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.