Pm-claude-skills pricing-strategy
Structure pricing strategy decisions, packaging options, and tier design for SaaS and digital products. Use when reviewing or setting pricing, designing pricing tiers, evaluating freemium vs paid, or preparing a pricing change. Produces a pricing strategy recommendation with model rationale, tier structure, competitive positioning, and rollout plan.
git clone https://github.com/mohitagw15856/pm-claude-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/mohitagw15856/pm-claude-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/pm-planning/skills/pricing-strategy" ~/.claude/skills/mohitagw15856-pm-claude-skills-pricing-strategy && rm -rf "$T"
plugins/pm-planning/skills/pricing-strategy/SKILL.mdPricing Strategy Skill
Build pricing that reflects value delivered — not cost to build. Structure every pricing decision with customer segmentation, value metric identification, competitive context, and a packaging recommendation.
Pricing Foundations
Three questions to answer before any pricing decision:
- Who is our buyer? (Role, company size, willingness to pay)
- What value do we deliver? (Quantifiable outcome — time saved, revenue generated, risk reduced)
- What is our pricing model? (Per seat, usage-based, flat, hybrid)
Pricing Models
| Model | Best For | Risk |
|---|---|---|
| Per Seat | Collaboration tools, team software | Disincentivises adoption as team grows |
| Usage-Based | APIs, infrastructure, consumption tools | Revenue unpredictability for both sides |
| Flat Rate | Simple tools, early-stage | Leaves money on table from power users |
| Tiered | Products with clear user segments | Feature gatekeeping frustrates users |
| Freemium | Viral/PLG products with low marginal cost | Conversion to paid is hard to engineer |
| Value-Based | Enterprise, outcomes-driven products | Requires strong ROI story |
Freemium Decision Framework
Use freemium when:
- ✅ Marginal cost per free user is near zero
- ✅ Product is inherently viral (network effects or sharing)
- ✅ Free tier creates genuine value (not just a demo)
- ✅ Clear upgrade trigger exists (feature, volume, or team size)
- ✅ Conversion benchmark is realistic (2–5% free-to-paid is typical)
Avoid freemium when:
- ❌ Support cost per free user is high
- ❌ No natural upgrade trigger in the product
- ❌ Core value requires features you'd need to gate
Packaging / Tiering Framework
Recommended 3-tier structure for SaaS:
| Tier | Target | Price Signal | Key Features | Lock-in Mechanism |
|---|---|---|---|---|
| Free / Starter | Individual, early discovery | $0 | Core value, usage-limited | Invite colleagues, export limit |
| Pro / Growth | SMB, growing teams | $[X]/seat/mo | Full features, higher limits | Team collaboration, integrations |
| Business / Enterprise | Mid-market, enterprise | $[X]/seat/mo or custom | Admin, SSO, SLAs, dedicated support | Security, compliance, volume |
Tier design rules:
- Each tier should be genuinely sufficient for its target segment
- The upgrade trigger should be felt naturally — not manufactured
- Price jumps of 3–5x between tiers are normal and defensible
Competitive Pricing Context
| Competitor | Model | Price | Key Differentiator |
|---|---|---|---|
| [Name] | [Model] | [Price] | [What they lead with] |
Positioning options:
- Premium: Price 20–40% above market. Justify with enterprise features, support, or brand.
- Parity: Match the market leader. Win on product or distribution.
- Value: Price below market. Win on volume. Dangerous without strong unit economics.
Output Format
Pricing Strategy Recommendation — [Product] — [Date]
Current State: [What pricing exists today, if any] Problem to Solve: [Why pricing is being reviewed]
Recommended Pricing Model: [Model name + rationale]
Value Metric: [The single unit that scales with customer value — e.g., "active users", "API calls", "documents processed"]
Proposed Tiers:
[Table using 3-tier structure above]
Free-to-Paid Upgrade Trigger: [Specific moment or threshold that creates natural upgrade pressure]
Competitive Position: [Premium / Parity / Value + reasoning]
Pricing Change Rollout (if applicable):
- Grandfathering: [Yes / No — recommendation and rationale]
- Communication plan: [How to tell customers + timing]
- Rollback plan: [Under what conditions you'd revert]
Risks:
- [Risk] → Mitigation: [Action]
Metrics to Monitor Post-Change:
- Conversion rate (free to paid)
- Churn rate by tier
- Average revenue per user (ARPU)
- Expansion revenue
Required Inputs
Ask the user for these if not provided:
- Product or service being priced
- Current pricing (if any — and why it's being reviewed)
- Target customer segments (size, role, willingness to pay)
- Key competitors and their pricing (if known)
- Business model (SaaS / Marketplace / Usage-based / Other)
- Primary goal (grow adoption / increase ARPU / reduce churn / new market entry)
Quality Checks
- Value metric is defined (the unit that scales with customer value)
- Free-to-paid upgrade trigger is specific (not "when they need more")
- Competitive positioning is chosen and justified (premium / parity / value)
- Pricing change rollout plan includes grandfathering decision
- Counter-metrics are defined to catch perverse incentives
- Risks have specific mitigations (not just listed)
Guidelines
- Never price based on cost — price based on value delivered to the customer
- Always A/B test price changes where possible; use geographic holdouts if A/B isn't feasible
- Recommend annual pricing with 15–20% discount — improves cash flow and reduces churn
- If enterprise pricing is "contact us", recommend adding a price floor to qualify inbound