You're right to be skeptical.
AI generating market research sounds like hallucination with extra steps. Here's exactly how we constrain it to reality - and how you can verify every result.
Trust Signal
Coming Soon
The problem with "correcting" AI opinions
Traditional approach
Most synthetic research uses statistical priors to "correct" AI responses toward expected distributions. If the AI says 60% would buy but you expected 40%, adjust it down. This destroys the signal you're paying for.
Our approach
We don't correct AI opinions. We measure how representative the panel is compared to real population data - and show you the gap. You get authentic AI persona reactions plus the context to interpret them.
Why this matters
Irrational consumer behavior is valuable data. When our "Budget Mom" persona unexpectedly loves your premium product, that's a signal - not an error to smooth away. You want the insight, not a sanitized average.
19 personas. Not 19 stereotypes.
Each persona is a complete psychological profile - not a demographic checkbox. They have contradictions, blind spots, and irrational preferences. Just like real people.
Core Demographic
Personas built on the life stage x income matrix. From budget-conscious urban starters to affluent empty nesters - the backbone of any consumer panel.
- Young singles across income tiers
- New parents navigating first purchases
- Established families balancing budgets
- Empty nesters with disposable income
Psychographic
Personas defined by how they buy, not who they are. These archetypes cut across demographics - a deal hunter can be 25 or 55, male or female.
- Tech early adopters seeking novelty
- Skeptics who research everything
- Values-driven sustainability buyers
- Emotional impulse purchasers
Edge Cases
Contrarian voices that break assumptions. The wealthy person who clips coupons. The marketer who sees through everything. The voices that challenge your positioning.
- High-income but value-obsessed
- Time-starved single parents
- Industry insiders immune to marketing
- Extreme deal hunters
What makes a persona real
Each persona includes 10+ attributes that create consistent, believable behavior across every interaction:
Identity
- Demographics (age, gender, income)
- Life stage and current situation
- Financial constraints and goals
Psychology
- Decision-making patterns
- Core values (ranked by priority)
- Emotional triggers and fears
Behavior
- Platform and media preferences
- Purchase turn-offs and red flags
- Typical objections raised
Real-time calibration against population data
Every survey includes automatic calibration. We don't guess if the panel is representative - we measure it against authoritative sources and show you exactly where it aligns or diverges.
Generate Metrics
Claude analyzes your product and identifies 3-4 demographic or behavioral statistics that would validate the panel for your specific use case.
Search Base Rates
Perplexity API searches authoritative sources in real-time, returning specific statistics with citations. No stale data - current numbers from government and academic sources.
Add Calibration Questions
Corresponding questions are added to your survey automatically. These measure the AI panel's characteristics using the same methodology as the base rate sources.
Compare & Score
After the survey, we compare panel responses to real-world base rates. Each dimension gets an alignment score, weighted by source confidence (government > industry > news).
Transparent Reporting
Every report shows the calibration score, which dimensions aligned or diverged, the source citations, and plain-English interpretation. Nothing hidden.
Calibrated against authoritative data
We don't make up base rates. Every calibration metric is sourced from peer-reviewed research, government statistics, or major polling organizations - with citations included in your report.
Source confidence affects how much each dimension contributes to your overall representativeness score. Government and academic sources receive full weight. Industry reports receive 70%. News and blog sources receive 40%.
Data Visualization
Coming Soon
Personas remember your brand
Real consumers don't evaluate your product in a vacuum. They remember past experiences, form opinions over time, and carry those opinions into future interactions. Our Brand Memory system gives personas the same capability.
Memory Timeline
Coming Soon
Longitudinal consistency without averaging
Each persona maintains their unique perspective across sessions. The skeptic stays skeptical. The early adopter stays enthusiastic. But their opinions evolve based on what they learn about your brand - just like real customers.
- Persistent memory across surveys and interviews
- Opinion evolution based on new information
- Relationship tracking over time
- Consistent personality, not random variation
Statistical rigor included
Every survey includes automatic statistical analysis. No spreadsheet wrangling required.
Descriptive statistics
Mean, median, standard deviation, and confidence intervals for every scale question. Know instantly whether results show consensus or scatter.
Purchase Intent
Coming Soon
Response distributions
See the full shape of responses - not just averages. NPS-style breakdowns reveal promoters, passives, and detractors at a glance.
Intent Distribution (NPS-Style)
Coming Soon
Segment comparison
Automatic breakdown by demographic segment. See which groups over-index with significance indicators showing meaningful differences.
Segment Comparison
Coming Soon
Executive summary
AI-generated key insights with priority levels and segment tags. Ready for stakeholders who won't read the full report.
Key Insights
Coming Soon
What we don't claim
Not a replacement for validation
AI research is for exploration and hypothesis generation. Before you bet the company on a direction, validate with real humans. We're the first conversation, not the final word.
Not perfect representation
No panel - AI or human - perfectly represents every variation in your market. Calibration shows you the gaps. Niche audiences may need custom persona development.
Not immune to AI limitations
LLMs can be confidently wrong. That's why we show our work - calibration scores, source citations, statistical distributions. You have the context to judge quality yourself.
See the methodology in action
Run a free survey. Check the calibration report. Dig into the statistics. The best way to evaluate AI-powered research is to try it on a question you already know the answer to.