Google Shopping & Product Trends Scraper ($0.30/1k)
Fast & Cheap ($0.30/1k): Monitor & scrape Google Shopping product trends, +5,000% breakout searches & buyer regions. Screen up to 100 products in 1-click Excel/CSV or JSON.
{
"scrape_type": "interest_over_time",
"keyword": "Air Fryer",
"gprop": "froogle",
"geo": "US",
"timeframe": "today 12-m",
"date": "2026-10-01",
"value": 88,
"is_partial": false,
"scraped_at": "2026-10-20T12:00:00Z"
}
Features
What the Google Shopping & Product Trends Scraper ($0.30/1k) Extracts
Top Buying Regions, DMA Metros & Cities
Allocate Google Shopping, Meta, and TikTok ad spend to the exact states or cities with 100 buyer demand.
Breakout & Top Product Queries
Uncover specific product models, sizes, and brands surging +5,000% (rising) alongside evergreen bestsellers (top).
Seasonal Buyer Timeline
Pinpoint the exact week Q4 holiday, summer, or back-to-school demand begins climbing.
Related Brands & Categories
Discover competing D2C brands and adjacent product lines.
Integration
Run It From Python or n8n
from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run_input = {
"keywords": ["Air Fryer", "Espresso Machine"],
"common_geo": "US",
"scrape_type": "all",
"compare_keywords": True,
"category": 0,
"predefined_timeframe": "today 12-m"
}
run = client.actor("unitbytes/google-shopping-trends-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item.get("keyword"), item.get("value"), item.get("date"))n8n Workflow Template
Schedule this scraper and send results to Google Sheets, Airtable, or Slack.
FAQ
Frequently Asked Questions
Q: How does Google Shopping Trends help e-commerce and Amazon FBA sellers?
By querying Google's dedicated Shopping search property (froogle), you isolate high-intent commercial product searches from general informational queries to spot breakout SKUs before inventory stocks out.
Q: Does it extract Breakout (+5,000%) product queries and brand models?
Yes. Every run captures both Top commercial queries and Breakout rising product variations alongside historical demand curves and regional DMA/state buyer heatmaps.
Q: Can I analyze seasonal product demand across multiple countries?
Yes. Pass any list of product keywords, select your target country or metro code, and compare 90-day, 12-month, or 5-year shopping demand curves.
Q: What is the pricing per 1,000 product trend records?
Pricing is $0.45 per 1,000 records ($0.00045/item) with volume discounts down to $0.30/1K and zero proxy or login requirements.
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Prefer Not to Run It Yourself?
Tell us what you need from Google Shopping & Product Trends Scraper ($0.30/1k) and we'll deliver a clean Excel/CSV file. One-time datasets from $99, custom scrapers from $299. We reply within 48 hours.