Assistant-ready listing program

Marketplace-native AI is now a primary ranking layer. Amazon’s shopping assistant reaches ~250M+ users, and AI-assisted shoppers convert roughly 60% higher than keyword search — so for accessories and peripherals sold on marketplaces, the assistant is the front door. This project rewrites listings for how the assistant reads, not how the old keyword box did.

Why this, mechanically. Marketplace assistants match on semantic intent — use cases, compatibility, setup — and weight review sentiment. A keyword-stuffed listing underperforms a listing that answers “will this work with my console” directly. Review-theme mining matters because the assistant surfaces complaint patterns whether or not you address them; better to know which ones before a shopper hears them.

Deliverable. The top marketplace accessory listings rewritten for semantic intent, plus a review-theme analysis flagging complaint patterns the assistant may surface.

Finish line. The priority listings are rewritten, and assistant surfacing and conversion are measurably better than the keyword baseline.

Marketplace weighting of review sentiment accrues over months and cannot be shortcut — scope this as a standing capability, not a one-time pass. Whether it belongs on your roadmap at all is a scope decision.