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As ultra-low-cost stores like Daiso and Cheonwon Mall (1,000-won stores) rapidly expand, small business owners in stationery, household goods, and beauty retail have a rule of thumb that sales drop 20-40% when a Daiso opens nearby. However, it is difficult to obtain advance information on new Daiso store openings, and data-driven decisions on how to differentiate product assortments are impossible.
Automatically crawl information on new Daiso and Cheonwon Mall store openings, and send an early warning when a store is scheduled to open within a 1km radius of your store. Analyze the Daiso's main categories, recommend non-overlapping differentiated product categories, and visually show 'opportunity areas where you can survive' based on foot traffic and competitor store density in the surrounding trade area.
| 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. |