Recommend · Assess & Decide · Analysis & Finance
Recommend a skim, penetration, or neutral launch-pricing strategy
I get a defensible launch-pricing call (skim, penetration, or neutral) that follows from an explicit read of the decision factors, so the strategy is not a guess.
You receive: A JSON object { recommendation, factors: [{ factor, assessment, favors }] } where recommendation is one of skim / penetration / neutral.
Part of Set My Price
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Cost20 credits
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Example
A sample of what this play produces. Your result is generated for your inputs.
penetration
Factors
| Factor | Assessment | Favors |
|---|---|---|
| cost-structure | Marginal cost per play is a thin slice of the roughly 13% cost base implied by an estimated 87% gross margin (mostly LLM inference plus judge verification compute); the catalog build and platform-owned judge are fixed costs already sunk across the ~265-play catalog spanning 14 playbooks. Low marginal cost supports broad plan pricing (Standard $20/mo, Pro $60/mo, Ultra $180/mo) rather than reserving pricing power for a narrow early segment. | penetration |
| segment-price-sensitivity | The target customer is solo and early-stage founders and small product teams commissioning verifiable knowledge work, a segment that is credit- and cash-conscious pre-revenue. Standard at $20/month for 500 credits (10 to 40 credits per play, $0.40 to $1.60) keeps the entry price low enough for this segment to try the catalog rather than pricing only for buyers who would pay a premium regardless. | penetration |
| competitive-response-threat | The nearest substitutes are general-purpose AI chat assistants, freelance marketplaces, and static documentation tools, none of which freeze acceptance criteria and settle payment on a platform-owned judge's verdict before it pays. That verification layer is not trivially copied in the near term, so the risk of an immediate price war from a feature-equivalent competitor is currently low. | skim |
| capacity-constraints | The catalog runs on an automated, platform-owned judge, so volume is software-scaled rather than bounded by human throughput; the illustrative 1 founder-operator, 30-plays-a-week concierge capacity applies only to the paid-fulfillment path, not to the self-serve catalog. With no binding capacity ceiling on the core catalog, holding volume back with a high price would not be protecting any scarcity that actually exists. | penetration |
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