Xianyu / Goofish Resale Market & Arbitrage Intelligence

Use this Actor to analyze jd.com product, seller and price and return decision-ready structured signals. It is designed for repeatable human, API, Apify AI, and MCP-driven workflows.

Analyze live public Xianyu/Goofish resale listings through Alibaba's signed H5/MTOP transport and turn raw marketplace rows into decision-ready resale intelligence.

What it returns

Each row includes listing ID, title, live price in CNY, city, seller nickname, image, want count, free-shipping and bargainability flags, plus QuanMatrix decision fields: demandScore, optional benchmark discountToReferencePct and grossSpreadCny, snapshot priceDelta / priceDeltaPct, arbitrageScore, and agentAction.

The Actor also stores a reusable SNAPSHOT and a MARKET_SUMMARY with median price, buy-candidate count, average demand score and top opportunities.

Why use this Actor

Most marketplace scrapers stop at extraction. This Actor is designed for repeated resale decisions. Supply a previous SNAPSHOT to measure exact price changes. Supply referencePriceCny to calculate benchmark spread and discount. The deterministic scoring layer turns those signals into BUY_CANDIDATE, WATCH, or MONITOR actions that downstream agents can consume without inventing their own business logic.

Key features

It combines an anonymous signed H5/MTOP live feed with listing normalization, exact snapshot price deltas, reference-price spread analytics, a demand score based on observable marketplace signals, an arbitrage score, deterministic agent actions, reusable snapshots, and a compact market summary for recurring monitoring workflows.

Input

• maxResults: 1-300 live listings.
• keywordContains: optional local title filter.
• minPriceCny / maxPriceCny: optional price band.
• referencePriceCny: optional retail, resale or sourcing benchmark.
• sortBy: arbitrageScore, demandScore, price, or wantCount.
• previousSnapshot: prior rows from SNAPSHOT for exact price deltas.

Example

{
  "maxResults": 50,
  "referencePriceCny": 1200,
  "sortBy": "arbitrageScore",
  "previousSnapshot": []
}

Use cases

Use it for resale-arbitrage scouting, second-hand market pricing, cross-market sourcing comparisons, price-drop monitoring, demand-signal research, and agentic ecommerce workflows. Twenty ready-made Task blueprints cover distinct commercial intents such as phones, laptops, gaming hardware, collectibles, luxury, wholesale-to-resale spread and recurring market pulse.

Data transport

The Actor does not use brittle page HTML as its primary transport. It establishes an anonymous H5/MTOP session, obtains the temporary MTOP token, signs requests with the platform's normal H5 request scheme, and reads the structured home-feed response. No account credential is required for the supported v1 workflow.

Limitations

v1 intentionally claims only the anonymous live home feed plus local title filtering. Authenticated keyword-search coverage is not advertised until it is independently hardened. Public platform contracts can change or throttle. Use the data in accordance with applicable laws and platform terms, and avoid decisions that unlawfully discriminate or misuse seller information.

Pricing

Pay-per-event is tied to the useful customer outcome: one enriched resale-intelligence row. Tiered FREE / BRONZE / SILVER / GOLD pricing is managed by the factory pricing governor; higher account tiers inherit GOLD until a distinct enterprise case is justified.

Output for automation

Dataset rows are JSON-first and stable for API, MCP and agent workflows. SNAPSHOT can be fed into a future run, while MARKET_SUMMARY gives a compact market-level result suitable for alerts and scheduled monitoring.