Temu Product Price Tracker

Compare Temu Public Pages, Schema Org Product and return product change rows with price, stock, availability, seller, and source evidence.

What it does

• Processes configured public sources or user-provided records for focused temu product price tracker monitoring.
• Emits structured rows with source references, stable identifiers, confidence, warnings, and run summary fields.
• Supports sample-mode runs so Apify Store QA and first-time users can inspect output without depending on live third-party availability.

What it does not do

• Does not scrape private, login-only, paywalled, or access-restricted data unless the user provides approved credentials for a source they control.
• Does not guarantee every field is available from every source; missing or blocked fields are returned as warnings or nulls.
• Does not make legal, financial, compliance, procurement, medical, safety, or regulatory decisions.

Who this is for

E-commerce, marketplace, pricing, merchandising, product, and market research teams use this actor when they need focused temu product price tracker output instead of a broad generic scraper or manual checking.

Buyer outcomes

• Detect temu product price tracker product changes without manually comparing product scraper runs or catalog snapshots.
• Prioritize action with product identifiers, current/previous price, availability, stock state, seller context, confidence, and source URL.
• Route product-change records into pricing, merchandising, competitive intelligence, alerting, or marketplace operations workflows.

Sources monitored

• Temu Public Pages
• Schema Org Product

Input

• sourceMode: use sample for a smoke run or startUrls for product pages, scraper dataset docs, catalog snapshots, or pricing sources.
• startUrls: product, SKU, marketplace, catalog, pricing, availability, stock, review, or scraper-output URLs.
• sourceIds: approved product, marketplace, catalog, or dataset source identifiers.
• maxItems: bounded number of product records or product changes to return.
• sinceLastRun: emit only new or changed product states when scheduled.
• watchlistTerms: SKU, product, brand, seller, price, stock, availability, or category terms.
• webhookUrl: optional destination for price, stock, availability, or catalog-change alerts.

How it transforms the input

• Input: product scraper dataset, product page, catalog snapshot, marketplace listing, pricing feed, or availability record.
• Transformation: normalize product identifiers and compare price, stock, availability, seller, title, rating, or shipping fields.
• Output: product-change record with product identifier, product name, current/previous price, availability, stock state, change type, timestamp, source URL, and confidence.

Output

The actor returns e-commerce product-change records with product identifiers, product names, current and previous prices, stock state, availability, seller context, source URLs, timestamps, and confidence.

Family-specific fields to expect:

• productIdentifier: Stable product, SKU, listing, or catalog identifier.

• productName: Product or listing name.

• currentPrice: Current observed price when available.

• previousPrice: Previous observed price when change tracking is available.

• currency: Currency for price fields.

• availability: Availability state from the source.

• stockStatus: In-stock, out-of-stock, limited, preorder, or unknown state.

• changeType: Observed product state change, such as price-change, stock-change, or source-observed.

• sourceUrl: Source-backed product or dataset URL.

• detectedAt: Timestamp when the product state was detected.

• recordId: Stable record ID for exports, dedupe, and downstream joins.

• title: Human-readable record title for review and export.

• sourceName: Source identifier used to trace where the record came from.

• sourceUrl: Direct source URL for review and audit.

• dedupeKey: Stable key used for delta mode and duplicate suppression.

• retrievedAt: Timestamp showing when the actor retrieved or generated this record.

• score: Normalized field for filtering, routing, or downstream review.

• scoreReasons: Buyer-readable explanation for the score or match.

• confidence: Normalized field for filtering, routing, or downstream review.

• errors: Normalized field for filtering, routing, or downstream review.

• runSummary: Run-level summary for counts, filters, charges, and next actions.

Pricing

This actor uses Apify pay-per-event pricing. Current public listing guidance: $29-$49 / 1,000 launch validation records until public data proof is complete. Charges are tied to buyer-visible value events such as product-result, product-detail, change-alert, dataset-processed, record-saved, enriched-record. Small validation runs are supported so you can inspect output before scaling a schedule.

• product-result: Charge after producing one Temu product result. Typical price: $0.003. A run that produces 10 matching records charges only for the matched buyer-value events and remains capped by the run limit.
• product-detail: Charge after producing one product detail enrichment. Typical price: $0.007. A run that produces 10 matching records charges only for the matched buyer-value events and remains capped by the run limit.
• change-alert: Charge after producing one price or stock alert. Typical price: $0.045. A run that produces 10 matching records charges only for the matched buyer-value events and remains capped by the run limit.
• dataset-processed: Base charge when Temu Product Price Tracker writes a non-empty default dataset. Typical price: $0.011. A run that produces 10 matching records charges only for the matched buyer-value events and remains capped by the run limit.
• first-run-cap: Recommended first run budget cap. Typical price: $2.000. Start with the default small run, inspect the dataset, then raise maxItems or schedule recurring runs.

API example

curl -X POST "https://api.apify.com/v2/actors/YOUR_USERNAME~temu-product-price-tracker/runs" \
+  -H "Authorization: Bearer $APIFY_TOKEN" \
+  -H "Content-Type: application/json" \
+  -d '{"maxItems":10,"sourceIds":["TEMU-PUBLIC-PAGES","SCHEMA-ORG-PRODUCT"],"includeSourceUrls":true,"includeMatchReasons":true,"outputMode":"buyer-ready-records"}'

Recommended first run

{
    "maxItems": 10,
    "sourceIds": [
        "TEMU-PUBLIC-PAGES",
        "SCHEMA-ORG-PRODUCT"
    ],
    "includeSourceUrls": true,
    "includeMatchReasons": true,
    "outputMode": "buyer-ready-records"
}

Sample output

Sample status: sample_unavailable at https://zentra.nimblique.studio/external/actor-review/samples/temu-product-price-tracker.json. No fake sample is published; run a bounded real sample refresh before using examples in promotion.

Recommended public tasks

[
    {
        "name": "Check 10 product changes",
        "description": "Low-cost validation run for checking product, price, stock, availability, and source fields.",
        "input": {
            "maxItems": 10,
            "sourceIds": [
                "TEMU-PUBLIC-PAGES",
                "SCHEMA-ORG-PRODUCT"
            ],
            "includeSourceUrls": true,
            "includeMatchReasons": true,
            "outputMode": "buyer-ready-records",
            "actorSlug": "temu-product-price-tracker"
        }
    },
    {
        "name": "Daily product change check",
        "description": "Recurring batch for product price, stock, seller, rating, and catalog changes.",
        "schedule": "Daily during local business hours",
        "input": {
            "maxItems": 25,
            "sourceIds": [
                "TEMU-PUBLIC-PAGES",
                "SCHEMA-ORG-PRODUCT"
            ],
            "includeSourceUrls": true,
            "includeMatchReasons": true,
            "outputMode": "buyer-ready-records",
            "actorSlug": "temu-product-price-tracker"
        }
    }
]

Example use cases

• Track temu product price tracker product price, stock, title, seller, rating, and availability changes.
• Send product-change records into pricing, merchandising, market research, or alerting workflows.
• Compare current and previous product states with source evidence and confidence.
• Schedule recurring checks for catalog drift, stock changes, and competitor price movement.

Trust and compliance

• Uses Temu Public Pages, Schema Org Product.
• Keeps source URLs and source identifiers in output records for auditability.
• Does not require private credentials unless a source is explicitly configured for approved authenticated access.

Reliability and QA

• Prefilled Apify Store QA input runs in sample mode and should finish within the automated quality window.
• Empty input is handled with deterministic sample or diagnostic output instead of a crash.
• Demo/sample runs suppress buyer-value charges while still writing representative dataset rows.
• Production runs use bounded maxItems, source references, warnings, and run summaries so blocked or changed targets are visible.

Limitations

• Results depend on public-source availability, source uptime, and source update cadence.
• Public sources can revise records after publication; rerun scheduled tasks for fresh evidence.
• Scores and match reasons are decision-support signals, not legal, financial, procurement, medical, safety, or regulatory advice.
• Large production runs can cost more than the default smoke run; start small, inspect output, then scale schedules.

Legal and responsible use

Use this Actor only for public data or data you are authorized to process. You are responsible for complying with applicable laws, marketplace terms, robots policies, privacy rules, and source-specific limits.

Support

Open an issue on the Actor page with the run ID, input summary, expected result, and observed result. Do not include secrets, cookies, auth headers, or private account data.

FAQ

Can I run this without URLs? Yes. The default sample mode is designed to succeed without user-supplied URLs, and URL-backed runs can use startUrls when needed.

Can I schedule it? Yes. Use sinceLastRun, watchlistTerms, and optional webhookUrl to turn the actor into a recurring alert or report workflow.

How do I verify value before scaling? Run the recommended first-run input, review the sample output fields, then increase maxItems or schedule recurring runs after the dataset matches your use case.