Install
$ agentstack add skill-manojbajaj95-claude-gtm-plugin-pricing-strategy ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Pricing Strategy
Workspace Context
Read bootstrap context before asking questions: strategy/brand.md for brand, audience, offer, channels, tools, constraints, and metrics; about/me.md for personal voice; content/ideas.md and content/calendar.md for content planning. Use legacy product-marketing context files only as fallback. Save generated drafts to content//drafts/YYYY-MM-DD_short-topic-slug.md, and route durable learnings back to strategy/brand.md, about/me.md, or content/ideas.md.
Operating Contract
This skill is self-contained for its frontmatter scope: use its local instructions, references, scripts, and assets as the playbook; ask only for missing task-specific inputs; hand off to adjacent skills instead of expanding scope; and return an actionable artifact, decision, plan, draft, or diagnostic.
Expert guidance on SaaS pricing, value metrics, tier structure, pricing research, and monetization.
Before Starting
Gather: product type, target market (SMB/mid-market/enterprise), GTM motion (self-serve/sales-led/hybrid), primary value delivered, competitive pricing, current conversion rate and ARPU, pricing goals (growth vs. revenue vs. profitability).
Pricing Fundamentals
Three axes: Packaging (what's in each tier) + Value metric (what you charge for) + Price point (the amount).
Core principle: 1% improvement in pricing = 11% improvement in profit (McKinsey). Price to value, not cost.
Value-based pricing: Price between the next best alternative and perceived value. Cost is a floor, not a basis.
Perceived value of your solution: $1,000
Your price: $500 ← capture value here
Next best alternative: $300 ← your floor
Your cost to serve: $50
Value calculation template:
Time savings: [hours/week × hourly rate × 52]
Revenue impact: [additional deals × deal value × 12]
Cost avoidance: [errors prevented × cost per error × 12]
Total annual value: $____
Suggested price: $[10% of value] – $[20% of value] / year
Pricing Models
| Model | Pros | Cons | |-------|------|------| | Flat Rate ($99/mo, unlimited) | Simple to sell | Leaves money on table | | Tiered (Starter/Pro/Business) | Captures segments, clear upsell | Anchor pricing matters | | Usage-Based ($0.01/call) | Perfect value alignment, low barrier | Unpredictable revenue | | Hybrid ($49/mo + $0.50/extra user) | Predictable base + scales | More complex to explain |
Value Metrics
The value metric is what you charge for — it should scale with the value customers receive.
| Metric | Best For | Examples | |--------|----------|---------| | Per user/seat | Collaboration tools | Slack, Notion | | Per usage/consumption | Variable workloads | AWS, Twilio | | Per contact/record | CRM, email tools | Mailchimp, HubSpot | | Per transaction | Payments, marketplaces | Stripe, Shopify | | Flat fee | Simple, bounded products | Basecamp | | Revenue share | High-value outcome tools | Affiliate platforms |
Choosing your metric: Analyze which usage patterns predict retention and expansion in your highest-LTV customers. If "more of X = more value," X is your metric.
Pricing Research Methods
Van Westendorp Price Sensitivity Meter
Ask 100–300 respondents four questions:
- Too expensive — would not buy
- Too cheap — would question quality
- Expensive but would consider
- Bargain / great value
Key intersections:
- PMC (Point of Marginal Cheapness): "Too cheap" × "Expensive" → lower bound
- PME (Point of Marginal Expensiveness): "Too expensive" × "Cheap" → upper bound
- OPP (Optimal Price Point): "Too cheap" × "Too expensive" → best price
- IDP (Indifference Price Point): "Expensive" × "Cheap" → acceptable midpoint
Acceptable range: PMC → PME. Optimal zone: OPP → IDP.
MaxDiff / Feature Importance
Show sets of 4–5 features; ask "most important" and "least important." Results rank features by utility score:
| Utility | Packaging Decision | |---------|-------------------| | Top 20% | Include in all tiers (table stakes) | | 20–50% | Use to differentiate tiers | | 50–80% | Higher tiers only | | Bottom 20% | Cut or premium add-on |
Willingness to Pay
- Gabor-Granger: Show price → "Would you buy at $X?" (Yes/No). Vary price across respondents to build demand curve.
- Conjoint analysis: Show bundles at different prices; respondents choose preferred option.
Tier Structure
The Rule of 3: Starter (50–60% of customers) → Pro/sweet spot (30–40%) → Business/Enterprise (5–10%).
Anchor pricing: Middle tier 3–4× starter price; top tier 2–3× middle. This makes the middle tier the obvious choice.
Starter: $29/mo — core features, 5 users, email support
Pro: $99/mo — everything + integrations, 20 users, priority support ← Most Popular
Business: $299/mo — everything + SSO, unlimited users, dedicated support
Good-Better-Best Framework
| Tier | Purpose | Price | Target | |------|---------|-------|--------| | Good (Starter) | Remove barriers to entry | Low, accessible | Small teams, trial converts | | Better (Pro) | Where most customers land | Anchor price | Growing teams | | Best (Business) | Capture high-value customers | 2–3× Better | Larger teams, power users |
Feature Gating
What to gate:
- Scale limits: users, projects, API calls, storage
- Sophistication: advanced analytics, automations, integrations
- Control: SSO/SAML, admin roles, audit logs, custom branding
Never gate: core functionality, security features, data export.
Freemium vs. Free Trial
| | Freemium | Free Trial | |-|----------|-----------| | Best for | PLG, wide top of funnel | Sales-led, high-ACV | | Conversion | 2–5% free → paid | 15–25% trial → paid | | Risk | Free riders, support cost | Shorter window to prove value | | Use when | Network effects, viral growth | Complex product needing onboarding |
Pricing Psychology
- Anchor effect: Show highest tier first to anchor perception
- Charm pricing: $49 vs. $50 (perceived as significantly cheaper)
- Decoy pricing: Add a "bad" middle option to push customers to "best"
- Annual vs. monthly: Offer 15–20% discount for annual (improves LTV and reduces churn). Offer at signup, after 2–3 months, and during renewal
- Per user transparency: Show total cost at common team sizes (e.g., "5 users = $X/mo")
Pricing Experiments
What to A/B test: Price points, tier packaging, billing frequency, free trial length, anchor tier.
Sample sizes: ~1,000 visitors/variant to detect 10% change; ~5,000 for 5% change.
Metrics to track: Conversion (trial → paid), ARPU, CAC, LTV, payback period.
Price increases: Raise every 12–18 months as you add value. Communicate 30+ days in advance. Grandfather existing customers for 12 months or offer annual lock-in at current price.
Revenue Expansion
Upsell triggers:
- User hits usage limit → show upgrade prompt immediately
- User clicks locked feature → show upgrade at moment of value
- User active 30+ days on starter → "power user" upgrade nudge
Add-ons (use when a feature has standalone value not everyone needs):
Base plan: $99/mo
+ Extra users: $10/user/mo
+ Advanced analytics: $49/mo
+ White label: $99/mo
+ Priority support: $199/mo
Pricing by Segment
| Segment | Price Point | Sales Motion | Decision Maker | Sales Cycle | |---------|-------------|--------------|----------------|-------------| | SMB | $29–99/mo | Self-serve | End user/team lead | Minutes–days | | Mid-Market | $99–999/mo | Self-serve + light touch | Dept head | Days–weeks | | Enterprise | $1,000+/mo | High-touch sales | VP/C-level | Weeks–months |
Key Metrics
| Metric | Healthy Benchmark | |--------|------------------| | Trial → Paid conversion | >15% | | MRR Growth (early stage) | >10%/month | | Churn Rate | 3:1 | | Payback Period | 100% |
Discount Framework
| Type | Trigger | Range | |------|---------|-------| | Volume | Commitment to scale | 10–30% | | Term | Annual commitment | 15–25% (2 months free) | | Competitive | Switching from competitor | 20–40% | | Strategic | Reference customer / logo value | Up to 50% |
Never discount when: customer hasn't articulated value, no competitive pressure, early in negotiation, or deal doesn't meet minimum size.
Alternatives to discounting: extended payment terms, additional services/training, extended trial, success milestone unlocks, multi-year lock-in.
Common Pricing Mistakes
- Pricing on cost, not value
- Too many tiers (analysis paralysis — stick to 3)
- Feature gates customers don't care about
- Gating core functionality (lock what makes your product worth using)
- Complex value metric (users shouldn't need a calculator for their bill)
- Ignoring price sensitivity by segment
- Never testing or iterating on pricing
- Burying the price page (hiding = distrust)
Price Increase Playbook
- Quantify value delivered since last price (new features, outcomes, benchmarks)
- Grandfather existing customers for 3–6 months (or 12 months for best customers)
- Communicate early (60-day notice minimum)
- Frame as investment not cost increase — tie to ROI
- Offer annual lock-in before increase date to capture cash
- Monitor churn closely for 90 days post-increase
Checklists
Launching pricing:
- [ ] Pick value metric; design 3 tiers with anchor prices (3–4× between tiers)
- [ ] Package features (60% / 85% / 100%); offer 14-day trial; set up billing
Optimizing pricing:
- [ ] Track conversion rates by tier; survey customers on pricing perception
- [ ] A/B test price points; add annual billing option; create in-app upgrade prompts
- [ ] Monitor NRR; review pricing every 6–12 months
Deep-dive on pricing models, discount structures, and services pricing: see references/pricing.md
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: manojbajaj95
- Source: manojbajaj95/claude-gtm-plugin
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.