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.

install
source · Clone the upstream repo
git clone https://github.com/mohitagw15856/pm-claude-skills
Claude Code · Install into ~/.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"
manifest: plugins/pm-planning/skills/pricing-strategy/SKILL.md
source content

Pricing 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:

  1. Who is our buyer? (Role, company size, willingness to pay)
  2. What value do we deliver? (Quantifiable outcome — time saved, revenue generated, risk reduced)
  3. What is our pricing model? (Per seat, usage-based, flat, hybrid)

Pricing Models

ModelBest ForRisk
Per SeatCollaboration tools, team softwareDisincentivises adoption as team grows
Usage-BasedAPIs, infrastructure, consumption toolsRevenue unpredictability for both sides
Flat RateSimple tools, early-stageLeaves money on table from power users
TieredProducts with clear user segmentsFeature gatekeeping frustrates users
FreemiumViral/PLG products with low marginal costConversion to paid is hard to engineer
Value-BasedEnterprise, outcomes-driven productsRequires 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:

TierTargetPrice SignalKey FeaturesLock-in Mechanism
Free / StarterIndividual, early discovery$0Core value, usage-limitedInvite colleagues, export limit
Pro / GrowthSMB, growing teams$[X]/seat/moFull features, higher limitsTeam collaboration, integrations
Business / EnterpriseMid-market, enterprise$[X]/seat/mo or customAdmin, SSO, SLAs, dedicated supportSecurity, 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

CompetitorModelPriceKey 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