Synthetic Market Research

synthetic-market-research

AI agent skill for fast, cheap market research using synthetic survey responses and [Semantic Similarity Rating (SSR)](https://github.com/pymc-labs/semantic-similarity-rating).

Test product concepts, pricing, and purchase intent in minutes instead of weeks, at $0 per respondent. Based on [PyMC Labs' validated methodology](https://arxiv.org/html/2510.08338v1) — 90% correlation with real human responses across 57 consumer surveys.

How It Works

1. Define your research question (purchase intent, pricing, concept appeal)
2. The skill generates demographic personas matching your target market
3. An LLM role-plays each persona and writes a natural-language reaction to your concept
4. SSR converts free-text responses into probability distributions over a Likert scale
5. You get segment-level breakdowns, overall scores, and qualitative themes

The key insight from the paper: asking an LLM for a number (1-5) gives poor results. Asking for free text and then mapping it to a scale via embedding similarity achieves 90% correlation with real humans.

Installation

Option 1: npx (recommended)

npx skills add BayramAnnakov/synthetic-market-research

Add `-g` to install globally (available in all your projects):

npx skills add BayramAnnakov/synthetic-market-research -g

Option 2: Manual (no Node.js required)

Clone the repo into your AI tool's skills directory:

Tool	Personal (global)	Project-level
Claude Code	~/.claude/skills/	.claude/skills/
Cursor	~/.cursor/skills/	.cursor/skills/
Windsurf	~/.codeium/windsurf/skills/	.windsurf/skills/
Codex	~/.codex/skills/	.agents/skills/

Example for Claude Code (personal):

git clone https://github.com/BayramAnnakov/synthetic-market-research.git \
  ~/.claude/skills/synthetic-market-research

Or download the [ZIP from GitHub](https://github.com/Ba