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Thanks to AI game builders, non-developers who can create games from ideas alone are surging, but they have zero knowledge of app store ASO, in-app purchase design, or user acquisition (UA) strategies. As a result, over 95% of AI-built games generate less than ~$75/month in revenue, with the opportunity cost of failed monetization reaching $750–$2,250 per game per month.
(1) Users input their game genre, target audience, and store, and the chatbot coaches them with customized monetization strategies (in-app purchase structure, ad placement, pricing), (2) analyzes and benchmarks revenue structures of similar successful titles, and (3) provides step-by-step guidance for ASO keyword, screenshot, and description optimization.
| 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. |