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Marketplace Trending Radar

Under maintenance

Pricing

$1.20 / 1,000 result rows

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Marketplace Trending Radar

Marketplace Trending Radar

Under maintenance

Track what is rising for any product search term across Amazon, eBay, Walmart, AliExpress, Alibaba and Taobao: rerun the same terms over time and get every product marked new, rising, falling or steady, with a 0-100 trend score, rank changes and a cross-marketplace breakout flag.

Pricing

$1.20 / 1,000 result rows

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Developer

Hamza

Hamza

Maintained by Community

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2 days ago

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What is rising right now — and what just appeared? Track any product search term across Amazon, eBay, Walmart, AliExpress, Alibaba and Taobao: each run reads the current top products for your terms and compares them against the previous snapshot, so every product comes back marked new, rising, falling or steady, with a 0-100 trend score and a cross-marketplace breakout flag when the same product surfaces on several marketplaces at once. No account and no login are needed: type your terms, press start, and rerun whenever you want a fresh read — the second run is where the trends appear. Pages are read directly, with no browser and nothing to sign in to.

What you can do with it

  • Catch breakouts early. Products that appear on several marketplaces at the same time are flagged crossMarketplace — the strongest early signal that a product is taking off.
  • See movement, not just a snapshot. Rerun the same terms daily or weekly: every product is compared against the previous run and marked with its rank change and direction.
  • Spot new arrivals. Products that were not in the previous snapshot are marked newThisRun with their first-seen date.
  • Rank by momentum. The 0-100 trend score blends rank position, the marketplace's own demand signals (sold units, ratings), newness and cross-marketplace presence, so the hottest products sort to the top.
  • Feed a spreadsheet or a schedule. Every field is a plain column — export to Excel, Google Sheets, CSV or JSON, or put the actor on a schedule and watch trends build up.

What you get

One row per product per marketplace per search term. Abridged real example:

{
"keyword": "wireless earbuds",
"marketplace": "aliexpress",
"rank": 3,
"title": "TWS Wireless Bluetooth Headset ...",
"price": 0.33,
"currency": "USD",
"soldCount": 45210,
"trendScore": 87,
"direction": "new",
"newThisRun": true,
"rankChange": null,
"crossMarketplace": true,
"matchedOn": ["alibaba", "taobao"],
"url": "https://www.aliexpress.com/item/3256807042125723.html"
}

How the trend signals work

  • Snapshots live in a key-value store named trend-radar-state, kept per tracking scope. Rerun with the same scope and terms and every product is compared against the previous snapshot: direction is new, rising, falling or steady, and rankChange shows how many places it moved. Use a different scope per project or client so trackings never mix.
  • The first run is the baseline. Everything is marked new; from the second run on, movement is real.
  • Trend score (0-100) blends four parts: position near the top of the site's own best-selling ordering, the raw demand signal (sold units or ratings), a boost for being new this run, and a boost for appearing on several marketplaces at once.
  • Cross-marketplace matching compares product titles across marketplaces within the same search term and flags likely matches.

Input

FieldTypeDefaultNotes
Search terms to tracklistwireless earbudsUp to 20 terms per run. Taobao reads work best with Chinese terms.
Marketplacesmulti-selectall sixWhere to track the terms.
Products to track per marketplacenumber30How many top products are compared run by run.
Tracking scopestringdefaultSnapshots are kept per scope; rerunning the same scope is what makes trends appear.
Parallel readsnumber4How many marketplace reads run at once.

Good to know

  • Partial runs still deliver. A marketplace that cannot be read is marked error with the reason; everything else is tracked normally.
  • Taobao speaks Chinese. Its catalogue only lists terms from its own vocabulary; other terms return an explanatory note instead of fake numbers.
  • Snapshots persist between runs of the same actor, so schedules and manual reruns build one continuous trend history per scope.