Market research methodology. Size a market as TAM/SAM/SOM computed BOTH top-down and bottoms-up (never a single number), plan a survey sample size with finite-p
复制下面这句话,粘贴给 Claude Code、Codex、Cursor 等 AI 编程工具,它会读取安装说明并在你确认后完成安装。
请阅读 https://ai.atlankj.com/install/asset/gh-claude-skills-dd95b7498bc1 ,按照其中的说明把「cs-market-research」安装到你(当前 AI 工具)中。执行前先告诉我将运行的命令和写入的位置,等我确认。
查看 AI 将读取的安装说明正在读取 GitHub 原文…
内容来自 GitHub 原始文件,由原作者维护。在 GitHub 查看
Run the market-research skill on this input:
$ARGUMENTS
market_sizer.py — Compute TAM/SAM/SOM by BOTH top-down (total market value × fractions) and bottoms-up (customers × price × adoption) methods side-by-side. Reports divergence and flags failed triangulation. Industry tuning via --profile. Never returns a single number.
sample_size_planner.py — Survey sample size from confidence, margin of error, and expected proportion, with the finite-population correction and per-segment minimums (a survey powered overall is not powered per reported segment).
segmentation_scorer.py — Score candidate segments against Kotler's measurable / substantial / accessible / differentiable / actionable criteria. Enforces a substantiality + accessibility gate; drops demographic slices that are too small or unreachable.
A market size always travels with its method (both ways) and assumptions — never a single unsourced number.
python3 skills/market-research/scripts/onboard.py (market profile, survey confidence, margin of error, sizing method) — saved config pre-configures every tool. --show lists the questions.skills/market-research/scripts/ar_evaluator.py (tam_divergence, lower is better).marketing-skill/campaign-analytics — that measures a live campaign. This is upstream methodology.marketing-skill/marketing-strategy-pmm — that sets positioning/GTM. This sizes and segments the market.commercial/pricing-strategist — that sets price. This sizes the market.