A UX research copilot for agile product teams

Seeing what users do isn’t enough—know why they do it.

UX Research Copilot Dashboard

Qualitative data reveals the 'why' behind their actions. You're not just tracking behavior or fielding complaints—you're understanding your users better than they understand themselves.

The Current Challenges

But qualitative research has many challenges

Despite its value, traditional UX research methods aren't working for modern product teams.

Limited Impact

UX research is often too complex, lacks concrete outputs, or fails to influence product decisions, making it feel like wasted effort.

Team Disconnect

UX and product teams operate in silos, making it difficult to integrate research into agile workflows and product decisions.

Data Undervalued

Qualitative insights aren't as respected as quantitative data because they're difficult to share, search, and reference consistently.

Not-Agile Research

Research work is labor-intensive, findings quickly become outdated, and the process is too slow to keep pace with modern agile product development.

UX Research Copilot

Qualitative research that unites your team

Get everyone on the same page

Pain Point 1

04:32 - 05:14

Active

Feature Request

08:19 - 09:02

Key Quote

12:45 - 13:10

Aha Moment

18:33 - 19:27

Breeze through qualitative data without any expertise

Smart Tag Assistant

Interview Transcript

Participant #24 - Sarah K.

Interviewer:

Could you walk me through how you typically plan your trip?

Participant:

"I usually start by researching the destination online, looking at both official tourism sites andsocial media for authentic experiencesBehavior. The problem is that it takes so much time to filter through everything to find what's relevant to me.I get overwhelmed by all the optionsFrustrationsand I'm never sure if I'm making the right choices. I wish there was a tool that couldcurate personalized recommendations based on my preferencesGoals & Needs."

AI-Detected Tags (20 seconds ago)

Frustrations: Information Overload

Behavior: Social Research

Goals & Needs: Personalization

Behavior: Seeking Authenticity

Frustrations: Decision Uncertainty

Personas that evolve with your product as you gather more insights

Profile Details

Culture Chaser

Based on 23 interviews

Demographics

Age: 28-42

Location: Urban centers

Income: $65-110k

Travel frequency: 3-4 trips/yr

Key Behaviors

Seeks authentic local experiences
Avoids tourist attractionsBalances tourist sites with local experiences
✎
Researches destinations extensively
Prioritizes local cuisine and food experiences
+

Pain Points

Language barriers when traveling
Finding reliable local guides
✕
Discovering non-touristy attractions
Last-minute itinerary changes
+

AI-Assisted Persona Analysis

Anna Zhang (Interview #24)

Frequent traveler, 34, Marketing professional

New persona?

No - This interviewee can be classified within an existing persona (Culture Chaser) with some updates to accommodate new insights.

How is this interviewee similar or different?

89% match with Culture Chaser persona.

Similar: Values local experiences, independent travel
Different: More emphasis on food experiences, more flexible on tourist attractions

Do we need to update this persona?

Yes - 3 recommended updates based on recent interviews:

Add food-focused behavior
Update tourist attraction avoidance
Remove guide-related pain point

Recommended Profile Updates

Add: New behavior - "Prioritizes local cuisine and food experiences"
Update: "Avoids tourist attractions" to "Balances tourist sites with local experiences"
Remove: Pain point "Finding reliable local guides" (solved by platform features)

Other potential matches: Budget Explorer (45%), Family Traveler (32%)

We keep your data beautifully messy—organized for thinking, not just finding.

For the best experience viewing the affinity diagram, please use a larger screen or rotate your device to landscape.

PersonaA Affinity Diagram

4 collaborators

Maria K.

Alex L.

Jamal T.

Sara P.

Topic 1

"I need to see patterns visually to understand connections"

"When data is just in spreadsheets, I miss important trends"

"Visual thinking helps me find unexpected relationships"

Topic 2

"I need to share insights with my team efficiently"

"Collaboration breaks down when we can't see the same data"

Topic 3

"I prefer to organize data spatially rather than linearly"

"My thinking process doesn't fit into rigid structures"

"I need flexibility to rearrange my thoughts as I go"

Topic 4

"Finding unexpected patterns is the most valuable part of research"

"I struggle when I can't connect related ideas from different interviews"

Topic 5

"I need to quickly iterate on ideas during analysis"

"Tools that limit exploration slow down my research process"

"I want to maintain a messy, creative space while working"

Great patterns emerging in Topic 3!

Just now

Draw me an affinity diagram grouping by topics for Persona A's interviews

I'll create an affinity diagram for Persona A. Would you like to filter by a specific date range?

Yes, Jan-Feb 2023 data only

Applying filters:

Persona A

Jan-Feb 2023

I've analyzed the filtered data and created an affinity diagram with 5 key topics. I found patterns related to visual thinking, collaboration, spatial organization, pattern recognition, and creative flexibility.

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