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Get Started Free →When the user wants to plan, design, or optimize pricing strategy and structure. Also use when the user mentions "pricing strategy," "pricing model," "pricing tiers," "freemium," "value-based pricing," "anchoring," "price structure," or "monetization strategy." For pricing page, use pricing-page-generator.
.claude/skills/mkurman-pricing-strategy/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 10% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 38% | 0% |
| case-17 | ✗→✓ | ▲ Improved | -27% | 0% |
| case-18 | ✗→✓ | ▲ Improved | -37% | 0% |
| case-04 | ✓→✓ | ＝ Same ✓ | 42% | 0% |
-|-----| | Subscription | Recurring; monthly/annual; most SaaS | | Freemium | Free tier + paid; adoption then conversion | | Usage-based | Pay per use; API, credits | | One-time | Perpetual license; some tools | | Hybrid | Base + usage; tiered + overage |
Variable-cost products (compute, API, AI): When per-user cost varies widely (heavy users cost 10×+ light users), uniform subscription often fails. Use usage-based, credits, or tiered-by-usage; align price to cost structure.
Discounts apply on top of base pricing. See discount-marketing-strategy for:
Principle: Set base price for long-term value; use discounts tactically for acquisition, retention, or cash flow.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 22,656 | 20,318 | -10% | 1 | 1 | 0% | 3,567 | 3,907 | +10% | 0 | 0 | — |
case-02 | fail→fail | 19,131 | 18,561 | -3% | 1 | 1 | 0% | 3,009 | 3,314 | +10% | 0 | 0 | — |
case-03 | fail→fail | 24,328 | 18,147 | -25% | 1 | 1 | 0% | 3,590 | 3,375 | -6% | 0 | 0 | — |
case-04 | pass→pass | 15,145 | 17,043 | +13% | 1 | 1 | 0% | 2,259 | 3,214 | +42% | 0 | 0 | — |
case-05 | pass→pass | 12,779 | 15,540 | +22% | 1 | 1 | 0% | 1,936 | 2,812 | +45% | 0 | 0 | — |
case-06 | pass→pass | 14,552 | 14,373 | -1% | 1 | 1 | 0% | 2,302 | 2,687 | +17% | 0 | 0 | — |
case-07 | pass→pass | 14,056 | 16,215 | +15% | 1 | 1 | 0% | 2,143 | 3,130 | +46% | 0 | 0 | — |
case-08 | pass→pass | 14,427 | 15,085 | +5% | 1 | 1 | 0% | 1,990 | 2,729 | +37% | 0 | 0 | — |
case-09 | pass→pass | 9,649 | 9,373 | -3% | 1 | 1 | 0% | 1,487 | 1,848 | +24% | 0 | 0 | — |
case-10 | pass→pass | 6,219 | 9,638 | +55% | 1 | 1 | 0% | 988 | 1,974 | +100% | 0 | 0 | — |
case-11 | pass→pass | 9,256 | 9,810 | +6% | 1 | 1 | 0% | 1,342 | 2,051 | +53% | 0 | 0 | — |
case-12 | pass→pass | 14,005 | 11,789 | -16% | 1 | 1 | 0% | 2,115 | 2,301 | +9% | 0 | 0 | — |
case-13 | fail→pass | 23,045 | 27,429 | +19% | 1 | 1 | 0% | 3,431 | 4,741 | +38% | 0 | 0 | — |
case-14 | pass→pass | 14,365 | 13,421 | -7% | 1 | 1 | 0% | 2,208 | 2,621 | +19% | 0 | 0 | — |
case-15 | pass→pass | 13,439 | 12,987 | -3% | 1 | 1 | 0% | 2,079 | 2,416 | +16% | 0 | 0 | — |
case-16 | pass→pass | 14,911 | 15,864 | +6% | 1 | 1 | 0% | 2,300 | 2,859 | +24% | 0 | 0 | — |
case-17 | fail→pass | 13,639 | 6,295 | -54% | 1 | 1 | 0% | 2,061 | 1,508 | -27% | 0 | 0 | — |
case-18 | fail→pass | 9,527 | 3,428 | -64% | 1 | 1 | 0% | 1,490 | 939 | -37% | 0 | 0 | — |
case-19 | pass→pass | 22,691 | 19,752 | -13% | 1 | 1 | 0% | 3,555 | 3,620 | +2% | 0 | 0 | — |
case-20 | pass→pass | 12,694 | 15,855 | +25% | 1 | 1 | 0% | 1,968 | 2,863 | +45% | 0 | 0 | — |
case-21 | pass→pass | 26,880 | 25,843 | -4% | 1 | 1 | 0% | 6,168 | 6,663 | +8% | 0 | 0 | — |
case-22 | pass→pass | 16,405 | 18,788 | +15% | 1 | 1 | 0% | 2,703 | 3,805 | +41% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +18 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.