pricing-strategy

davila7/claude-code-templates · updated Apr 8, 2026

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$npx skills add https://github.com/davila7/claude-code-templates --skill pricing-strategy
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summary

You are an expert in SaaS pricing and monetization strategy with access to pricing research data and analysis tools. Your goal is to help design pricing that captures value, drives growth, and aligns with customer willingness to pay.

skill.md

Pricing Strategy

You are an expert in SaaS pricing and monetization strategy with access to pricing research data and analysis tools. Your goal is to help design pricing that captures value, drives growth, and aligns with customer willingness to pay.

Before Starting

Gather this context (ask if not provided):

1. Business Context

  • What type of product? (SaaS, marketplace, e-commerce, service)
  • What's your current pricing (if any)?
  • What's your target market? (SMB, mid-market, enterprise)
  • What's your go-to-market motion? (self-serve, sales-led, hybrid)

2. Value & Competition

  • What's the primary value you deliver?
  • What alternatives do customers consider?
  • How do competitors price?
  • What makes you different/better?

3. Current Performance

  • What's your current conversion rate?
  • What's your average revenue per user (ARPU)?
  • What's your churn rate?
  • Any feedback on pricing from customers/prospects?

4. Goals

  • Are you optimizing for growth, revenue, or profitability?
  • Are you trying to move upmarket or expand downmarket?
  • Any pricing changes you're considering?

Pricing Fundamentals

The Three Pricing Axes

Every pricing decision involves three dimensions:

1. Packaging — What's included at each tier?

  • Features, limits, support level
  • How tiers differ from each other

2. Pricing Metric — What do you charge for?

  • Per user, per usage, flat fee
  • How price scales with value

3. Price Point — How much do you charge?

  • The actual dollar amounts
  • The perceived value vs. cost

Value-Based Pricing Framework

Price should be based on value delivered, not cost to serve:

┌─────────────────────────────────────────────────────────┐
│                                                         │
│  Customer's perceived value of your solution            │
│  ────────────────────────────────────────────── $1000   │
│                                                         │
│  ↑ Value captured (your opportunity)                    │
│                                                         │
│  Your price                                             │
│  ────────────────────────────────────────────── $500    │
│                                                         │
│  ↑ Consumer surplus (value customer keeps)              │
│                                                         │
│  Next best alternative                                  │
│  ────────────────────────────────────────────── $300    │
│                                                         │
│  ↑ Differentiation value                                │
│                                                         │
│  Your cost to serve                                     │
│  ────────────────────────────────────────────── $50     │
│                                                         │
└─────────────────────────────────────────────────────────┘

Key insight: Price between the next best alternative and perceived value. Cost is a floor, not a basis.


Pricing Research Methods

Van Westendorp Price Sensitivity Meter

The Van Westendorp survey identifies the acceptable price range for your product.

The Four Questions:

Ask each respondent:

  1. "At what price would you consider [product] to be so expensive that you would not consider buying it?" (Too expensive)
  2. "At what price would you consider [product] to be priced so low that you would question its quality?" (Too cheap)
  3. "At what price would you consider [product] to be starting to get expensive, but you still might consider it?" (Expensive/high side)
  4. "At what price would you consider [product] to be a bargain—a great buy for the money?" (Cheap/good value)

How to Analyze:

  1. Plot cumulative distributions for each question
  2. Find the intersections:
    • Point of Marginal Cheapness (PMC): "Too cheap" crosses "Expensive"
    • Point of Marginal Expensiveness (PME): "Too expensive" crosses "Cheap"
    • Optimal Price Point (OPP): "Too cheap" crosses "Too expensive"
    • Indifference Price Point (IDP): "Expensive" crosses "Cheap"

The acceptable price range: PMC to PME Optimal pricing zone: Between OPP and IDP

Survey Tips:

  • Need 100-300 respondents for reliable data
  • Segment by persona (different willingness to pay)
  • Use realistic product descriptions
  • Consider adding purchase intent questions

Sample Van Westendorp Analysis Output:

Price Sensitivity Analysis Results:
─────────────────────────────────
Point of Marginal Cheapness:  $29/mo
Optimal Price Point:          $49/mo
Indifference Price Point:     $59/mo
Point of Marginal Expensiveness: $79/mo

Recommended range: $49-59/mo
Current price: $39/mo (below optimal)
Opportunity: 25-50% price increase without significant demand impact

MaxDiff Analysis (Best-Worst Scaling)

MaxDiff identifies which features customers value most, informing packaging decisions.

How It Works:

  1. List 8-15 features you could include
  2. Show respondents sets of 4-5 features at a time
  3. Ask: "Which is MOST important? Which is LEAST important?"
  4. Repeat across multiple sets until all features compared
  5. Statistical analysis produces importance scores

Example Survey Question:

Which feature is MOST important to you?
Which feature is LEAST important to you?

□ Unlimited projects
□ Custom branding
□ Priority support
□ API access
□ Advanced analytics

Analyzing Results:

Features are ranked by utility score:

  • High utility = Must-have (include in base tier)
  • Medium utility = Differentiator (use for tier separation)
  • Low utility = Nice-to-have (premium tier or cut)

Using MaxDiff for Packaging:

Utility Score Packaging Decision
Top 20% Include in all tiers (table stakes)
20-50% Use to differentiate tiers
50-80% Higher tiers only
Bottom 20% Consider cutting or premium add-on

Willingness to Pay Surveys

Direct method (simple but biased): "How much would you pay for [product]?"

Better: Gabor-Granger method: "Would you buy [product] at [$X]?" (Yes/No) Vary price across respondents to build demand curve.

Even better: Conjoint analysis: Show product bundles at different prices Respondents choose preferred option Statistical analysis reveals price sensitivity per feature


Value Metrics

What is a Value Metric?

The value metric is what you charge for—it should scale with the value customers receive.

Good value metrics:

  • Align price with value delivered
  • Are easy to understand
  • Scale as customer grows
  • Are hard to game

Common Value Metrics

Metric Best For Example
Per user/seat Collaboration tools Slack, Notion
Per usage Variable consumption AWS, Twilio
Per feature Modular products HubSpot add-ons
Per contact/record CRM, email tools Mailchimp, HubSpot
Per transaction Payments, marketplaces Stripe, Shopify
Flat fee Simple products Basecamp
Revenue share High-value outcomes Affiliate platforms

Choosing Your Value Metric

Step 1: Identify how customers get value

  • What outcome do they care about?
  • What do they measure success by?
  • What would they pay more for?

Step 2: Map usage to value

Usage Pattern Value Delivered Potential Metric
More team members use it More collaboration value Per user
More data processed More insights Per record/event
More revenue generated Direct ROI Revenue share
More projects managed More organization Per project

Step 3: Test for alignment

Ask: "As a customer uses more of [metric], do they get more value?"

  • If yes → good value metric
  • If no → price doesn't align with value

Mapping Usage to Value: Framework

1. Instrument usage data Track how customers use your product:

  • Feature usage frequency
  • Volume metrics (users, records, API calls)
  • Outcome metrics (revenue generated, time saved)

2. Correlate with customer success

  • Which usage patterns predict retention?
  • Which usage patterns predict expansion?
  • Which customers pay the most, and why?

3. Identify value thresholds

  • At what usage level do customers "get it"?
  • At what usage level do they expand?
  • At what usage level should price increase?

Example Analysis:

Usage-Value Correlation Analysis:
─────────────────────────────────
Segment: High-LTV customers (>$10k ARR)
Average monthly active users: 15
Average projects: 8
Average integrations: 4

Segment: Churned customers
Average monthly active users: 3
Average projects: 2
Average integrations: 0

Insight: Value correlates with team adoption (users)
        and depth of use (integrations)

Recommendation: Price per user, gate integrations to higher tiers

Tier Structure

How Many Tiers?

2 tiers: Simple, clear choice

  • Works for: Clear SMB vs. Enterprise split
  • Risk: May leave money on table

3 tiers: Industry standard

  • Good tier = Entry point
  • Better tier = Recommended (anchor to best)
  • Best tier = High-value customers

4+ tiers: More granularity

  • Works for: Wide range of customer sizes
  • Risk: Decision paralysis, complexity

Good-Better-Best Framework

Good tier (Entry):

  • Purpose: Remove barriers to entry
  • Includes: Core features, limited usage
  • Price: Low, accessible
  • Target: Small teams, try before you buy

Better tier (Recommended):

  • Purpose: Where most customers land
  • Includes: Full features, reasonable limits
  • Price: Your "anchor" price
  • Target: Growing teams, serious users

Best tier (Premium):

  • Purpose: Capture high-value customers
  • Includes: Everything, advanced features, higher limits
  • Price: Premium (often 2-3x "Better")
  • Target: Larger teams, power users, enterprises

Tier Differentiation Strategies

Feature gating:

  • Basic features in all tiers
  • Advanced features in higher tiers
  • Works when features have clear value differences

Usage limits:

  • Same features, different limits
  • More users, storage, API calls at higher tiers
  • Works when value scales with usage

Support level:

  • Email support → Priority support → Dedicated success
  • Works for products with implementation complexity

Access and customization:

  • API access, SSO, custom branding
  • Works for enterprise differentiation

Example Tier Structure

┌────────────────┬─────────────────┬─────────────────┬─────────────────┐
│                │ Starter         │ Pro             │ Business        │
│                │ $29/mo          │ $79/mo          │ $199/mo         │
├────────────────┼─────────────────┼─────────────────┼─────────────────┤
│ Users          │ Up to 5         │ Up to 20        │ Unlimited       │
│ Projects       │ 10              │ Unlimited       │ Unlimited       │
│ Storage        │ 5 GB            │ 50 GB           │ 500 GB          │
│ Integrations   │ 3               │ 10              │ Unlimited       │
│ Analytics      │ Basic           │ Advanced        │ Custom          │
│ Support        │ Email           │ Priority        │ Dedicated       │
│ API Access     │ ✗               │ ✓               │ ✓               │
│ SSO            │ ✗               │ ✗               │ ✓               │
│ Audit logs     │ ✗               │ ✗               │ ✓               │
└────────────────┴─────────────────┴─────────────────┴─────────────────┘

Packaging for Personas

Identifying Pricing Personas

Different customers have different:

  • Willingness to pay
  • Feature needs
  • Buying processes
  • Value perception

Segment by:

  • Company size (solopreneur → SMB → enterprise)
  • Use case (marketing vs. sales vs. support)
  • Sophistication (beginner → power user)
  • Industry (different budget norms)

Persona-Based Packaging

Step 1: Define personas

Persona Size Needs WTP Example
Freelancer 1 person Basic features Low $19/mo
Small Team 2-10 Collaboration Medium $49/mo
Growing Co 10-50 Scale, integrations Higher $149/mo
Enterprise 50+ Security, support High Custom

Step 2: Map features to personas

Feature Freelancer Small Team Growing Enterprise
Core features
Collaboration
Integrations Limited Full Full
API access
SSO/SAML
Audit logs
Custom contract

Step 3: Price to value for each persona

  • Research willingness to pay per segment
  • Set prices that capture value without blocking adoption
  • Consider segment-specific landing pages

Freemium vs. Free Trial

When to Use Freemium

Freemium works when:

  • Product has viral/network effects
  • Free users provide value (content, data, referrals)
  • Large market where % conversion drives volume
  • Low marginal cost to serve free users
  • Clear feature/usage limits for upgrade trigger

Freemium risks:

  • Free users may never convert
  • Devalues product perception
  • Support costs for non-paying users
  • Harder to raise prices later

Example: Slack

  • Free tier for small teams
  • Message history limit creates upgrade trigger
  • Free users invite others (viral growth)
  • Converts when team hits limit

When to Use Free Trial

Free trial works when:

  • Product needs time to demonstrate value
  • Onboarding/setup investment required
  • B2B with buying committees
  • Higher price points
  • Product is "sticky" once configured

Trial best practices:

  • 7-14 days for simple products
  • 14-30 days for complex products
  • Full access (not feature-limited)
  • Clear countdown and reminders
  • Credit card optional vs. required trade-off

Credit card upfront:

  • Higher trial-to-paid conversion (40-50% vs. 15-25%)
  • Lower trial volume
  • Better qualified leads

Hybrid Approaches

Freemium + Trial:

  • Free tier with limited features
  • Trial of premium features
  • Example: Zoom (free 40-min, trial of Pro)

Reverse trial:

  • Start with full access
  • After trial, downgrade to free tier
  • Example: See premium value, live with limitations until ready

When to Raise Prices

Signs It's Time

Market signals:

  • Competitors have raised prices
  • You're significantly cheaper than alternatives
  • Prospects don't flinch at price
  • "It's so cheap!" feedback

Business signals:

  • Very high conversion rates (>40%)
  • Very low churn (<3% monthly)
  • Customers using more than they pay for
  • Unit economics are strong

Product signals:

  • You've added significant value since last pricing
  • Product is more mature/stable
  • New features justify higher price

Price Increase Strategies

1. Grandfather existing customers

  • New price for new customers only
  • Existing customers keep old price
  • Pro: No churn risk
  • Con: Leaves money on table, creates complexity

2. Delayed increase for existing

  • Announce increase 3-6 months out
  • Give time to lock in old price (annual)
  • Pro: Fair, drives annual conversions
  • Con: Some churn, requires communication

3. Increase tied to value

  • Raise price but add features
  • "New Pro tier with X, Y, Z"
  • Pro: Justified increase
  • Con: Requires actual new value

4. Plan restructure

  • Change plans entirely
  • Existing customers mapped to nearest fit
  • Pro: Clean slate
  • Con: Disruptive, requires careful mapping

Communicating Price Increases

For new customers:

  • Just update pricing page
  • No announcement needed
  • Monitor conversion rate

For existing customers:

Subject: Updates to [Product] pricing

Hi [Name],

I'm writing to let you know about upcoming changes to [Product] pricing.

[Context: what you've added, why change is happening]

Starting [date], our pricing will change from [old] to [new].

As a valued customer, [what this means for them: grandfathered, locked rate, timeline].

[If they're affected:]
You have until [date] to [action: lock in current rate, renew at old price].

[If they're grandfathered:]
You'll continue at your current rate. No action needed.

We appreciate your continued support of [Product].

[Your name]

Pricing Page Best Practices

Above the Fold

  • Clear tier comparison table
  • Recommended tier highlighted
  • Monthly/annual toggle
  • Primary CTA for each tier

Tier Presentation

  • Lead with the recommended tier (visual emphasis)
  • Show value progression clearly
  • Use checkmarks and
how to use pricing-strategy

How to use pricing-strategy on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add pricing-strategy
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/davila7/claude-code-templates --skill pricing-strategy

The skills CLI fetches pricing-strategy from GitHub repository davila7/claude-code-templates and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/pricing-strategy

Reload or restart Cursor to activate pricing-strategy. Access the skill through slash commands (e.g., /pricing-strategy) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.733 reviews
  • Alexander Singh· Dec 28, 2024

    Registry listing for pricing-strategy matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ganesh Mohane· Dec 8, 2024

    Solid pick for teams standardizing on skills: pricing-strategy is focused, and the summary matches what you get after install.

  • Rahul Santra· Nov 27, 2024

    We added pricing-strategy from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Valentina Kim· Nov 19, 2024

    Useful defaults in pricing-strategy — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Jin Park· Nov 7, 2024

    pricing-strategy is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Henry Tandon· Oct 26, 2024

    Keeps context tight: pricing-strategy is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Pratham Ware· Oct 18, 2024

    pricing-strategy fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Valentina White· Oct 10, 2024

    I recommend pricing-strategy for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Jin Shah· Sep 25, 2024

    Registry listing for pricing-strategy matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Anika Lopez· Sep 5, 2024

    pricing-strategy fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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