E-commerce Price & Stock Monitor

Compare Schema Org Product, Google Product Structured Data, Apify datasets/storage and return product change rows with price, stock, availability, seller, and source evidence.

Who this is for

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

Buyer outcomes

• Detect e-commerce price & stock 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

• Schema Org Product
• Google Product Structured Data
• Apify datasets/storage

Inputs

• 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.

Outputs

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-change, product-processed, alert-sent, dataset-processed, record-saved, enriched-record. Small validation runs are supported so you can inspect output before scaling a schedule.

• product-change: Charge after producing one product change. Typical price: $0.010. A run that produces 10 matching records charges only for the matched buyer-value events and remains capped by the run limit.
• product-processed: Charge after producing one product row checked. Typical price: $0.001. A run that produces 10 matching records charges only for the matched buyer-value events and remains capped by the run limit.
• alert-sent: Charge after producing one webhook alert. Typical price: $0.015. 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 E-commerce Price & Stock Monitor 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/zentrafoundry~ecommerce-price-stock-change-monitor/runs" \
+  -H "Authorization: Bearer $APIFY_TOKEN" \
+  -H "Content-Type: application/json" \
+  -d '{"maxItems":10,"sourceIds":["SCHEMA-ORG-PRODUCT","GOOGLE-PRODUCT-STRUCTURED-DATA","APIFY-DATASETS"],"includeSourceUrls":true,"includeMatchReasons":true,"outputMode":"buyer-ready-records"}'

Recommended first run

{
    "maxItems": 10,
    "sourceIds": [
        "SCHEMA-ORG-PRODUCT",
        "GOOGLE-PRODUCT-STRUCTURED-DATA",
        "APIFY-DATASETS"
    ],
    "includeSourceUrls": true,
    "includeMatchReasons": true,
    "outputMode": "buyer-ready-records"
}

Sample output

Sample status: sample_unavailable at https://zentra.nimblique.studio/external/actor-review/samples/ecommerce-price-stock-change-monitor.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": [
                "SCHEMA-ORG-PRODUCT",
                "GOOGLE-PRODUCT-STRUCTURED-DATA",
                "APIFY-DATASETS"
            ],
            "includeSourceUrls": true,
            "includeMatchReasons": true,
            "outputMode": "buyer-ready-records",
            "actorSlug": "ecommerce-price-stock-change-monitor"
        }
    },
    {
        "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": [
                "SCHEMA-ORG-PRODUCT",
                "GOOGLE-PRODUCT-STRUCTURED-DATA",
                "APIFY-DATASETS"
            ],
            "includeSourceUrls": true,
            "includeMatchReasons": true,
            "outputMode": "buyer-ready-records",
            "actorSlug": "ecommerce-price-stock-change-monitor"
        }
    }
]

Use cases

• Track e-commerce price & stock 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 Schema Org Product, Google Product Structured Data, Apify datasets/storage.
• 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.

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.

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.