When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' 'monetization,' 'how much should I charge,' 'my pricing is wrong,' 'pricing page,' 'annual vs monthly,' 'per seat pricing,' 'should I offer a free plan,' 'pricing page teardown,' 'pricing page audit,' 'is my pricing page AI-readable,' or 'can AI read my pricing.' Use this whenever someone is figuring out what to charge, how to structure their plans, or wants to audit a pricing page (for humans and for the AI agents that shortlist tools). For in-app upgrade screens, see paywalls. For offer construction (bonuses, guarantees, value framing, naming) on services/courses/coaching/high-ticket B2B, see offers.
Copy the skill from the publisher's repository (skills/pricing/SKILL.md). PlugMCP lists it. We do not host or rewrite the file.
README
name: pricing
description: "When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' 'monetization,' 'how much should I charge,' 'my pricing is wrong,' 'pricing page,' 'annual vs monthly,' 'per seat pricing,' 'should I offer a free plan,' 'pricing page teardown,' 'pricing page audit,' 'is my pricing page AI-readable,' or 'can AI read my pricing.' Use this whenever someone is figuring out what to charge, how to structure their plans, or wants to audit a pricing page (for humans and for the AI agents that shortlist tools). For in-app upgrade screens, see paywalls. For offer construction (bonuses, guarantees, value framing, naming) on services/courses/coaching/high-ticket B2B, see offers."
metadata:
version: 2.1.4
Pricing Strategy
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
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
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.
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?
Related Skills
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