Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
dengineproblem avatar

Pricing Strategy

  • 62 installs
  • Updated January 1, 1970
  • dengineproblem/agents-monorepo

Helps a solo founder define a pricing strategy - tiers, packaging, and price points - grounded in value, costs, and competitor benchmarks.

About

A skill that helps a solo founder work out a pricing strategy - tiers, packaging, and price points informed by value delivered, costs, and competitor benchmarks. You reach for it when deciding how to monetize a product and want a structured way to land on defensible prices rather than guessing.

  • Designs pricing tiers and packaging
  • Benchmarks against competitors
  • Ties price to value

Pricing Strategy by the numbers

  • 62 all-time installs (skills.sh)
  • Ranked #1,543 of 3,282 Productivity & Planning skills by installs in the Skillselion catalog
  • Data as of Jul 29, 2026 (Skillselion catalog sync)
npx skills add https://github.com/dengineproblem/agents-monorepo --skill pricing-strategy

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs62
Last updatedJanuary 1, 1970
Repositorydengineproblem/agents-monorepo

What it does

Helps a solo founder define a pricing strategy - tiers, packaging, and price points - grounded in value, costs, and competitor benchmarks.

Who is it for?

founders deciding how to price a product

Skip if: purely technical implementation

Files

SKILL.mdMarkdownGitHub ↗

Pricing Strategy Expert

Strategic expertise in SaaS pricing, monetization models, and value-based pricing.

Pricing Models

pricing_models:
  per_user:
    description: "Charge per active user/seat"
    pros: ["Predictable revenue", "Easy to understand"]
    cons: ["Can limit adoption", "Encourages seat sharing"]
    best_for: "Collaboration tools, CRM"
    examples: "Slack, Salesforce"

  usage_based:
    description: "Charge based on consumption"
    pros: ["Low barrier to entry", "Fair value exchange"]
    cons: ["Revenue unpredictability", "Complex billing"]
    best_for: "API services, infrastructure"
    examples: "AWS, Twilio, Stripe"

  tiered:
    description: "Feature-based plan tiers"
    pros: ["Clear upgrade path", "Natural segmentation"]
    cons: ["Complexity risk", "Feature arbitrage"]
    best_for: "Most B2B SaaS"
    examples: "HubSpot, Zoom"

  freemium:
    description: "Free tier with paid upgrades"
    pros: ["Viral growth potential", "Product-led growth"]
    cons: ["Conversion challenges", "Free user costs"]
    best_for: "PLG companies"
    examples: "Dropbox, Notion"

Value-Based Pricing

Research Methods

pricing_research:
  van_westendorp:
    questions:
      - "At what price would this be too cheap?"
      - "At what price would this be a bargain?"
      - "At what price would this be expensive?"
      - "At what price would this be too expensive?"

  conjoint_analysis:
    purpose: "Understand feature value trade-offs"
    output: "Willingness to pay per feature"

  customer_interviews:
    questions:
      - "How do you currently solve this problem?"
      - "What would you pay for [benefit]?"
      - "What budget do you have for this?"

Tier Design

tier_structure:
  free:
    purpose: "Acquisition, product trial"
    includes: "Core functionality, limited usage"

  starter:
    target: "Individual users, small teams"
    features: "Core + basic analytics"

  professional:
    target: "Growing teams"
    features: "Advanced features, integrations"

  enterprise:
    target: "Large organizations"
    features: "Custom, security, SLA, dedicated support"

Psychological Pricing

pricing_psychology:
  anchoring: "Show highest price first"
  charm_pricing: "$99 instead of $100"
  price_framing: "$3/day vs $90/month"
  bundling: "Bundle price < sum of parts"
  annual_discount: "15-20% for annual payment"

Metrics

pricing_metrics:
  arpu: "MRR / Active Users"
  arpa: "MRR / Active Accounts"
  price_realization: "Actual Price / List Price (target >90%)"
  discount_rate: "Average discount given (target <15%)"

Лучшие практики

1. Value first — цена на основе ценности для клиента 2. Segment pricing — разные сегменты = разная готовность платить 3. Test everything — данные важнее интуиции 4. Annual contracts — стимулируйте годовые контракты 5. Simple packaging — сложность убивает конверсию 6. Regular reviews — пересматривайте цены ежегодно

Related skills

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.