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Agent Skill · 研究检索

pricing-strategy(定价策略)

pricing-strategy 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。

pricing-strategy 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 15,411。

总安装 7,869周安装 338GitHub Stars 26,428下载 2,758核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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-strategy(定价策略)
来源仓库:https://github.com/davila7/claude-code-templates
仓库路径:skills/pricing-strategy
安装命令:
npx skills add https://github.com/davila7/claude-code-templates --skill pricing-strategy
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

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

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

基于价值捕获与客户支付意愿设计 SaaS 产品定价模型。分析竞争格局、成本结构与 GTM 策略,输出分层定价建议。支持免费增值、按需付费、年度订阅等多种商业化模式探索。pricing-strategy 属于研究检索类 Skill,可作为该场景下的辅助能力补充。需输入业务类型、当前价格与市场定位等上下文方可生成有效方案。

结果为策略框架,最终决策需结合法务合规与财务测算综合判断。

来源仓库内路径:skills/pricing-strategy

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/davila7/claude-code-templates --skill pricing-…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

pricing-strategy 怎么安装?

在终端执行 npx skills add https://github.com/davila7/claude-code-templates --skill pricing-strategy。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

pricing-strategy 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

pricing-strategy 需要什么权限?

权限级别是需要联网。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。

pricing-strategy 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

pricing-strategy 用的人多吗?

公开数据是累计安装 7,869 次,近一周安装 338 次,下载 2,758 次,GitHub 26,428 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

pricing-strategy 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
pricing-strategy

定价策略 · 本页

7,86926,428需要联网MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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 ScorePackaging 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

MetricBest ForExample
Per user/seatCollaboration toolsSlack, Notion
Per usageVariable consumptionAWS, Twilio
Per featureModular productsHubSpot add-ons
Per contact/recordCRM, email toolsMailchimp, HubSpot
Per transactionPayments, marketplacesStripe, Shopify
Flat feeSimple productsBasecamp
Revenue shareHigh-value outcomesAffiliate 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 PatternValue DeliveredPotential Metric
More team members use itMore collaboration valuePer user
More data processedMore insightsPer record/event
More revenue generatedDirect ROIRevenue share
More projects managedMore organizationPer 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

PersonaSizeNeedsWTPExample
Freelancer1 personBasic featuresLow$19/mo
Small Team2-10CollaborationMedium$49/mo
Growing Co10-50Scale, integrationsHigher$149/mo
Enterprise50+Security, supportHighCustom

Step 2: Map features to personas

FeatureFreelancerSmall TeamGrowingEnterprise
Core features✓✓✓✓
Collaboration—✓✓✓
Integrations—LimitedFullFull
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 limits, not paragraphs
  • Anchor to higher tier (show enterprise first or savings)

Common Elements

  • Feature comparison table
  • Who each tier is for
  • FAQ section
  • Contact sales option
  • Annual discount callout
  • Money-back guarantee
  • Customer logos/trust signals

Pricing Psychology to Apply

  • Anchoring: Show higher-priced option first
  • Decoy effect: Middle tier should be obviously best value
  • Charm pricing: $49 vs. $50 (for value-focused)
  • Round pricing: $50 vs. $49 (for premium)
  • Annual savings: Show monthly price but offer annual discount (17-20%)

Price Testing

Methods for Testing Price

1. A/B test pricing page (risky)

  • Different visitors see different prices
  • Ethical/legal concerns
  • May damage trust if discovered

2. Geographic testing

  • Test higher prices in new markets
  • Different currencies/regions
  • Cleaner test, limited reach

3. New customer only

  • Raise prices for new customers
  • Compare conversion rates
  • Monitor cohort LTV

4. Sales team discretion

  • Test higher quotes through sales
  • Track close rates at different prices
  • Works for sales-led GTM

5. Feature-based testing

  • Test different packaging
  • Add premium tier at higher price
  • See adoption without changing existing

What to Measure

  • Conversion rate at each price point
  • Average revenue per user (ARPU)
  • Total revenue (conversion × price)
  • Customer lifetime value
  • Churn rate by price paid
  • Price sensitivity by segment

Enterprise Pricing

When to Add Custom Pricing

Add "Contact Sales" when:

  • Deal sizes exceed $10k+ ARR
  • Customers need custom contracts
  • Implementation/onboarding required
  • Security/compliance requirements
  • Procurement processes involved

Enterprise Tier Elements

Table stakes:

  • SSO/SAML
  • Audit logs
  • Admin controls
  • Uptime SLA
  • Security certifications

Value-adds:

  • Dedicated support/success
  • Custom onboarding
  • Training sessions
  • Custom integrations
  • Priority roadmap input

Enterprise Pricing Strategies

Per-seat at scale:

  • Volume discounts for large teams
  • Example: $15/user (standard) → $10/user (100+)

Platform fee + usage:

  • Base fee for access
  • Usage-based above thresholds
  • Example: $500/mo base + $0.01 per API call

Value-based contracts:

  • Price tied to customer's revenue/outcomes
  • Example: % of transactions, revenue share

Pricing Checklist

Before Setting Prices

  • Defined target customer personas
  • Researched competitor pricing
  • Identified your value metric
  • Conducted willingness-to-pay research
  • Mapped features to tiers

Pricing Structure

  • Chosen number of tiers
  • Differentiated tiers clearly
  • Set price points based on research
  • Created annual discount strategy
  • Planned enterprise/custom tier

Validation

  • Tested pricing with target customers
  • Reviewed pricing with sales team
  • Validated unit economics work
  • Planned for price increases
  • Set up tracking for pricing metrics

Questions to Ask

If you need more context:

  1. What pricing research have you done (surveys, competitor analysis)?
  2. What's your current ARPU and conversion rate?
  3. What's your primary value metric (what do customers pay for value)?
  4. Who are your main pricing personas (by size, use case)?
  5. Are you self-serve, sales-led, or hybrid?
  6. What pricing changes are you considering?

Related Skills

  • page-cro: For optimizing pricing page conversion
  • copywriting: For pricing page copy
  • marketing-psychology: For pricing psychology principles
  • ab-test-setup: For testing pricing changes
  • analytics-tracking: For tracking pricing metrics

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Claude Code

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Cursor

22.13%
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OpenCode

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Gemini CLI

13.1%
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Antigravity

8.67%
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github-copilot

3.34%
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