mcpField
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pricing-strategy

pricing-strategy

github.com/phurynMarketing & growth27.5k3.0k installsUpdated 2w ago
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About pricing-strategy

pricing-strategy is a product-pricing skill for teams shaping a pricing recommendation. It evaluates customer value, pricing models, competitors, tiers, price sensitivity, and experiments.

Key features

  1. 01Assess value delivered and willingness to pay
  2. 02Compare pricing models and competitors
  3. 03Design tiers, feature gates, and value metrics
  4. 04Estimate price sensitivity
  5. 05Plan pricing experiments

Use cases

  1. 01Develop pricing for a new product
  2. 02Rework SaaS tiers and feature access
  3. 03Use survey data to assess price sensitivity

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/phuryn/pm-skills --skill pricing-strategy

After installing, type/pricing-strategyin Claude Code to confirm it loaded.

Details

From the project README

Pricing Strategy

Design a pricing strategy grounded in value delivery, competitive positioning, and willingness to pay.

Context

You are developing a pricing strategy for $ARGUMENTS.

If the user provides files (competitor pricing, survey data, financial models, or usage data), read them first. Use web search to research competitor pricing if needed.

Instructions

  1. Understand the value delivered:

    • What is the core value proposition?
    • What is the customer's alternative (and its cost)?
    • What quantifiable outcomes does the product deliver? (time saved, revenue gained, cost reduced)
    • What is the customer's willingness to pay based on that value?

  2. Evaluate pricing models — recommend the best fit:

    ModelBest ForExample
    Flat-rateSimple products, predictable costsBasecamp ($99/mo flat)
    Per-seatCollaboration tools, team productsSlack, Figma
    Usage-basedInfrastructure, API productsAWS, Twilio
    TieredProducts with distinct user segmentsMost SaaS (Free/Pro/Enterprise)
    FreemiumProducts with viral/network effectsSpotify, Notion
    Freemium + usagePlatform productsVercel, OpenAI API
    Value-basedHigh-impact enterprise toolsSalesforce, Palantir

  3. Analyze competitive pricing:

    • Map competitor pricing tiers and what's included
    • Identify where your product sits (premium, mid-market, budget)
    • Find pricing gaps or opportunities
    • Note any industry pricing conventions

  4. Design the pricing structure:

    • Tiers: Define 2-4 tiers with clear differentiation
    • Feature gating: Which features go in which tier? (Use value metrics, not arbitrary limits)
    • Value metric: What unit do you charge on? (users, events, storage, API calls)
    • Anchor pricing: Set the most popular tier to feel like the obvious choice
    • Annual discount: Typically 15-20% off monthly pricing

  5. Estimate price sensitivity:

    • Van Westendorp Price Sensitivity Meter (if survey data available):
      • Too cheap → quality concerns
      • Cheap → good value
      • Expensive → starting to hesitate
      • Too expensive → won't buy
    • Alternatively, estimate based on competitor pricing and value delivered

  6. Plan pricing experiments:

    • A/B test pricing pages (different price points, tier names, feature bundles)
    • Founder-led sales conversations to test willingness to pay
    • Landing page tests with different price anchors
    • Cohort analysis of conversion rates by price point

  7. Output a pricing recommendation:

    Recommended Model: [Model type]
Value Metric: [What you charge on]

| Tier | Price | Target Segment | Key Features | Positioning |
|---|---|---|---|---|

Key Assumptions:
- [Assumption] → [How to test]

Risks:
- [Risk] → [Mitigation]

Think step by step. Save as markdown. Flag any assumptions that need validation before launch.

Further Reading

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