SynthPanel replaces slow, expensive market research with a mathematically rigorous library of synthetic AI personas — grounded in real census data, published market reports, and your own customer data.
The traditional market research industry, valued at $140 billion, is constrained by slow survey deployment, biased human panels, and lagging insights that take weeks to compile and cost millions to execute.
Product managers and marketing teams are forced to make high-stakes decisions based on gut reactions, feature popularity, or outdated focus groups. 49% of product managers report they do not know how to prioritize features without reliable customer feedback.
At SynthPanel, we believe that data should be predictive, not historical. Our mission is to empower cross-functional teams to validate product ideas, prioritize features, and optimize marketing campaigns instantly.
Our Population Architect Agent builds synthetic personas using US Census data, the World Values Survey, Pew Research digital behavior studies, and anonymized consumer spending data. Every agent is mathematically constrained by actual demographic distributions — not invented by an LLM.
LLMs hallucinate statistics. That is why our LLMs only generate qualitative reactions. A pure Python backend calculates all 14 market KPIs — including Net Promoter Score, Churn Risk Rate, and Revenue-Weighted Sentiment — deterministically. Every number is reproducible and traceable back to individual agent responses.
The agent that builds our synthetic populations never sees the scenario being tested. This architectural constraint prevents positive response bias — the tendency of LLMs to give every product a strong reaction. Our simulated markets are as indifferent as real ones.
A bi-monthly AI research agent ingests real market reports — Knight Frank Wealth Report, McKinsey Consumer Trends, GWI Global Consumer Survey, Bain Luxury Study, and more — extracting real personas and grounding synthetic agents in published research. Every sourced persona is attributed to its report.
12 integrated modules covering the full research lifecycle — from persona generation to campaign simulation to academic study design.
Synthetic agents grounded in census, psychographic, and behavioral data. Filter by generation, region, income, platform, and interests. Network analysis reveals hidden connections between persona clusters. Interest-based semantic filter finds personas matching any personality or hobby.
Deploy instant surveys to synthetic agents. Get 14 deterministic KPIs with full drill-down — every number traces back to individual agent responses. Conditional KPIs: price perception only shows if you enter a price. Download raw response data as CSV, Excel, or JSON.
Optional funnel analysis toggle on every survey. See how your target personas move from unaided awareness through consideration, intent, and purchase — with drop-off rates and improvement recommendations at each stage.
Reverse persona study: enter your product or brand and discover who your natural audience is, what interests them, how they perceive your brand, and the most effective channels to reach them.
A live virtual focus group where synthetic personas converse in character. AI moderator, real-time sentiment pulse, and professional report export. Qualitative depth at quantitative scale.
Professional design frameworks — Kano Model, RICE scoring, Jobs-to-be-Done, Empathy Mapping — applied by synthetic design panels. Feature prioritisation, usability testing, and design sprint simulation with actionable improvement guidance.
Upload your customer data as CSV or Excel, or connect directly to your database. SynthPanel generates synthetic personas grounded in your actual customer profiles — then lets you run research and chat with them in real time.
Upload any market research report (PDF, Word) and our AI agent extracts defined personas, attributes, and insights. Every extracted persona is tagged with its source report for full traceability. A bi-monthly agent keeps the curated library current.
Designed for academic researchers. Build IRB-style questionnaires, deploy to synthetic participant panels, and download structured response data for statistical analysis in SPSS, R, or Excel. Full citation support.
Force-directed network graph revealing relationships between personas based on shared traits, platforms, and psychographic clusters. Identify influence hubs and segment boundaries visually.
Full Traditional Chinese interface with language-aware AI responses. Switch languages instantly — all LLM outputs, KPI explanations, and agent verbatims respond in your selected language.
Fully responsive across all screen sizes. Install as a Progressive Web App on iOS or Android for a native-like experience. Run research from anywhere.
Your synthetic audience persists across the entire product lifecycle. The same Gen Z fintech users who validate your product concept are the same ones who react to your marketing taglines and pricing strategy.
Every KPI has an [i] methodology button explaining exactly how the number was calculated. Hover any metric to see the raw agent breakdown — how many agents said what, and why. No black boxes.
All proprietary data is PII-scrubbed before any LLM call. Custom personas are stored in dedicated encrypted namespaces. Zero data retention agreements with all LLM providers.
Our persona library spans 40+ countries, 6 generations, 12 income brackets, and 30+ psychographic archetypes — from Gen Z in Southeast Asia to Ultra High Net Worth individuals from the Knight Frank Wealth Report.
Pre-seeded personas come from real published research — Knight Frank, McKinsey, GWI, Bain, Edelman, and more. A bi-monthly AI agent keeps the library current. Every persona is attributed to its source report.
Upload your CRM data or connect your database. SynthPanel generates synthetic versions of your actual customers — preserving behavioral patterns without any real PII — then lets you run research on them.
From product managers to academic researchers — SynthPanel adapts to your workflow.
Validate product concepts, prioritise features using Kano + RICE, run design sprints — before writing a single line of code.
Understand how different demographic segments perceive your brand, identify positioning gaps, and simulate campaign messaging.
Replace expensive panel recruitment with instant synthetic surveys. Export raw data for your own statistical analysis.
Run IRB-style questionnaires on synthetic participant panels. Get structured response data for SPSS, R, or Python analysis.
Model price elasticity across all customer segments. Find the exact price point where churn risk outweighs margin gain.
Simulate audience reaction to social posts, ads, or video content before spending a dollar on media. Predict virality and purchase intent.
Our synthetic personas are not invented — they are mathematically constrained by live data from the world's most trusted sources.
| Data Category | Primary Sources | Purpose in SynthPanel | Update Frequency |
|---|---|---|---|
| Demographics & Census | US Census API, Eurostat, World Bank | Quarterly | |
| Psychographics & Values | General Social Survey, World Values Survey | Annually | |
| Economic & Spending Power | Bureau of Economic Analysis | Monthly | |
| Digital Platform Behavior | Pew Research, GWI GlobalWebIndex | Bi-Annually | |
| Market Trend Signals | Google Trends API, Reddit API | Daily / Real-time | |
| Published Market Reports | Knight Frank, McKinsey, Bain, Edelman, GWI | Bi-Monthly (AI Agent) |
Join forward-thinking product teams, marketing leaders, and academic researchers who have replaced slow, expensive research agencies with SynthPanel.
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