🛍️ Google Shopping Trends Scraper — Breakout Product Demand

Spot winning products 4–8 weeks before inventory stockouts. Query Google's dedicated Google Shopping Search Index directly to extract Breakout shopping searches (+5,000%), seasonal buyer timelines, high-converting states/DMA metros, and related brands—up to 100 product keywords in a single run.

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⚡ UnitBytes · Search Trends & Market Demand Intelligence Suite
🛍️ Google Shopping Trends 📍 You are here Breakout physical products, seasonal buyer demand & regions		🔥 Google Trending Now Realtime Viral Spikes 4h/24h/48h/7d trending searches, volumes & breaking news		🎥 YouTube Trends Scraper Video Creators & SEO Breakout YouTube search queries, video topics & viewer regions
📈 Google Trends All-in-One Scraper Marketers & Spreadsheets 20-year timelines, DMA heatmaps, bulk 100 keywords & Excel/CSV			⚡ Google Trends Fast API Developers & AI Agents (MCP) Sub-second REST API & unnested flat JSON for LLM pipelines

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✨ Why Use Google Shopping Trends Scraper?

1. 🛍️ 100% Pure Buyer-Intent Search Signals

Standard Web search mixes informational curiosity with shopping. By querying Google Shopping (gprop: "froogle") directly, every single data point reflects real shoppers searching for physical products, brands, models, and price comparisons.

2. ⭐ All 4 E-Commerce Datasets in One Run (scrape_type: "all")

• 🚀 Breakout & Top Product Queries (related_queries): Uncover specific product models, sizes, and brands surging +5,000% (rising) alongside evergreen bestsellers (top).
• 📈 Seasonal Buyer Timeline (interest_over_time): Pinpoint the exact week Q4 holiday, summer, or back-to-school demand begins climbing.
• 🌍 Top Buying Regions, DMA Metros & Cities (interest_by_region): Allocate Google Shopping, Meta, and TikTok ad spend to the exact states or cities with 100 buyer demand.
• 🏷️ Related Brands & Categories (related_topics): Discover competing D2C brands and adjacent product lines.

3. 📦 Compare 5 Competitors OR Bulk-Screen 100 Products

• Head-to-Head Product Comparison (compare_keywords: true - Default): Compare up to 5 products or brands on a shared 0–100 scale.
• Bulk Catalog Screening (compare_keywords: false): Screen up to 100 SKU or product keywords in a single run.

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🧪 Ready-to-Run Input Examples

1. ⭐ Complete Product Demand Intelligence (Timeline + Regions + Breakout Queries + Brands)

{
  "scrape_type": "all",
  "keywords": ["Air Fryer", "Espresso Machine"],
  "predefined_timeframe": "today 12-m",
  "common_geo": "US"
}

2. 🚀 Winning Product & Breakout Model Discovery (category: 18 = Shopping)

{
  "scrape_type": "related_queries",
  "keywords": ["Walking Pad", "Red Light Therapy", "Ice Bath"],
  "category": 18,
  "predefined_timeframe": "today 3-m",
  "common_geo": "US"
}

3. 📦 Bulk 100-SKU Catalog Demand Screening (compare_keywords: false)

{
  "scrape_type": "interest_over_time",
  "keywords": [
    "portable blender",
    "massage gun",
    "sunrise alarm clock",
    "standing desk",
    "ergonomic chair",
    "wireless carplay adapter"
  ],
  "compare_keywords": false,
  "predefined_timeframe": "today 12-m",
  "common_geo": "US"
}

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⚙️ Input Parameters Reference

Parameter	Type	Default	Description
keywords	array[string]	["Air Fryer", "Espresso Machine"]	Products or brands to analyze (up to 5 in comparative mode, or up to 100 when compare_keywords: false)
scrape_type	string	"all"	"all" (all 4 datasets), "related_queries", "interest_over_time", "interest_by_region", or "related_topics"
compare_keywords	boolean	true	true compares up to 5 products on a shared 0–100 scale. false runs up to 100 products independently
category	integer	0	Retail category filter (0 = All, 18 = Shopping, 5 = Electronics, 11 = Home & Garden, 44 = Beauty, 68 = Apparel, 71 = Food)
predefined_timeframe	string	"today 12-m"	now 1-d, now 7-d, today 1-m, today 3-m, today 12-m, today 5-y, all
custom_timeframe	string	""	Custom date range 'YYYY-MM-DD YYYY-MM-DD'
common_geo	string	"US"	2-letter ISO country code (US, GB, DE, CA, AU, etc.), country name, or WORLDWIDE
custom_geo_code	string	""	Sub-region code (US-CA, US-TX, etc.)
geo_resolution	string	"COUNTRY"	Regional granularity: COUNTRY, REGION, DMA, or CITY
output_format	string	"flat"	"flat" (1 row per data point for Excel/CSV/APIs) or "legacy" (nested JSON envelope)
max_events	integer	10000	Maximum number of results to extract

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💎 Pay-Per-Event Pricing (Zero Start Penalty)

Apify Plan Tier	Unit Price per Data Point	Cost per 25-Item Query	Run Start Fee
Free	$0.00045	~$0.011 (1.1¢)	$0.00 ($0.00005)
Starter	$0.00040	~$0.010 (1.0¢)	$0.00 ($0.00005)
Scale	$0.00035	~$0.008 (0.8¢)	$0.00 ($0.00005)
Enterprise	$0.00030	~$0.007 (0.7¢)	$0.00 ($0.00005)

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📞 Support & Feedback

• 🐛 Bug Reports & Feature Requests: Open a ticket on the Apify Issues Tab
• 💬 Creator Profile: unitbytes on Apify

⚖️ Compliance & Privacy

This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Google LLC or Alphabet Inc. It retrieves only publicly available, aggregate search statistics published by Google Trends and does not collect or process any personal data. Read Apify's guide on the legality of web scraping.