Unified search across secondhand marketplaces — aggregated listings & alerts

Secondhand shoppers and casual resellers face fragmented discovery across dozens of apps and niche marketplaces, spending hours chasing listings and comparing duplicates; this problem affects an estimated 200 million active secondhand shoppers globally who have no single place to surface cross-platform inventory quickly. Sellers and brokers also lose sell-through when listings are mispriced or duplicated across channels, creating inefficiency and missed matches. You could build an aggregator that indexes major marketplaces, normalizes metadata, and delivers deduped, AI-matched search and real-time alerts—using computer vision and NLP to cluster cross-posts and provide automated pricing comparisons. A lightweight subscription plus affiliate/referral model targeting roughly $20 ARPU/year makes the economics plausible, but the product faces clear technical and commercial hurdles: data access (APIs vs scraping and platform TOS), maintaining high dedupe precision at scale, and converting users into paying subscribers. The market dynamics favor entry now—resale adoption is accelerating, and the addressable market is about $4.0B (200M users x $20 ARPU), with a market score of 92/100, revenue potential 84/100, and medium competition—while AI advances make accurate cross-listing matching practical. Pursue this opportunity cautiously and focus early on a vertical or geography, secure marketplace partnerships, and differentiate on precision matching, transparent provenance, and conservative unit economics to prove the model before broad scaling.