Amazon Product Scraper for Price Monitoring

What this pipeline does

Amazon price tracking works best when the first version is boring. Pick the ASINs you care about, collect the same fields on every run, and only alert when the new value is meaningfully different from the last good record.

The Amazon Product Scraper returns product details such as title, ASIN, price, availability, rating, review count, seller signals, and ranking fields. That is enough to build a useful competitor monitor without starting with a heavy data warehouse project.

Best first run

Start with three to five product URLs or ASINs from one marketplace.

{
  "productUrls": [
    "https://www.amazon.com/dp/B0EXAMPLE1"
  ],
  "maxItems": 5,
  "includeReviews": false,
  "enableAiAnalysis": false
}

The first run should answer one question: can you reliably get asin, title, price, availability, rating, and review_count for the products that matter?

Monitor table shape

{
  "asin": "B0EXAMPLE1",
  "title": "Example Product",
  "price": 49.99,
  "availability": "in_stock",
  "rating": 4.6,
  "review_count": 128,
  "captured_at": "2026-05-30T08:00:00Z"
}

Store one row per product per run. Then keep a small current-state table keyed by ASIN. The current-state table powers dashboards; the history table lets you explain what changed.

Alerting rules

Do not alert on every small movement. Use thresholds:

• Price changed by more than 5 percent
• Availability moved from in stock to unavailable
• Rating changed by at least 0.2
• Review count jumped faster than the category usually moves

Those rules keep the feed useful for category managers, sellers, and analysts who need signals, not noise.

Deployment notes

Run high-value products daily and long-tail products weekly. Keep the raw Apify dataset URL for each run so a teammate can inspect the original scrape when a price looks wrong. If you later need a managed feed, keep the same ASIN keys and history table so the upgrade does not break reports.