S
WeatherRisk Alert API
4.20
Derivation Chain
Step 1
Advances in real-time global weather data visualization technology
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Step 2
Weather data utilization services
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Step 3
Weather-based sales risk early alert API for Small Business Owners
Problem
Approximately 300,000 Small Business Owners operating outdoor cafes, food trucks, and mobile shops are directly affected by weather and make business decisions based solely on weather forecasts. When the precipitation probability is 50%, they have no criteria for deciding whether to open. Unnecessary commuting and material preparation result in average daily losses of $112-$225 (~150,000-300,000 KRW), occurring more than 20 days per year.
Solution
A business recommendation alert service combining the Korea Meteorological Administration's ultra-short-term forecast API with historical sales-weather correlation analysis. (1) Ultra-short-term (6-hour) weather risk score based on business location, (2) industry-specific (cafe/food truck/market) business recommendations based on historical data, (3) KakaoTalk alerts sent twice — the evening before and the morning of.
NUMR-V Scores
NUMR-V Scoring System
| 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. |
SaaS N=.15 U=.20 M=.15 R=.30 V=.20
Senior N=.25 U=.25 M=.05 R=.30 V=.15
Feasibility (68%)
Data Availability
19.2/25
Feasibility Breakdown
| 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. |
Market Validation (55/100)
Validation Breakdown
| 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. |
Technical Requirements
Data Pipeline [medium]
Backend [medium]
Frontend [low]