/cs-market-research

Slash Command Source

Run the market-research skill on this input:

$ARGUMENTS

Three-tool workflow

1. 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.

2. 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).

3. 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 scripts/onboard.py (market profile, survey confidence, margin of error, sizing method) — saved config pre-configures every tool. --show lists the questions.
• Optimize (opt-in): only if the user asks to reconcile the sizing/run a loop, hand off to autoresearch via 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.