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Limited-edition release schedules from brands like Starbucks, Nike, LEGO, and Pokémon are scattered across individual brand apps, social media, and community forums, causing collectors to miss drops and lose open-run opportunities. On average, limited-edition collectors spend 3–5 hours per week searching for release info, and fail to even learn about 3 out of 10 drops.
Automatically aggregates limited-edition release schedules from major brands like Starbucks, Nike, and LEGO into a unified calendar. Users register interest by brand and category to receive alerts 3 days before and on the morning of each release. Shares online stock availability by store and offline store locations with community-sourced queue-line updates.
| 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. |