定价与能力包设计｜个人思维图谱小站

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SKILL.md

中文导读

研究产品价值、计费方式、能力组合与付费意愿，支持定价讨论。

输入材料

产品价值与费用条件
客户研究和现有定价

交付结果

定价方案
需要验证的假设

阅读与使用

本页保存指定版本的原始 Skill 和配套文件，可查看中文导读、原文与参考资料。获取完整包后，按原文准备所需工具与材料。

来源仓库为 coreyhaines31/marketingskills，采用 MIT 许可。Stars 表示仓库关注度，核验日期为 2026-10-15。分类表示适用的工作环节，实际执行条件以原文为准。

原始 Skill

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

Before Starting

Check for product marketing context first: If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

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?

3. Current Performance

What's your current conversion rate?
What's your ARPU and churn rate?
Any feedback on pricing from customers/prospects?

4. Goals

Optimizing for growth, revenue, or profitability?
Moving upmarket or expanding downmarket?

Pricing Fundamentals

The Three Pricing Axes

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
Perceived value vs. cost

Value-Based Pricing

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

Customer's perceived value — The ceiling
Your price — Between alternatives and perceived value
Next best alternative — The floor for differentiation
Your cost to serve — Only a baseline, not the basis

Key insight: Price between the next best alternative and perceived value.

Don't anchor on the wrong things:

Not competitor-based — matching a competitor's price copies their strategy, not their economics. It's a data point, not a target.
Not cost-based — cost is a floor, never the basis. Value + differentiation set the price.

Initial Pricing — "Pick a Price You Can Learn From"

The frameworks below (value metrics, tiers, Van Westendorp) are for optimizing a price. On day one you don't have a price to optimize — you have a bet to place. The goal of your first price is learning, not precision. Pick a number, ship it, and let real buyers tell you if it's wrong.

The $10 / $100 / $1,000 rule of thumb

When you have nothing to go on, start with the order of magnitude that matches who you serve:

~$10/mo — prosumer / individual, high volume, low touch
~$100/mo — SMB / team tool, the SaaS default
~$1,000/mo — mid-market / business-critical / sales-assisted

Pick the bucket by who the customer is and how much value you deliver, then start near the round number. You can move within the bucket fast once you have signal.

Avoid the $9 trap

Resist the urge to price ultra-low (e.g. $9/mo) to reduce friction. Ultra-low pricing:

Creates false traction — signups that look like validation but come from people who'd never pay a real price
Traps you — it's far harder to raise a price 5–10x later than to have started higher, and your cheapest customers churn most and complain loudest (see references/pricing-models.md on low-price retention)

Round-and-slightly-higher beats clever-and-cheap.

"Just charge $50 and see what happens"

When early Intercom agonized over pricing, Jason Fried's advice was essentially: just charge $50 and see what happens. Stop modeling; get a real signal. If people pay without flinching, raise it. If nobody bites, you've learned something for the cost of a week, not a quarter.

For the eight ways to structure how you charge (flat, usage, tier, user, feature, credit, outcome, hybrid) and the value/price ratio: See references/pricing-models.md.

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
Per transaction	Payments, marketplaces	Stripe
Flat fee	Simple products	Basecamp

Choosing Your Value Metric

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

The value metric picks the pricing model. Once you know what scales with value, choose how to charge on it — flat, usage, tier, user, feature, credit, outcome, or a hybrid. See references/pricing-models.md.

Tier Structure Overview

Good-Better-Best Framework

Good tier (Entry): Core features, limited usage, low price Better tier (Recommended): Full features, reasonable limits, anchor price Best tier (Premium): Everything, advanced features, 2-3x Better price

Tier Differentiation

Feature gating — Basic vs. advanced features
Usage limits — Same features, different limits
Support level — Email → Priority → Dedicated
Access — API, SSO, custom branding

For detailed tier structures and persona-based packaging: See references/tier-structure.md

Pricing Research

Van Westendorp Method

Four questions that identify acceptable price range:

Too expensive (wouldn't consider)
Too cheap (question quality)
Expensive but might consider
A bargain

Use intersections to identify perceived price acceptability and candidate prices to test. The named "Optimal Price Point" is a survey intersection, not proof of revenue or profit maximization. The four questions alone do not estimate conversion, churn or demand at a new price.

MaxDiff Analysis

Identifies which features customers value most:

Show sets of features
Ask: Most important? Least important?
Results inform tier packaging

For detailed research methods: See references/research-methods.md

When to Raise Prices

Signs It's Time

Market signals:

Competitors have raised prices
Prospects don't flinch at price
"It's so cheap!" feedback

Business signals:

Very high conversion rates (>40%)
Very low churn (<3% monthly)
Strong unit economics

Product signals:

Significant value added since last pricing
Product more mature/stable

Price Increase Strategies

Grandfather existing — New price for new customers only
Delayed increase — Announce 3-6 months out
Tied to value — Raise price but add features
Plan restructure — Change plans entirely

Rollout Methodology

A price change is a rollout, not a switch you flip. Sequence it to de-risk:

Test on new customers first. Raise the price only for new signups and watch conversion. New customers have no anchor and no relationship at stake, so they give you a clean read on whether the market accepts the number — before you touch a single existing account.
Don't reflexively grandfather forever. Grandfathering feels kind, but it can leave enormous money on the table. Run the math: a customer paying $50/mo who should be at $250/mo is a $2,400/yr gap — and $200/mo you're subsidizing indefinitely across your whole base. Grandfather as a transition (a grace period), not a permanent exemption.
Roll out small, then gradually. Move 5–10% of existing customers to the new price first. Watch churn and support volume for a cycle, then expand in staggered waves. A staggered rollout contains the blast radius and gives you an off-ramp if churn spikes.
Communicate the why, months ahead, with a generous offer. Tell customers why the price is changing (usually: more value shipped) well in advance. Soften it: lock-in-the-old-price-if-you-upgrade-to-annual-now, an extended grace window, or a one-time credit. Advance notice + a generous option converts a resentment moment into a loyalty one.

Expect — and accept — some churn. The customers most likely to leave over a justified increase are usually your least-profitable, highest-support, most price-sensitive accounts.

Pricing Page Best Practices

Above the Fold

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

Common Elements

Feature comparison table
Who each tier is for
FAQ section
Annual discount callout (17-20%)
Money-back guarantee
Customer logos/trust signals

Pricing Psychology

Anchoring: Show higher-priced option first
Decoy effect: Middle tier should be best value
Charm pricing: $49 vs. $50 (for value-focused)
Round pricing: $50 vs. $49 (for premium)

Pricing Page Teardown

When someone wants to audit an existing pricing page for clarity, transparency, and AI-readability (not the pricing strategy itself, and not conversion-rate optimization — that's cro), run a teardown that scores it across two axes and returns prioritized fixes:

Human buyer experience — value-prop clarity, plan differentiation, cognitive load, trust signals, pricing psychology, and price transparency.
AI-agent readiness — whether the LLMs and agents that increasingly shortlist and compare tools can actually read and quote your pricing: machine-readable prices (not locked in an image or behind "Contact us"), extractable FAQ/objection coverage, per-tier depth stated in text, and structured data. Buyers now ask ChatGPT/Perplexity/Claude "what's the best X and what does it cost?" before visiting — a pricing page an agent can't parse loses deals you never see.

Fast check — the "paste test": give the pricing URL to a browsing-capable AI (Perplexity, ChatGPT with search, Claude with web) — or paste the rendered page text — and ask "what are the plans and prices?" A clean miss means agents fetching your page will struggle too (a heuristic, not proof every agent fails).

The AI-readiness fixes are usually high-impact, low-effort (put prices in text, add Offer schema). Hand implementation to schema (Product/Offer JSON-LD) and ai-seo (extractability, AI-bot access, llms.txt).

For the full 10-dimension rubric, scoring, and report template: See references/pricing-page-teardown.md. (AI-agent-readiness lens adapted from Kyle Poyar / Growth Unhinged.)

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

Task-Specific Questions

What pricing research have you done?
What's your current ARPU and conversion rate?
What's your primary value metric?
Who are your main pricing personas?
Are you self-serve, sales-led, or hybrid?
What pricing changes are you considering?

churn-prevention: For cancel flows, save offers, and reducing revenue churn
cro: For optimizing pricing page conversion
ai-seo: For making the pricing page extractable/citable by AI (the teardown's AI-agent-readiness axis)
schema: For Product/Offer structured data so machines can read your tiers and prices
copywriting: For pricing page copy
marketing-psychology: For pricing psychology principles
ab-testing: For testing pricing changes
revops: For deal desk processes and pipeline pricing
sales-enablement: For proposal templates and pricing presentations