Pricing strategy

Skill dills122/ai-central/templates/skills/imported/pm-skills/pm-product-strategy/skills/pricing-strategy

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Analyze and design pricing strategies including pricing models, competitive pricing analysis, willingness-to-pay estimation, and price elasticity. Use when setting prices, evaluating pricing models, preparing for a pricing change, or comparing freemium vs paid approaches.

SKILL.md

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Pricing Strategy

Design a pricing strategy grounded in value delivery, competitive positioning, and willingness to pay.

Context

You are developing a pricing strategy for $ARGUMENTS.

If the user provides files (competitor pricing, survey data, financial models, or usage data), read them first. Use web search to research competitor pricing if needed.

Instructions

Understand the value delivered:
- What is the core value proposition?
- What is the customer's alternative (and its cost)?
- What quantifiable outcomes does the product deliver? (time saved, revenue gained, cost reduced)
- What is the customer's willingness to pay based on that value?

Evaluate pricing models — recommend the best fit:

Model	Best For	Example
Flat-rate	Simple products, predictable costs	Basecamp ($99/mo flat)
Per-seat	Collaboration tools, team products	Slack, Figma
Usage-based	Infrastructure, API products	AWS, Twilio
Tiered	Products with distinct user segments	Most SaaS (Free/Pro/Enterprise)
Freemium	Products with viral/network effects	Spotify, Notion
Freemium + usage	Platform products	Vercel, OpenAI API
Value-based	High-impact enterprise tools	Salesforce, Palantir

Analyze competitive pricing:
- Map competitor pricing tiers and what's included
- Identify where your product sits (premium, mid-market, budget)
- Find pricing gaps or opportunities
- Note any industry pricing conventions
Design the pricing structure:
- Tiers: Define 2-4 tiers with clear differentiation
- Feature gating: Which features go in which tier? (Use value metrics, not arbitrary limits)
- Value metric: What unit do you charge on? (users, events, storage, API calls)
- Anchor pricing: Set the most popular tier to feel like the obvious choice
- Annual discount: Typically 15-20% off monthly pricing
Estimate price sensitivity:
- Van Westendorp Price Sensitivity Meter (if survey data available):
  - Too cheap → quality concerns
  - Cheap → good value
  - Expensive → starting to hesitate
  - Too expensive → won't buy
- Alternatively, estimate based on competitor pricing and value delivered
Plan pricing experiments:
- A/B test pricing pages (different price points, tier names, feature bundles)
- Founder-led sales conversations to test willingness to pay
- Landing page tests with different price anchors
- Cohort analysis of conversion rates by price point

Output a pricing recommendation:

Recommended Model: [Model type]
Value Metric: [What you charge on]

| Tier | Price | Target Segment | Key Features | Positioning |
|---|---|---|---|---|

Key Assumptions:
- [Assumption] → [How to test]

Risks:
- [Risk] → [Mitigation]

Think step by step. Save as markdown. Flag any assumptions that need validation before launch.

Gives 0 of the 12 instructions most research analysis skills give

Counted across 1,063 of the 1,754 authors here whose files we hold, read 2026-08-06

generate a markdown reportin 32 of 1063, across 17 files
cite each claim's sourcein 31 of 1063, across 14 files
define the ideal customer profilein 20 of 1063, across 2 files
search for companies matching the criteriain 20 of 1063, across 2 files
assign a fit score from one to tenin 20 of 1063, across 2 files
format results in a scannable markdown templatein 20 of 1063, across 2 files
analyze the codebase to understand the productin 19 of 1063, across 1 file
ask clarifying questions about the value propositionin 19 of 1063, across 1 file
look for signals of immediate needin 19 of 1063, across 1 file
identify the target decision maker rolein 19 of 1063, across 1 file
suggest a personalized contact strategyin 19 of 1063, across 1 file
provide conversation starters for outreachin 19 of 1063, across 1 file

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.