Validate your product ideas overnight
— for the price of lunch.

Get human-level purchase intent data in minutes, powered by peer-reviewed AI that replicates real focus groups with 90% accuracy.

No surveys. No panels. No delays.

Science, Not Hype

Built on research that's actually been published — not “AI magic.”

Powered by Semantic Similarity Rating (SSR), a peer-reviewed method developed by PyMC Labs and Colgate-Palmolive in 2025.

SSR Methodology

SSR allows large language models to replicate human purchase-intent ratings by analyzing open-ended responses and mapping them to a 5-point Likert scale — with proven statistical precision.

Peer-Reviewed Research

Published methodology with academic validation

Enterprise Tested

Developed with Colgate-Palmolive research teams

Statistically Rigorous

Validated across 9,000+ survey participants

≈ 90%
of human test–retest reliability
across 9,000 survey participants

Research Citation

“LLMs Reproduce Human Purchase Intent via Semantic Similarity Elicitation of Likert Ratings.”
Maier et al., 2025 — Published October 9 2025.
9,000+
Participants
2025
Published

How It Works

Get statistically representative consumer data in three simple steps — no recruiting, no panels, no waiting.

01

Describe your concept

Paste your product description or upload a mockup. Optionally choose a target persona such as “Gen Z budget shopper” or “eco-conscious parent.”

02

Simulate realistic consumers

SimuPanel prompts AI personas to respond naturally — producing hundreds of purchase-intent statements as if you ran a real focus group.

03

Quantify intent with SSR

Each response is converted to an embedding vector and compared against calibrated anchor statements. The result: a realistic Likert-style distribution that mirrors human survey data.

Output: statistically representative purchase-intent distribution + text rationales in under 60 seconds.

Consumer data, without consumers.

Get the insights you need in minutes, not weeks. No need to find participants, schedule sessions, or wait for results.

Results You Can See

Know not just what consumers think — but why.

Every simulation returns a complete Likert distribution plus the “why” behind the ratings.

Mean Purchase Intent
4.2
out of 5
Reliability vs. Humans
≈90%
test-retest accuracy

Purchase Intent Distribution

1
8%
2
12%
3
25%
4
35%
5
20%
1 = Very Unlikely to Purchase • 5 = Very Likely to Purchase
KS-similarity: 0.88
Runtime: ≈ 52 seconds per simulation

Sample Synthetic Feedback

I'd probably try this — especially if it's affordable.

The eco-friendly angle appeals to me.

Sounds innovative, but I'd want proof of effectiveness.

This could solve a real problem I have.

Not sure if it's worth the price point.

What You Get

  • Complete Likert distribution with statistical significance
  • Qualitative insights explaining purchase decisions
  • Demographic breakdown by persona
  • Exportable data for further analysis

Under the Hood

The process behind every simulation — for teams who care how the data's made, not just what it says.

1

Generate Realistic Responses

Persona-conditioned prompting produces natural consumer statements.

Implementation Details

Persona-conditioned prompting
Natural language generation
Diverse response patterns
2

Encode Semantic Meaning

High-dimensional embeddings capture semantic similarity and context.

Implementation Details

High-dimensional embeddings
Semantic similarity calculations
Context-aware encoding
3

Map to Likert Scale

Calibrated anchor statements yield realistic purchase-intent distributions.

Implementation Details

Calibrated anchor statements
Cosine similarity scoring
Statistical variance preservation

Every step of the process follows three core principles:

Transparent

Open methodology with published research papers and validation studies.

Reproducible

Consistent results across runs with documented parameters and settings.

Responsible

Built and tested with strict data-privacy and ethical-AI practices — no personal data collection, ever.

Use Cases & Who Benefits

Research-backed consumer insights for teams who need statistically significant data, not guesswork.

Use Cases

Product Validation

Quantify purchase intent before manufacturing investment. 90% accuracy vs. human panels.

Creative Testing

Measure message resonance and creative appeal with statistical significance.

Research Scaling

Screen concepts at scale. Prioritize human research based on SSR-powered rankings.

Who Benefits

Founder

Founders

Quantify product-market fit before investing in inventory or ads. Validate ideas with real purchase-intent simulations in minutes.

Marketing

Marketers

Measure message resonance and creative appeal using simulated consumer data. Optimize campaigns before launch.

Agency

Agencies

Pre-screen creative concepts and back client reports with data-driven validation. Deliver research-grade insights fast.

Research

Researchers

Scale testing without panels or recruiting. Prototype surveys and rank concepts with SSR-powered accuracy.

Coming Soon: Simple, one-click pricing

Join our waitlist to be the first to access SimuPanel when we launch.

🧪 Single Test

Run one simulation with 100 synthetic responses. Perfect for quick validation or product testing.

$9
100 synthetic responses
Likert distribution + rationales
PDF export
Basic persona controls

⚙️ 5-Pack

Run five simulations. Best for testing multiple concepts or campaigns.

$35$45
Save $10
5 simulations total
Priority processing
CSV + PDF exports
Email support

🚀 20-Pack

Run twenty simulations. Ideal for teams or researchers running frequent tests.

$99$140
Save $41
20 simulations total
Full persona customization
API access
Priority support

Be the first to know when SimuPanel launches.
Join our waitlist for early access and exclusive pricing.

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Frequently Asked Questions

Everything you need to know about how SimuPanel works — and why it's different.

SimuPanel doesn't guess — it measures.

Get your first validated insights today.

Make confident, data-backed decisions — in minutes, not months.

SimuPanel uses validated AI and peer-reviewed science to simulate real consumer behavior — instantly.

Get results in minutes, not months
90% of human focus-group accuracy
No recruiting, scheduling, or surveys needed
Backed by peer-reviewed science

Backed by peer-reviewed research — powered by Semantic Similarity Rating (SSR).