Marketplace Trending Radar
Under maintenancePricing
$1.20 / 1,000 result rows
Marketplace Trending Radar
Under maintenanceTrack 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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Hamza
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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
newThisRunwith 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:directionisnew,rising,fallingorsteady, andrankChangeshows 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
| Field | Type | Default | Notes |
|---|---|---|---|
| Search terms to track | list | wireless earbuds | Up to 20 terms per run. Taobao reads work best with Chinese terms. |
| Marketplaces | multi-select | all six | Where to track the terms. |
| Products to track per marketplace | number | 30 | How many top products are compared run by run. |
| Tracking scope | string | default | Snapshots are kept per scope; rerunning the same scope is what makes trends appear. |
| Parallel reads | number | 4 | How many marketplace reads run at once. |
Good to know
- Partial runs still deliver. A marketplace that cannot be read is marked
errorwith 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.