pricing-strategy
The pricing-strategy skill analyzes and designs pricing strategies by evaluating value proposition, selecting appropriate pricing models (flat-rate, per-seat, usage-based, tiered, freemium, or value-based), conducting competitive analysis, and estimating customer willingness to pay. Use it when setting initial prices for a product, evaluating whether to change pricing, comparing different monetization approaches, or preparing to launch new pricing tiers.
git clone --depth 1 https://github.com/phuryn/pm-skills /tmp/pricing-strategy && cp -r /tmp/pricing-strategy/pm-product-strategy/skills/pricing-strategy ~/.claude/skills/pricing-strategySKILL.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
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.
---
### 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)Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split test data, or deciding whether to ship a variant.
Analyze and prioritize a list of feature requests by theme, strategic alignment, impact, effort, and risk. Use when reviewing customer feature requests, triaging a backlog, or making prioritization decisions.
Generate an Ansoff Matrix analysis mapping growth strategies across market penetration, market development, product development, and diversification. Use when considering growth options, planning market expansion, or evaluating strategic growth paths.
Identify the first beachhead market segment for a product launch. Evaluates segments against burning pain, willingness to pay, winnable market share, and referral potential. Use when choosing a first market, targeting an initial customer segment, or planning market entry strategy.
Design experiments to test assumptions for an existing product — prototypes, A/B tests, spikes, and other low-effort validation methods. Use when validating assumptions, testing feature ideas cheaply, or planning product experiments.
Design lean startup experiments (pretotypes) for a new product. Creates XYZ hypotheses and suggests low-effort validation methods like landing pages, explainer videos, and pre-orders. Use when validating a new product idea, creating pretotypes, or testing market demand.
Brainstorm product ideas for an existing product using multi-perspective ideation from PM, Designer, and Engineer viewpoints. Use when generating new feature ideas, brainstorming solutions for an identified opportunity, or ideating with a product trio.
Brainstorm feature ideas for a new product in initial discovery from PM, Designer, and Engineer perspectives. Use when starting product discovery for a new product, exploring features for a startup idea, or doing initial ideation.