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Command

/cs-pricing-strategy

Pricing model selection (subscription / usage / value / hybrid), Van Westendorp WTP analysis, packaging design. Recommends a model + range, never a specific number. Direct invocation of the pricing-strategist skill.

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claude-skills
24k116 skills100 agents116 commands1 MCP
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$ npx -y skills add alirezarezvani/claude-skills --agent claude-code

How it fires

How this command gets triggered: by you, by Claude, or both.

  • Fires itselfClaude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/cs-pricing-strategy

Context preview

What this command does when you run it.

Pricing model selection (subscription / usage / value / hybrid), Van Westendorp WTP analysis, packaging design. Recommends a model + range, never a specific number. Direct invocation of the pricing-strategist skill.

Command definition

cs-pricing-strategy.md
description: Pricing model selection (subscription / usage / value / hybrid), Van Westendorp WTP analysis, packaging design. Recommends a model + range, never a specific number. Direct invocation of the pricing-strategist skill.
argument-hint: "<pricing context: industry, deal size, customer count, value drivers>"

/cs:pricing-strategy — Pricing model + WTP + packaging

Run the `pricing-strategist` skill on this input:

**$ARGUMENTS**

Three-tool workflow

1. **`pricing_model_picker.py`** — Rank 5 pricing models (subscription seat-based, usage-based, value-based, freemium, hybrid) with fit-score 0-100 each. Industry tuning via `--profile {saas,api,ai-tools,enterprise-software,marketplace}`. Deterministic logic — consumption pattern + value drivers map to model fit.

2. **`wtp_analyzer.py`** — Van Westendorp Price Sensitivity Meter. Takes survey responses (4 prices per respondent: too cheap, bargain, getting expensive, too expensive). Computes OPP / IDP / PMC / PME intersections. Outputs **Range of Acceptable Prices** + **Optimal Price Point** (with N<30 sample-size warning).

3. **`packaging_designer.py`** — 3-tier (Good/Better/Best) packaging recommendation with feature-to-tier assignment based on importance + segment fit. Flags anti-patterns: "no differentiation", "Best > 2x price with < 1.5x value".

Output

  • Pricing model recommendation (model + range)
  • WTP analysis (4 price points + RAP + OPP)
  • Packaging design (3-tier feature map)

Hard rule

**This skill never recommends a specific price.** It recommends a **model and a range**. The human picks the number.

Distinct from

  • `cs-deal-desk` — that's **per-deal** discount approval.
  • `c-level-advisor/cmo-advisor` — that's **positioning + brand**.
  • `c-level-advisor/cro-advisor` — that's **strategic revenue motion**.
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Python
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MIT
License
3d ago
Last commit
9mo ago
Created

Repo: alirezarezvani/claude-skills