/pricing-strategy

name: pricing-strategy
description: "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

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:

| Model | Best For | Example | |---|---|---| | **Flat-rate** | Simple products, predictable costs | Basecamp ($99/mo flat) | | **Per-seat** | Collaboration tools, team products | Slack, Figma | | **Usage-based** | Infrastructure, API products | AWS, Twilio | | **Tiered** | Products with distinct user segments | Most SaaS (Free/Pro/Enterprise) | | **Freemium** | Products with viral/network effects | Spotify, Notion | | **Freemium + usage** | Platform products | Vercel, OpenAI API | | **Value-based** | High-impact enterprise tools | Salesforce, 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.

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Further Reading

• [Product Pricing Strategies 101](https://www.productcompass.pm/p/product-pricing-strategies-101)
• [The AI Product Pricing Masterclass: OpenAI Product Lead on Why SaaS Pricing Fails in AI (and How to Fix It)](https://www.productcompass.pm/p/ai-product-pricing) (video course)