/cs:market-research — TAM/SAM/SOM + survey sampling + segmentation
Run the market-research skill on this input:
$ARGUMENTS
Three-tool workflow
-
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.
Output
- TAM/SAM/SOM both ways + triangulation flag + assumptions
- Survey n (overall + per-segment floors)
- Segment scores with TARGET / WATCH / DROP verdicts
- Top 3 next actions
Hard rule
A market size always travels with its method (both ways) and assumptions — never a single unsourced number.
First run + optimization
- Onboard first:
python3 skills/market-research/scripts/onboard.py(market profile, survey confidence, margin of error, sizing method) — saved config pre-configures every tool.--showlists the questions. - Optimize (opt-in): only if the user asks to reconcile the sizing/run a loop, hand off to autoresearch via
skills/market-research/scripts/ar_evaluator.py(tam_divergence, lower is better).
Distinct from
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.