Synthetic Market Research
Run market research surveys in minutes using AI-generated synthetic respondents
What You Can Do
You can conduct full market research studies—concept tests, pricing research, and purchase intent surveys—in minutes instead of weeks, without recruiting real respondent panels. Claude generates diverse synthetic survey responses based on your research questions, then applies Semantic Similarity Rating to validate directional accuracy against real-world behavior. This methodology, validated by PyMC Labs across 57 surveys, delivers statistically meaningful insights at near-zero cost.
Features
Validate new product ideas with synthetic respondent feedback on messaging, positioning, and feature appeal
Test price sensitivity and willingness-to-pay across multiple price points using synthetic consumer panels
Measure purchase likelihood and identify drivers of intent before investing in real panels
Validate synthetic responses against real-world behavior patterns for directional accuracy
Quantify sentiment and agreement across custom survey dimensions with statistical summaries
Run multiple research rounds in hours, enabling quick hypothesis testing and product refinement
Generate responses from specified customer personas and segments for targeted insights
Generate survey data, statistical tables, and markdown reports ready for stakeholder presentations
Example Output
Concept Test Results:
- Product concept resonated with 73% of synthetic respondents (n=50)
- Top benefit mentioned: "Saves 5+ hours per week on admin tasks"
- Primary objection: "Integration complexity with existing tools"
- Recommended messaging: Lead with time-savings, address integration in FAQ
Pricing Research Summary:
- Optimal price point: $29/month (70% purchase intent)
- Price elasticity: 5% drop in intent per $10 increase
- Segment analysis: Enterprise buyers show 2x higher intent at $99/month
Survey Response Sample:
Q: "How likely are you to purchase this product?" A: "8/10 — Solves a real pain point, but I'd need to see ROI vs. current solution"
What's Included
- SKILL.md: Complete skill instructions and operating modes for interactive and batch research
- SSR_METHODOLOGY.md: Technical reference on Semantic Similarity Rating, validation approach, and when to apply
- product_concept_test.md: Template and worked example for testing new product concepts
- pricing_research.md: Template and worked example for conducting price sensitivity studies
- Bash utilities: Installation scripts and environment setup for semantic-similarity-rating package
Who It's For
- Product Managers — Validate product concepts and feature prioritization before development
- Startup Founders — Test market viability and pricing strategy with minimal budget
- Market Researchers — Accelerate research cycles and enable rapid hypothesis testing
- Growth & Marketing Teams — Optimize messaging and positioning against synthetic consumer panels
- UX Researchers — Supplement qualitative research with quantitative concept validation data
Best For
- Concept testing and product validation before launch
- Price sensitivity analysis and optimal pricing discovery
- Purchase intent measurement and buyer behavior prediction
- Rapid A/B testing of messaging, positioning, and positioning
- Competitive analysis and feature prioritization research
- Early-stage market validation with limited research budgets
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