SKILL.md
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:
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
-
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.