--- description: Design a pricing strategy — models, competitive analysis, willingness-to-pay estimation, and pricing experiments argument-hint: "" --- # /pricing -- Pricing Strategy Design Build a pricing strategy from first principles: analyze pricing models, estimate willingness to pay, benchmark against competitors, and design pricing experiments. ## Invocation ``` /pricing SaaS project management tool moving from free to paid /pricing Should we switch from per-seat to usage-based pricing? /pricing [upload competitor pricing pages or current pricing data] ``` ## Workflow ### Step 1: Understand the Pricing Context Ask: - What is the product? What value does it deliver? - Current pricing (if any): model, price points, packaging - What's the trigger? (new product, pricing change, competitive pressure, growth stall) - Target customer profile and their budget context - Any constraints? (contractual obligations, market expectations, competitive positioning) ### Step 2: Analyze Pricing Models Apply the **pricing-strategy** and **monetization-strategy** skills: Evaluate applicable models: - **Flat-rate**: Simple, predictable — best for commoditized products - **Per-seat/user**: Scales with adoption — best for collaboration tools - **Usage-based**: Aligns cost with value — best for infrastructure and API products - **Tiered**: Captures different willingness to pay — best for segmented markets - **Freemium**: Drives adoption — best for products with network effects - **Hybrid**: Combines models — best for complex products with multiple value levers For each relevant model: pros, cons, fit for your product, revenue projection approach. ### Step 3: Competitive Pricing Analysis Using web research: - Benchmark pricing against 3-5 competitors - Identify pricing model patterns in the category - Note pricing trends (e.g., shift from per-seat to usage-based in B2B SaaS) - Find pricing page screenshots and data points ### Step 4: Willingness to Pay Estimation If the user has survey data or customer feedback: - Apply Van Westendorp analysis (if data available) - Segment willingness to pay by user type If no data: - Estimate based on value delivered, competitive anchoring, and market norms - Design a willingness-to-pay survey the user can run ### Step 5: Generate Pricing Recommendation ``` ## Pricing Strategy: [Product] **Date**: [today] **Current pricing**: [if applicable] ### Recommended Model: [Model Name] **Why this model**: [rationale tied to product value delivery] ### Pricing Structure | Tier | Price | Includes | Target Segment | Key Limit | |------|-------|---------|---------------|-----------| ### Free / Trial Strategy [What's free, what's gated, conversion triggers] ### Competitive Benchmark | Competitor | Model | Price Range | Positioning | |-----------|-------|-----------|------------| ### Revenue Projections | Scenario | Assumptions | Year 1 ARR | Year 2 ARR | |----------|-----------|-----------|-----------| | Conservative | [X] | [Y] | [Z] | | Expected | [X] | [Y] | [Z] | | Optimistic | [X] | [Y] | [Z] | ### Migration Plan [If changing pricing: how to transition existing customers] - Grandfathering approach - Communication plan - Timeline ### Pricing Experiments | Experiment | What We're Testing | Method | Duration | |-----------|-------------------|--------|----------| ### Risks and Mitigations | Risk | Likelihood | Impact | Mitigation | |------|-----------|--------|-----------| ### Key Metrics to Track - Conversion rate by tier - Average revenue per user (ARPU) - Upgrade/downgrade rates - Churn by price sensitivity - Price elasticity signals ``` Save as markdown. ### Step 6: Offer Next Steps - "Want me to **create a monetization strategy** with alternative revenue models?" - "Should I **run a market scan** to validate pricing assumptions?" - "Want me to **draft customer communication** for the pricing change?" - "Should I **design the A/B test** for pricing experiments?" ## Notes - Pricing is the most powerful lever for revenue growth — a 1% improvement in pricing typically has 3-4x the impact of 1% improvement in customer acquisition - Value-based pricing always beats cost-plus — start from customer value, not your costs - The best pricing is simple to understand and predictable for the customer - Freemium only works if free users generate value (network effects, word of mouth, marketplace liquidity) - Always design a migration path for existing customers — pricing changes that alienate your base destroy trust