UX intelligence that deepens with every study
Every research conversation becomes searchable knowledge your team builds on. Study users once. Reuse insights forever. Ship faster because you stand on what you've already learned.
Users complete core tasks 40% faster after targeted navigation improvements...
UX intelligence means treating research as organizational memory, not one-off deliverables. Instead of insights scattered across Notion docs and Figma comments, every study contributes to a searchable knowledge base. Teams reuse learnings about user motivations, pain points, and decision patterns. Understanding deepens as you study more users, and compounds when you cross-reference findings across features, segments, and versions.
Your UX research is scattered across
Notion, Figma, and abandoned decks
New team members can't access what you already learned. Every study starts from zero. Insight velocity doesn't match product velocity.
Knowledge Fragmentation
User pain points from checkout research don't inform onboarding research. Emotional insights from one segment aren't accessible to other teams.
New Team Members Start From Zero
A designer joins and redesigns a feature you researched 3 months ago. They don't know it. You waste budget re-discovering what you already learned.
Research Ships Monthly, Product Ships Weekly
Traditional UX research takes 4–8 weeks. Product sprints run 2 weeks. Insights arrive too late to influence decisions.
Shallow Research Stays Shallow
'Users struggled with checkout' doesn't compound into organizational knowledge. You need the why: trust anxiety? friction? complexity?
Reports Gather Dust
A 30-page PDF lands three weeks late. Product priorities shifted. Smart research, irrelevant timing. It sits archived instead of informing what ships next.
Deep Research Is a Luxury
Traditional UX research costs $500–$2,000+ per interview. Only large research departments with six-figure budgets can afford it.
Real-world applications
for ux research
User Motivation & Needs Research
Move beyond feature lists to uncover the emotional and functional drivers behind user decisions. What job is the user hiring your product to do?
Experience Mapping & Journey Research
Understand the full user journey — where users encounter friction, when delight occurs, and what moments create abandonment risk.
Decision Psychology Research
Reveal subconscious drivers: visual trust, cognitive ease, social proof, loss aversion. Redesign to align with how users' brains actually work.
Emotional Response Research
How does your product make users feel? Does onboarding feel welcoming or overwhelming? Does error messaging feel punitive or supportive?
Comparative UX Evaluation
Side-by-side research comparing your product against 1–3 competitors. Where do users prefer your experience? Where do competitors outperform?
Onboarding & Activation Research
Isolate onboarding friction points: where new users get confused, what accelerates activation, what delight moments drive commitment.
User Intuition vs.
traditional ux research
| Dimension | User Intuition | UserTesting / dscout / In-House |
|---|---|---|
| Interview Depth | 5–7 levels AI laddering | 2–4 levels (user-driven or varies) |
| Turnaround | 72 hours | 5–10 days (UserTesting) to 2–4 weeks (in-house) |
| Study Cost | From $200 | $750–$5,000+ depending on method |
| Moderation Consistency | 100% AI-standardized | 60–80% (varies by moderator) |
| Panel Access | 4M+ verified consumers | 1–2M+ or limited/internal |
| Scalability | Unlimited at fixed cost | Cost increases 1:1 with volume |
| Researcher Required | No · anyone can launch | Often yes (in-house moderation) |
| Annual Commitment | None · pay per study | Subscriptions or headcount |
| Key Output | WHY users behave; emotional root causes | WHAT users do; task completion |
From question to brand intelligence
Define Question
Write research questions, set screener logic
AI Interviews
30–60 min conversations run in parallel
Auto-Analyze
Transcription, thematic coding, synthesis
Dashboard
Interactive insights with quotes and themes
Share
Export to PDF, Slack, Jira, or API
Compound
Build searchable insight library
"We used to wait 6 weeks for research. Now we run studies inside our sprint cycle. The depth of the AI's laddering surprised me — we uncovered emotional trust barriers that changed our entire onboarding approach."
Joel M., CEO — Abacus Wealth Partners
When AI Helps and When a Human Should Lead UX Research
AI-moderated interviews fit into sprint cycles — but some UX questions need in-person human observation.
AI-Moderated Interviews Excel At
- User motivation and decision psychology research
- Consistent methodology across user segments
- Onboarding and activation experience research
- Feature prioritization and pain point discovery
- Remote usability interviews with screen sharing
- Eliminating moderator bias in user preference studies
Consider Human Moderation For
- In-person contextual inquiry and observation
- Complex prototype walkthroughs requiring real-time guidance
- Accessibility research with users who need accommodations
- Highly sensitive UX topics (health, finance, safety)
- Co-design and participatory design workshops
- Expert heuristic evaluation sessions
Methodology refined through Fortune 500 consulting engagements.
UX intelligence that deepens
with every study
In 72 hours, understand the why behind user behavior. Build institutional knowledge that makes every product decision smarter.
See how continuous UX research integrates into sprint cycles. We'll help you build a compounding research practice.
Launch a UX research study in minutes. Results in 72 hours. No contract required.
No contract · No retainers · Results in 72 hours