/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.
$ npx -y skills add alirezarezvani/claude-skills --agent claude-codeHow it fires
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/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.mddescription: 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:
**$ARGUMENTS**
Three-tool workflow
1. **`pricing_model_picker.py`** — Rank 5 pricing models (subscription seat-based, usage-based, value-based, freemium, hybrid) with fit-score 0-100 each. Industry tuning via `--profile {saas,api,ai-tools,enterprise-software,marketplace}`. Deterministic logic — consumption pattern + value drivers map to model fit.
2. **`wtp_analyzer.py`** — Van Westendorp Price Sensitivity Meter. Takes survey responses (4 prices per respondent: too cheap, bargain, getting expensive, too expensive). Computes OPP / IDP / PMC / PME intersections. Outputs **Range of Acceptable Prices** + **Optimal Price Point** (with N<30 sample-size warning).
3. **`packaging_designer.py`** — 3-tier (Good/Better/Best) packaging recommendation with feature-to-tier assignment based on importance + segment fit. Flags anti-patterns: "no differentiation", "Best > 2x price with < 1.5x value".
Output
- Pricing model recommendation (model + range)
- WTP analysis (4 price points + RAP + OPP)
- Packaging design (3-tier feature map)
Hard rule
**This skill never recommends a specific price.** It recommends a **model and a range**. The human picks the number.
Distinct from
- `cs-deal-desk` — that's **per-deal** discount approval.
- `c-level-advisor/cmo-advisor` — that's **positioning + brand**.
- `c-level-advisor/cro-advisor` — that's **strategic revenue motion**.
Read more
description: Pricing model selection (subscription / usage / value / hybrid), Van Westendorp WTP analysis, packaging design. Recommends a model + range, never a specific number. Direct invocation of the pricing-strategist skill. argument-hint: "<pricing context: industry, deal size, customer count, value drivers>"
/cs:pricing-strategy — Pricing model + WTP + packaging
Run the `pricing-strategist` skill on this input:
**$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**.
362 production-ready Claude Code skills, plugins, and agent skills for 13 AI coding tools. The most comprehensive open-source library of Claude Code skills and agent plugins — also works with OpenAI Codex, Gemini CLI, Cursor, and 9 more coding agents.
Repo: alirezarezvani/claude-skills
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