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When trending beverages like Starbucks' Aerocano emerge, 90,000+ independent cafes nationwide need to launch similar menu items within 2–4 weeks to stay competitive. However, manually simulating the cost, margin, and pricing for a single new menu item using spreadsheets takes 3–5 hours, and failing to reflect ingredient price fluctuations frequently results in margins 5–10 percentage points lower than projected.
(1) Auto-calculate costs based on real-time ingredient prices upon entering a trending beverage recipe (2) Simulate selling price, margin, and break-even point (3) Benchmark pricing against similar menu items at nearby cafes.
| N Novelty | 1-5 | How uncommon the service is in market context. |
| U Urgency | 1-5 | How urgently users need this problem solved now. |
| M Market | 1-5 | Market size and growth potential from proxy indicators. |
| R Realizability | 1-5 | Buildability for a small team with realistic constraints. |
| V Validation | 1-5 | Validation signal quality from competition and demand data. |
| Tech Complexity | / 40 | Difficulty of core implementation stack. |
| Data Availability | / 25 | Practical availability and cost of required data. |
| MVP Timeline | / 20 | Expected time to ship a usable MVP. |
| API Bonus | / 15 | Bonus for viable public API leverage. |
| Competition | / 20 | Signal quality from competitor landscape. |
| Market Demand | / 20 | Demand proxies from search and mention patterns. |
| Timing | / 20 | Fit with current shifts in tech, behavior, and regulation. |
| Revenue Signals | / 15 | Reference evidence for monetization viability. |
| Pick-Axe Fit | / 15 | How well the concept serves participants in a trend. |
| Solo Buildability | / 10 | Practicality for lean-team implementation. |