Token导航 LogoToken导航TokenDH.com
研究检索需要联网github未标认证来源可访问clear审计未展示

pricing-strategist定价策略师

Agent Skill

pricing-strategist 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

15,426

周安装

504

GitHub Stars

公开资料未说明

下载量

6,534
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:pricing-strategist(定价策略师)
来源仓库:https://github.com/eddiebe147/claude-settings
仓库路径:skills/pricing-strategist
安装命令:
npx skills add eddiebe147/claude-settings --skill "pricing-strategist"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add eddiebe147/claude-settings --skill "pricing-strategist"

简介

pricing-strategist 用于发现并推荐与定价策略相关的 AI 代理技能与解决方案。

  • 适合在制定产品定价模型、评估市场竞争力或优化收益策略时辅助信息检索。
  • 通过 GitHub 仓库路径安装,支持 Codex、Claude、Cursor 和 Gemini CLI 等宿主环境。
  • 安装前应检查仓库活跃度和技能兼容性,避免引入不稳定或已弃用的组件。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

name
Pricing Strategist
slug
pricing-strategist
description
Develop pricing strategies, analyze pricing models, optimize revenue, and test pricing changes
category
business
complexity
complex
version
1.0.0
author
ID8Labs
triggers
tags

Pricing Strategist

Expert pricing strategy and optimization system that helps you develop pricing models, analyze willingness to pay, optimize revenue, and test pricing changes. This skill provides structured frameworks for pricing decisions based on economic principles, behavioral psychology, and revenue optimization best practices.

Pricing is one of the most powerful levers for business growth. This skill helps you move beyond cost-plus pricing to value-based strategies, design pricing tiers that maximize revenue, and test changes scientifically. Whether you're launching a new product or optimizing existing pricing, this provides the analytical rigor and strategic thinking required.

Built on pricing psychology, behavioral economics, and SaaS pricing best practices, this skill combines willingness-to-pay research, competitive analysis, and experimentation frameworks to optimize your most important revenue lever.

Core Workflows

Workflow 1: Pricing Model Selection

Choose the right pricing structure for your business

  1. Common Pricing Models

Cost-Plus Pricing - Formula: Cost + Markup % = Price - Pros: Simple, ensures margin - Cons: Ignores customer value, leaves money on table - Best for: Commodities, manufacturing, retail

Competitive Pricing - Formula: Match or undercut competitor prices - Pros: Fast to market, safe - Cons: Race to bottom, ignores your unique value - Best for: Undifferentiated markets, price-sensitive customers

Value-Based Pricing - Formula: Price based on value delivered to customer - Pros: Maximizes revenue, aligns with customer outcomes - Cons: Requires deep customer understanding - Best for: Differentiated products, B2B SaaS, consulting

Freemium - Formula: Free tier + paid premium tiers - Pros: Low barrier, viral growth, try before buy - Cons: Conversion rate typically 2-5%, support costs - Best for: PLG (product-led growth), network effects

Usage-Based Pricing - Formula: Pay per unit consumed (API calls, seats, GB, transactions) - Pros: Aligns cost with value, grows with customer - Cons: Unpredictable revenue, complex billing - Best for: Infrastructure, APIs, marketplaces

Tiered Pricing - Formula: Good/Better/Best packages at different price points - Pros: Customer segmentation, upsell path, price discrimination - Cons: Complexity, analysis paralysis - Best for: SaaS, subscriptions, services

Performance-Based Pricing - Formula: Fee tied to results delivered (% of savings, revenue share) - Pros: Aligns incentives, de-risks for customer - Cons: Hard to measure, revenue uncertainty - Best for: Consulting, AdTech, FinTech

  1. Model Selection Criteria

- Customer preference (how do they want to buy?) - Competitive norms (what's standard in industry?) - Value delivery (when does customer realize value?) - Revenue predictability (do you need stable MRR?) - Sales motion (self-serve vs. enterprise sales?)

Workflow 2: Willingness to Pay Research

Understand what customers will actually pay

  1. Research Methods

Van Westendorp Price Sensitivity Meter Ask 4 questions: - At what price is this too expensive (wouldn't consider)? - At what price is this expensive (but would consider)? - At what price is this a bargain? - At what price is this too cheap (would question quality)?

Plot responses to find: - Optimal Price Point: Intersection of "expensive" and "bargain" - Acceptable Price Range: Between "too expensive" and "too cheap"

Conjoint Analysis - Present customers with product bundles with varying features and prices - Ask to choose preferred bundle - Statistically derive feature value and price sensitivity - Reveals trade-offs customers make

Competitor Analysis - Research competitor pricing (public pricing pages, sales calls) - Identify pricing tiers and feature differentiation - Map value proposition vs. price - Find gaps and opportunities

Customer Interviews - Ask about current spend on alternatives - Budget authority (how much can they approve without escalation?) - ROI expectations (what value justifies investment?) - Pricing structure preferences

  1. Segmentation

Different customer segments have different willingness to pay: - By company size: SMB vs. Mid-Market vs. Enterprise - By use case: High-value vs. low-value applications - By geography: Purchasing power varies by region - By industry: Some industries have higher budgets

Tailor pricing tiers to segments.

Workflow 3: Pricing Tier Design

Structure pricing tiers to maximize revenue and customer fit

  1. Tier Strategy

3-Tier Model (Most Common) - Starter/Basic (Anchor): - Purpose: Low barrier entry, volume play - Price: $X/month (affordable, minimal friction) - Features: Core functionality, limited usage - Target: Small businesses, individuals, trials

- Professional/Growth (Target): - Purpose: Optimized for ideal customer, highest volume - Price: 3-5x Basic (most choose this) - Features: Full functionality, higher limits, integrations - Target: Core market, majority of customers

- Enterprise (Aspiration): - Purpose: Anchor high end, premium features, custom - Price: "Contact us" or 10x+ Basic - Features: Unlimited, advanced, white-glove support, SLAs - Target: Large companies, high-value customers

  1. Feature Gating Strategy

- Good Tier: Core features that deliver basic value - Better Tier: Add productivity features, higher limits, integrations - Best Tier: Add enterprise features (SSO, advanced security, SLA, dedicated support)

Gate features by: - Usage limits: 10 projects vs. unlimited - Advanced features: Automations, AI, analytics - Integrations: API access, Zapier, Salesforce - Support: Email vs. chat vs. phone + CSM - SLAs: Uptime guarantees, response times

  1. Pricing Anchoring

- Decoy Effect: Add expensive tier to make mid-tier seem reasonable - Price Anchoring: Show "Most Popular" badge on target tier - Contrast: Strike-through annual pricing to show monthly equivalent savings - Loss Aversion: "Save $200/year" vs. "Pay $17/month"

  1. Annual vs. Monthly

- Offer both with 10-30% annual discount - Annual benefits: Cash upfront, lower churn, commitment - Monthly benefits: Lower barrier, easier to try - Position annual as better value ("Save 2 months")

Workflow 4: Pricing Psychology & Tactics

Leverage behavioral economics to optimize perceived value

  1. Psychological Pricing Tactics

Charm Pricing ($99 vs. $100) - Ending in .99 or .95 feels significantly cheaper - Best for: Consumer products, B2C - Avoid for: Enterprise (seems cheap)

Prestige Pricing (Round Numbers) - $1,000 feels premium vs. $999 - Best for: Luxury, enterprise

Price Anchoring - Show higher price first, then discount - "Was $299, Now $199" (30% off) - Reference competitor pricing to anchor high

Decoy Pricing - Introduce asymmetrically dominated option - Example: Small ($3), Large ($7), Medium ($6.50) - Medium seems like bad deal, customers choose Large

Bundling - Combine products/features at discount vs. a la carte - Increases perceived value - "Everything you need in one plan"

Good-Better-Best Positioning - Make middle tier the "Goldilocks" choice - Add "Most Popular" badge - Limit choice to 3 options (paradox of choice)

  1. Framing & Presentation

- Per-unit pricing: "$5 per user/month" (scales with value) - Total cost framing: "$60/year" vs. "$5/month" (depends on goal) - Feature emphasis: Lead with value, price secondary - Money-back guarantee: De-risk purchase decision - Social proof: "Join 10,000+ customers"

Workflow 5: Pricing Experimentation & Optimization

Test pricing changes scientifically to maximize revenue

  1. Experimentation Framework

A/B Testing - Test pricing changes with cohorts - 50% see Price A, 50% see Price B - Measure: Conversion rate, revenue per visitor, LTV - Run until statistical significance (usually 100+ conversions) - Choose winning variant

Grandfather Clause - When raising prices, let existing customers keep old pricing - Reduces churn, builds goodwill - Eventually sunset after 12-24 months

Beta Pricing - Launch at lower "early access" pricing - Increase as you add features and mature - Communicate value growth justifies price increase

Cohort Analysis - Compare customer cohorts by pricing experienced - LTV, churn, expansion by price point - Identify optimal price/value balance

  1. What to Test

- Price levels: $99 vs. $149 vs. $199 - Tier structure: 2-tier vs. 3-tier vs. 4-tier - Feature gates: What features in each tier? - Pricing display: Annual vs. monthly default - Discount strategy: 20% off vs. 2 months free - Payment terms: Monthly vs. annual vs. quarterly

  1. Metrics to Track

- Conversion rate: % of visitors who purchase - Average Revenue Per User (ARPU): Total revenue / customers - Customer Lifetime Value (LTV): ARPU × (1 / churn rate) - Price elasticity: % change in demand / % change in price - Tier distribution: % of customers in each tier

  1. When to Raise Prices

- Product maturity: Added significant value/features - Market validation: Strong demand, low churn - Competitive positioning: Still below competitors - Customer feedback: "Too cheap" concerns - New customer only: Grandfather existing (avoids churn)

Workflow 6: Packaging & Discounting Strategy

Design packages and discounts that drive revenue

  1. Package Design

- Single Product Tiers: Basic, Pro, Enterprise (SaaS) - Multi-Product Bundles: Suite vs. individual products - Add-ons: Base platform + a la carte features - Usage-Based + Base Fee: Hybrid model

  1. Discount Strategy

- Annual Discount: 10-30% off (standard for SaaS) - Volume Discount: Tiered pricing (10+ seats = 10% off) - Launch Discount: Early adopter pricing (limited time) - Nonprofit/Education: 30-50% discount (goodwill, low CAC) - Contract Length: Multi-year commitments (3-year = 15% off)

  1. When to Discount (Carefully)

- Enterprise sales: Expected part of negotiation - Annual commitment: To secure longer contract - Competitive displacement: Win deal from competitor - End of quarter: Sales team closing deals - Upsell: Discount expansion to grow account

  1. When NOT to Discount

- Self-serve SMB: Trains customers to expect discounts - High-velocity sales: Erodes margins at scale - Strong product-market fit: You have leverage - First ask: Make them earn it (ask for annual, reference, etc.)

Quick Reference

ActionCommand/Trigger
Pricing model"Recommend pricing model for [product]"
Tier design"Design 3-tier pricing for [product]"
Willingness to pay"Research pricing for [market]"
Price optimization"Optimize pricing for revenue"
Competitive analysis"Analyze competitor pricing for [industry]"
A/B test plan"Design pricing A/B test"
Discount policy"Create discount guidelines"
Price increase"Plan price increase for [product]"
Packaging"Design product bundle pricing"
ROI calculator"Build pricing justification tool"

Best Practices

Research & Analysis

  • Interview 20+ customers about willingness to pay
  • Analyze competitor pricing before setting yours
  • Test pricing with beta customers before launch
  • Use multiple research methods (don't rely on one)
  • Segment pricing by customer type

Pricing Design

  • Start simple—add complexity later
  • Make default choice obvious ("Most Popular")
  • Ensure clear value differentiation between tiers
  • Don't over-gate features (freemium conversion killer)
  • Price on value, not cost

Communication

  • Explain value, not just features
  • Show ROI and payback period
  • Transparent pricing on website (for SMB)
  • Custom pricing for enterprise (protect margin)
  • Price increase notices: 30-60 days, explain value added

Experimentation

  • Change one variable at a time
  • Run tests to statistical significance
  • Document learnings and iterate
  • Grandfather existing customers when raising prices
  • Monitor churn closely after changes

Optimization

  • Review pricing quarterly
  • Track tier distribution (80% in middle tier = good design)
  • Measure price sensitivity with small tests
  • Raise prices annually (2-3% inflation minimum)
  • Don't be afraid to charge more

Common Pitfalls to Avoid

  • Pricing too low: Undervaluing your product, leaving money on table
  • Copying competitors: Not considering your unique value
  • Too many tiers: Choice paralysis (limit to 3-4)
  • Confusing value metrics: Unclear what customer is paying for
  • Feature bloat: Putting everything in basic tier
  • No price increases: Inflation erodes revenue over time
  • Discounting by default: Trains customers to expect it
  • Ignoring psychology: Not using anchoring, framing, charm pricing
  • No experimentation: Guessing instead of testing

Pricing Model Examples by Industry

SaaS (B2B):

  • Model: Tiered subscription (per seat or per company)
  • Tiers: Starter ($49/seat), Professional ($99/seat), Enterprise (custom)
  • Example: Slack, HubSpot, Salesforce

SaaS (B2C):

  • Model: Freemium + tiered subscription
  • Tiers: Free, Plus ($9.99/month), Premium ($19.99/month)
  • Example: Spotify, Dropbox, Notion

Marketplace:

  • Model: Commission on transactions (GMV take rate)
  • Pricing: 10-30% of transaction value
  • Example: Airbnb (host fee + guest fee), Etsy, Uber

API/Infrastructure:

  • Model: Usage-based (pay-per-API call, GB, request)
  • Tiers: Free tier + pay-as-you-go + volume discounts
  • Example: Stripe, AWS, Twilio

E-commerce:

  • Model: Cost-plus with psychological pricing
  • Pricing: Charm pricing ($19.99), bundling, volume discounts
  • Example: Amazon, retail

Consulting/Services:

  • Model: Hourly, project-based, or retainer
  • Pricing: Value-based (ROI to client)
  • Example: Strategy consulting, agencies

Pricing Analysis Template

Current State:

  • Current pricing: $99/month
  • Average deal size: $1,188/year
  • Churn rate: 5%/month
  • LTV: $1,188 / 0.05 = $23,760
  • Tier distribution: 10% Basic, 70% Pro, 20% Enterprise

Proposed Change:

  • Increase Pro to $149/month (+50%)
  • Hypothesis: Minimal churn, revenue increase

Impact Model:

ScenarioConversion RateARPUChurnLTVRevenue Impact
Current5%$995%$23,760Baseline
Conservative4% (-20%)$1496%$29,800+25%
Expected4.5% (-10%)$1495.5%$32,509+37%
Optimistic5% (0%)$1495%$35,760+50%

Decision: Test with cohort, monitor for 90 days, roll out if Expected or better.

Tools & Resources

Research:

  • SurveyMonkey/Typeform: Willingness to pay surveys
  • Conjointly: Conjoint analysis platform
  • ProfitWell (by Paddle): Pricing optimization, benchmarking

Experimentation:

  • Google Optimize: A/B testing
  • Optimizely: Advanced experimentation
  • LaunchDarkly: Feature flags for pricing tests

Competitive Intelligence:

  • BuiltWith: Tech stack and pricing research
  • SimilarWeb: Traffic and engagement
  • Competitor websites: Public pricing pages

Pricing Psychology:

  • "Priceless" by William Poundstone
  • "Monetizing Innovation" by Madhavan Ramanujam
  • ProfitWell blog and benchmarks

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

27.68%
按下载量换算1,809

OpenCode

25.96%
按下载量换算1,696

Gemini CLI

16.99%
按下载量换算1,110

Antigravity

13.23%
按下载量换算864

Cursor

9.09%
按下载量换算594

windsurf

3.99%
按下载量换算261

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills