advanced Market Research, Growth UXR, Great Research, AI and UXR, Up Up and Away!, and Moonshot Research.

‍

‍

‍

What are the key themes and insights that emerged from Research Week?

‍

‍

• Product defines, marketing communicates,  business captures the value, and researchers are translators and connectors.
• Build a culture of influence because influence isn't a moment, it's a structure.
• The insights alone are not enough; it's how you deliver and socialize them that makes them stick.
• Nothing hits like good UX research: compelling clips, stats, and verbatims.
• AI is transforming workflows, enabling large-scale data processing so researchers can focus on high-value work.

‍

‍

Practical takeaways to implement next week

‍

‍

Know who you're translating for and what matters to them

‍

‍

The gap in research most teams face right now is translation. Every function hears research differently. Each has a completely different "so what," as Apurva Luty puts it, so you need to respond and hear different ways, hearing data science in questions, design in critique, marketing in frameworks, engineering in constraints, and leadership in confidence. No one wants to hear: "we need to do more research”, but when you feel rushed for insights, you can always ask upfront if it’s a quick directional and recognize when you need more time for a comprehensive answer. 

‍

Building that bridge doesn’t mean you’re a gatekeeper. Rachel Ousley has seen democratizing access to data play out through more conversations and approaches with better questions.  Map your stakeholders' "so what" and foster an open line of communication because you are working towards the same goal in the end. 

‍

‍

Design for a culture of influence

‍

‍

Influence isn't a moment, it's a structure. Jess Holbrook breaks down direct influence versus indirect influence where direct influence is the central mechanism you present to senior leadership, and indirect influence is about setting the stage. Get ahead of it: know what your organization needs to understand in three months, six months, nine months, and how do we set ourselves up now to do that? 

‍

Build a culture of influence by giving credit loudly and often, saying people's names in the room by sharing wins and shoutouts. At Optimal, we do this through a celebrations Slack channel and quarterly value awards with open nominations through the company. Bring stakeholders, even ones you might not see eye-to-eye with upfront, into conversations where their perspective is genuinely valued, and anticipate what your team needs.

‍

‍

Continue running thoughtful studies with your users

‍

‍

The value of research is clear: to build better experiences, you must listen to the people who are using the product, service, the thing you’re making, and are affected by it. It is in discovery where you, well, discover what users actually want. As Andrew Chamberlain says, those hack projects and rapid prototypes can scale and become new products, and beyond that, research is how you elevate your brand and get invited into new spaces. 

‍

In discovery, know when to screen for behavior and when to screen for demographics. Maybe you’re looking at how people us mobile devices in homes, where one phone does not necessarily mean one owner or one user and in this case, your questions need to be framed openly and intuitively to get insight into your users’ mental models and actions, often different from your own, with people assigning different meanings to the same words. Nicole Naurath uses the example of asking “Do you share a device?” instead of, “How does someone else access this device?” to capture richer, more accurate insights into actual behavior.

‍

‍

Treat delivery like it's part of the research

‍

‍

Research reporting is socialization. Your decks don't have to change, but the artifacts around it do. A compelling clip, a sharp stat, a well-chosen verbatim – nothing hits like it. Nicole Zeng explains UX research as the thing that silences rooms, changes minds, and redirects roadmaps.

‍

Format your findings and discussion for the spaces people already work. Lauren Lin describes sharing insights as stackable and shareable clips on Slack as well as data cards that are downloadable as Figma components. 

‍

‍

Use AI to buy back your time for the work that matters

‍

‍

AI is enabling large-scale data processing that used to take months, which means you can spend less time in the weeds and more time on the work that moves the needle – the  judgment, translation, organizational, goal setting, and influence-building work. AI can handle the volume and scale of your data. However, everyone has a different comfort level with new tools. Nicole Zeng uses the analogy of a lake: maybe you’re diving in headfirst, maybe you’re watching from the shore, or maybe you’re paddling through the waves. 

‍

Break your workflow and explore novel ways of leveraging AI in UX research, then share out your findings and flows, because that's how we make progress as teams, get deeper customer insights, and ultimately make better decisions. It's why we're constantly evolving Optimal, and Optimal 3.0 is built for exactly this: helping product teams discover, validate, and continuously optimize user experiences that drive real business results.

‍

We're in an exciting time and it's moments like this when our industry comes together that we never forget. Stay connected with us on LinkedIn to get the latest updates on our upcoming events!

A well-maintained participant panel is more than a time-saver. It sets your team up for better research from day one. The people you recruit and how you track, segment, and manage those relationships over time directly shapes how reliable your findings are.  

‍

With the right setup in place, you can move forward with confidence, knowing that these participants meet your criteria, aren’t overused, and can bring fresh perspectives to each study.

‍

Tools like Rally UXR bring that structure to participant recruitment. It helps you build and manage your own participant panel, keep track of consent and contact history, coordinate logistics, and stay on top of all the moving parts. You can also see things like incentive history and email engagement, making it much easier to decide who to invite and when.

‍

But recruitment is just the starting point. The real value comes next: running the research and turning participant feedback into insights you can actually use.

‍

‍

‍

Using Rally + Optimal together

Whether you’re running unmoderated studies, testing designs, navigation, or content, or conducting usability testing calls, having the right research tools in place is critical. If you’re already using Rally, pairing it with Optimal can connect the dots from recruitment through to insights, without adding friction to your workflow.
‍

You can also use Optimal’s on-demand or custom managed recruitment services, though Rally’s strength lies in building your own custom panel and database.
‍

Here’s how to combine Rally and Optimal into a smooth, efficient research workflow.
‍
‍

Start with intentional recruitment

Define your participant criteria in Rally. Use screening questions not just to qualify participants. Think beyond “does this person qualify?” and start building segments you can reuse: power users vs. casual users, returning users vs. first-timers, people familiar with the old design vs. new. These segments can make it easier to run focused studies and compare results over time.

‍

Build your study in parallel

A simple shift that makes a big difference: don’t wait. Build your study in Optimal before sending invites from Rally. This ensures that when participants are ready, the link can be dropped into Rally, and distribution happens the moment you're ready.

‍

Use the strengths of each platform

Rally handles the relationship and profile management: who's been invited, who's confirmed, who needs a reminder, screener and survey history, consent forms, and more. Optimal handles the research: collecting quantitative and qualitative data, visualising patterns, quantifying usability issues, automating insights with AI, and surfacing the metrics and insights that actually answer your research question. 

‍

With Optimal, you can immediately put Rally-recruited participants into studies including:
‍

• Prototype testing
• Live site testing 
• Card sorting
• Tree testing
• First-click testing
• Surveys
  ‍
  ‍

Keep your insights in one place‍‍

When it comes to research, scattered insights = lost impact. Using Optimal as your central hub for results, recordings, and analysis makes it easier to share findings with your team and stakeholders, track progress over time, and back up decisions with real evidence. 
‍

The tools you use for recruitment and the tools you use for research aren't just operational choices. They shape your research culture. When recruitment and research are both well-structured, everything runs more smoothly. Teams that invest in structure on both ends of the workflow tend to produce research that's faster, more credible, and more likely to influence decisions. 
‍

Rally and Optimal are powerful on their own. Together, they create a workflow that’s scalable, insight-driven, and built for continuous discovery.

If you're not yet using Optimal, you can start a free trial or book a demo.