See a user's most-liked posts — native in-app ranked view (quick UX)

Executive Summary

Many creators and power users (an addressable group of roughly 200 million people) struggle to surface and present their best posts quickly for pitches, sponsor conversations, or portfolio links because platform UIs bury high-signal content in feeds, bookmarks, or analytics dashboards. The result is wasted time, missed revenue opportunities, and difficulty proving impact in a few compelling examples. A lightweight native in-app ranked view would show a user’s most-liked posts across configurable windows (last 7/30/90 days or all-time), let them filter by network or content type, and provide AI-generated one-line summaries and highlight snippets for each post to make sharing and pitching immediate. The product could be a freemium mobile SDK or standalone app that targets $20/year ARPU with premium export, team decks, and cross-network aggregation features. This is an attractive moment: the creator economy continues to expand, decentralized platforms like Bluesky and Mastodon are fragmenting attention, and generative models now make instant summarization and signal extraction practical; combined these justify a $4.0B TAM assumption (200M creators x $20/year) and align with a market score of 74/100 and revenue potential of 92/100. Demand drivers are straightforward, but timing matters because APIs and platform openness are shifting quickly. To stand out you must deliver near-zero-friction UX (native, one-tap ranked view), reliable engagement-weighted ranking algorithms, and crisp AI summaries that save users minutes per pitch, while emphasizing privacy-preserving cross-network aggregation. Real challenges include medium competition, dependence on platform APIs and permissions, moderation and attribution complexity, and the sales motion to move creators from free tools to a paid $20/year product, so early partnership and technical defensibility should be priorities.