Shopify Commercial Change Intelligence

Monitor public Shopify stores and turn catalog changes into prioritized commercial intelligence — not thousands of raw product rows.

Designed for competitor monitoring, ecommerce pricing analysis, assortment tracking, sourcing, retail intelligence, and market research.

What you get

The Actor groups related product changes into decision-ready events:

• Broad price drops or increases across multiple products
• Promotions starting or ending
• Multi-product restocks and stockouts
• Catalog expansion or contraction
• New product categories

Every event includes:

• impactScore from 1 to 100
• Urgency and confidence
• Number and percentage of affected products
• Evidence with product links
• A concise summary
• A recommended commercial response

Why use this Actor

Most Shopify scrapers return product rows. This Actor keeps a persistent baseline for each store and monitor, compares later scans, and consolidates related changes into a small number of meaningful signals.

Instead of reviewing hundreds of records, you can receive an event such as:

Prices dropped across 34 products, averaging 18%. Impact score: 82. Urgency: critical.

Quick start

1. Add one or more public Shopify storefront URLs.
2. Keep a stable monitorId for each monitoring project.
3. Run the Actor once to create the baseline.
4. Run it again later with the same monitorId to detect changes.
5. Schedule recurring runs or connect the dataset to your workflow.

The first run normally returns baseline_created. Later runs return a scan summary and any qualified commercial events.

Input

• storeUrls: public Shopify storefront domains
• monitorId: stable baseline namespace
• minPriceChangePercent: ignores smaller price movements
• minAffectedProducts: prevents isolated changes from becoming broad signals
• maxProductsPerStore: hard product and cost limit
• maxStoresPerRun: hard store and cost limit
• outputMode: events with summary, events only, or summary only

Example output

{
  "eventType": "broad_price_drop",
  "title": "Prices dropped across 34 products",
  "affectedProducts": 34,
  "totalProducts": 180,
  "magnitudePercent": -18,
  "impactScore": 82,
  "urgency": "critical",
  "confidence": 0.98,
  "recommendedAction": "Compare affected SKUs and decide whether to match, hold, or reinforce value positioning.",
  "evidence": [
    {
      "title": "Example product",
      "url": "https://example-store.com/products/example-product",
      "averagePriceChangePercent": -18
    }
  ]
}

Automation and integrations

The structured dataset can be consumed through the Apify API or connected to scheduling and automation workflows. A common setup is to run the same monitor daily or weekly and continue the workflow only when status is changed.

No store login, private Shopify Admin API token, paid external API, browser, or proxy is required by default.

Cost controls

The Actor uses direct HTTP and enforces limits for stores and products per run. Its default configuration is intentionally conservative. Users can also set Apify's maximum cost per run.

Limitations

• The storefront must expose a public Shopify product catalog.
• A store may block or customize its public catalog endpoint.
• The Actor reports catalog-level signals; it does not access orders, customers, private inventory systems, or Shopify Admin data.
• A stable monitorId is required for meaningful comparisons.
• Changing product limits between runs can intentionally create expansion or contraction signals.

Responsible use

Use only with public storefronts and in accordance with applicable law, site terms, and robots policies. The Actor does not log in, bypass access controls, or collect customer data.