Product intelligence that compounds with every study
Stop running one-off validation studies that disappear. Build a compounding knowledge base of what your consumers want — so every product decision gets smarter, and teams never re-learn the same lessons.
Strong unmet need identified; adoption hinges on integration simplicity...
Product intelligence that compounds means validating concepts, testing positioning, and prioritizing features — then keeping that knowledge so your next study builds on the last. You stop re-learning what consumers want. Teams move faster because they stand on what they've already discovered. Every decision gets sharper with each research cycle.
Product teams keep re-learning
what consumers want
Three teams, three studies, three silos. Your organization doesn't learn from its own research because insights are trapped in one-off reports.
Insights Trapped in One-Off Studies
You commission a study, get results, move on. Six months later, similar questions arise. You commission another study. Same research, double the cost.
Product Teams Don't Trust Shallow Research
Surveys tell you what consumers do, not why. A survey says 64% prefer option A — but you don't know if they'd actually buy it.
Knowledge Walks Out When People Leave
A product director who spent 18 months learning your consumer gets hired away. That institutional knowledge leaves with them.
Validation Doesn't Inform Ongoing Decisions
You validate a concept. It tests well. Post-launch, you discover customers care about something the study didn't explore.
No Third Option Between Fast and Deep
Surveys are fast and cheap but shallow. Focus groups are deep but take 4 weeks and cost $12K. There's no middle ground.
Research Is a Gate, Not a System
Validation is seen as a one-time checkpoint. It doesn't fuel continuous product improvement or iteration.
Real-world applications
for product innovation research
Concept Validation
Test early-stage concepts before committing engineering resources. Launch multiple variants and understand the reasoning behind consumer preference.
Packaging Testing
Does your design communicate the right benefit? Would this package convince a consumer to pick it off the shelf? Test before printing.
Positioning & Messaging
Which value proposition lands hardest? Lead with health, taste, convenience, or price? Discover what actually resonates.
Feature Prioritization
Which features drive adoption and loyalty? Prioritize roadmaps around what customers actually want instead of engineering preferences.
Line Extension Testing
Will existing customers embrace a new product variant? Does a new flavor or functional benefit feel relevant to the brand?
Pricing Research
What price feels fair? When does it feel too expensive? Find the sweet spot between maximizing margin and maintaining perceived value.
User Intuition vs.
traditional product innovation research
| Dimension | User Intuition | Focus Groups / Surveys / Internal |
|---|---|---|
| Interview Depth | 30+ min · 5–7 laddering levels | Surface reactions or yes/no answers |
| Turnaround | 72 hours | 4–8 weeks (focus groups) or 1–2 weeks (surveys) |
| Study Cost | From $200 | $8K–$15K+ (focus groups) |
| Groupthink Risk | None · one-on-one | High (focus groups) or N/A (surveys) |
| Iteration Speed | Run multiple concepts in parallel | Sequential and expensive |
| Methodology Consistency | AI-moderated · standardized | Moderator-dependent or template-based |
| Global Access | 4M+ panelists · 50+ languages | Limited, local-only (focus groups) |
| Annual Commitment | None · pay per study | Retainers or long contracts |
| Key Output | WHY consumers prefer; motivational drivers | WHAT they prefer; stated opinions |
From question to brand intelligence
Define Question
Frame concept, target consumer, success criteria
Set Sample
Choose 10–500+ consumers from 4M+ panel
Launch
Watch interviews stream in live
Analyze
Themes, quotes, and recommendations
Brief
Share structured results with leadership
Iterate
Modify concept, test again, compound learnings
"User Intuition turned our product roadmap from a stakeholder debate into a data-backed strategy. We tested 5 concepts in 2 weeks. One of them became our fastest-growing SKU."
Director of Innovation — CPG Company
When AI Helps and When a Human Should Lead Product Research
AI-moderated interviews accelerate product validation — but some innovation stages benefit from human facilitation.
AI-Moderated Interviews Excel At
- Concept validation and feature prioritization at scale
- Consistent methodology across product lines
- Iterative prototype feedback in 72-hour cycles
- Cross-segment needs analysis and pain point discovery
- Multilingual product research across markets
- Eliminating moderator bias in product preference studies
Consider Human Moderation For
- Open-ended discovery and ideation workshops
- Physical prototype testing requiring hands-on demos
- Deep domain expertise in specialized categories
- Co-creation sessions with lead users
- Ethnographic in-context product usage observation
- Strategic product roadmap alignment with executives
Methodology refined through Fortune 500 consulting engagements.
Product intelligence that
compounds with every study
In 72 hours, validate your next product concept with real consumers. Build a knowledge base that makes every launch smarter.
See how continuous product research works. We'll help you design a compounding innovation program.
Launch a product validation study in minutes. Results in 72 hours. No contract required.
No contract · No retainers · Results in 72 hours