Pricing Monetization Advisor
Use this skill to decide whether a product should make money, who should pay, and how value should be packaged. Optimize for realistic willingness to pay, simplicity, and strategic fit instead of pricing-theater.
Workflow
- Identify the user, use case, urgency, and current alternative.
- Determine whether the product creates recurring value, one-time value, or mostly signaling value.
- Decide whether monetization should happen now, later, or not at all.
- Evaluate packaging options before debating exact price points.
- Recommend the simplest pricing test that can produce learning.
Pricing Lenses
Always inspect:
- who gets enough value to pay
- what painful alternative currently exists
- whether value is episodic or recurring
- whether pricing should be per seat, per usage, per project, per report, or subscription
- whether free should be a growth surface, not just generosity
- whether the paid layer is meaningfully better than the free layer
- whether operational cost or model cost makes the offer fragile
- whether bespoke services are masquerading as software revenue
- whether packaging matches the buyer, not just the user
Output Shape
Unless asked otherwise, include:
- should this be monetized now
- likely payer
- likely pricing model
- what belongs in free vs paid
- risks in the proposed model
- smallest pricing or monetization test
- what would change the recommendation
Monetization Rules
- Do not force monetization onto products that are better as leverage, credibility, or audience assets.
- Recommend packaging before price precision.
- Be skeptical of premium plans with no sharply differentiated value.
- Name when the real offer is service, data, software, media, or intelligence.
- Flag cost structure risks early for AI-heavy products.
- Prefer a narrow paid use case over broad but fuzzy monetization.
1---2name: pricing-monetization-advisor3description: Pricing, packaging, and monetization strategy skill for product ideas, SaaS tools, AI products, information products, dashboards, APIs, newsletters, and emerging software businesses. Use when Codex should evaluate what to charge for, who should pay, how to package value, what pricing model to test, or whether a product should be monetized at all.4---56# Pricing Monetization Advisor78Use this skill to decide whether a product should make money, who should pay, and how value should be packaged. Optimize for realistic willingness to pay, simplicity, and strategic fit instead of pricing-theater.910## Workflow11121. Identify the user, use case, urgency, and current alternative.132. Determine whether the product creates recurring value, one-time value, or mostly signaling value.143. Decide whether monetization should happen now, later, or not at all.154. Evaluate packaging options before debating exact price points.165. Recommend the simplest pricing test that can produce learning.1718## Pricing Lenses1920Always inspect:2122- who gets enough value to pay23- what painful alternative currently exists24- whether value is episodic or recurring25- whether pricing should be per seat, per usage, per project, per report, or subscription26- whether free should be a growth surface, not just generosity27- whether the paid layer is meaningfully better than the free layer28- whether operational cost or model cost makes the offer fragile29- whether bespoke services are masquerading as software revenue30- whether packaging matches the buyer, not just the user3132## Output Shape3334Unless asked otherwise, include:3536- should this be monetized now37- likely payer38- likely pricing model39- what belongs in free vs paid40- risks in the proposed model41- smallest pricing or monetization test42- what would change the recommendation4344## Monetization Rules4546- Do not force monetization onto products that are better as leverage, credibility, or audience assets.47- Recommend packaging before price precision.48- Be skeptical of premium plans with no sharply differentiated value.49- Name when the real offer is service, data, software, media, or intelligence.50- Flag cost structure risks early for AI-heavy products.51- Prefer a narrow paid use case over broad but fuzzy monetization.
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