Good day @casey-chow,
Thanks again for engaging on this. I wanted to share a prioritized set of suggestions that we believe would materially improve app discovery, quality signals, and overall ecosystem health:
-
User ratings across the board
Allow all users to rate apps. This creates a strong, scalable signal around quality and gives you better data to rank and surface apps effectively. -
Category sorting based on actual usage
Ranking apps within categories based on real engagement (vs. primarily featuring established names) would better reflect what users are finding valuable and create a more merit-based ecosystem. I see the apps on the current store never change, are static and not related to actual ussage. -
Initial traffic seeding for new apps
New apps shouldn’t sit at zero usage for extended periods. Even a small amount of guaranteed exposure would help overcome the cold-start problem and generate meaningful signals/data for openAI to analyze. -
Language-based filtering (default to user’s language)
Let users filter apps by language, with a default that prioritizes their primary language. This should significantly improve relevance and engagement. -
Leverage app metadata more effectively
Direct prompts included in our app’s metadata could play a larger role in indexing, categorization, and surfacing apps. -
“New apps” section
A dedicated section for recently launched apps would improve discovery and give builders an initial window to gain traction. -
Dedicated “Games” category
This feels like a high-potential vertical that likely deserves its own category.
Appreciate you taking this into consideration.
Best,
Jonathan