pricing

SKILL.md

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

~$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

Analyze intersections to find optimal pricing zone.

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?

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