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pricing-strategy

Analyze and design pricing strategies including pricing models, competitive pricing analysis, willingness-to-pay estimation, and price elasticity. Use when setting prices, evaluating pricing models, preparing for a pricing change, or comparing freemium vs paid approaches.

Author

@phuryn

Category

PM

Install

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name:pricing-strategydescription:"Analyze and design pricing strategies including pricing models, competitive pricing analysis, willingness-to-pay estimation, and price elasticity. Use when setting prices, evaluating pricing models, preparing for a pricing change, or comparing freemium vs paid approaches."

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

  • 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?

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • Product Pricing Strategies 101

  • The AI Product Pricing Masterclass: OpenAI Product Lead on Why SaaS Pricing Fails in AI (and How to Fix It) (video course)