We extract cross-retailer product listings, Shopping ad placements, organic Shopping ranks, merchant pricing, and promotion data from Google Shopping. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Shopping Results objects from shopping.google.com. All fields typed and schema-versioned.
"query": "sony wh-1000xm5", "position": 1, "product_title": "Sony WH-1000XM5 Wireless Noise Canceling Headphones", "merchant_name": "Best Buy", "price": 279.99, "currency": "USD", "shipping_cost": 0.00, "listing_type": "SPONSORED", "price_drop_badge": true, "product_rating": 4.6
| # | query | country | locale | position | product_title | product_id |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Product Panels objects from shopping.google.com. All fields typed and schema-versioned.
"product_id": "9837261940482817483", "product_title": "Sony WH-1000XM5 Wireless Headphones", "google_product_rating": 4.6, "google_review_count": 41820, "price_low": 249.99, "price_high": 349.99, "merchant_count": 34, "price_insight_label": "Typical price: $299.99"
| # | product_id | product_title | brand | category | google_product_rating | google_review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Merchant Comparisons objects from shopping.google.com. All fields typed and schema-versioned.
"product_id": "9837261940482817483", "merchant_name": "Amazon", "price": 269.99, "shipping_cost": 0.00, "total_price": 269.99, "promotion_text": "15% off with code SAVE15", "google_merchant_rating": 4.7, "in_stock": true
| # | product_id | query | merchant_name | merchant_url | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ad Placements objects from shopping.google.com. All fields typed and schema-versioned.
"query": "sony wh-1000xm5", "ad_position_type": "TOP_CAROUSEL", "position": 2, "merchant_name": "Walmart", "price": 258.00, "promotion_text": "Free 2-day shipping", "badge": "PRICE_DROP", "device_type": "desktop", "scraped_at": "2026-05-12T10:30:00Z"
| # | query | country | position | ad_position_type | merchant_name | product_title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Google Shopping is the broadest cross-retailer pricing dataset available. Our scraper captures Shopping ad placements, organic listings, product panel ratings, per-merchant pricing, and promotion text — across any keyword, country, and locale.
For any query, capture every merchant's price, shipping cost, total cost, and promotion text — the full competitive pricing picture that Google surfaces to consumers.
Identify which merchants are running Shopping ads, their carousel positions, badge types, and promotion copy — the paid search data most retailers have no visibility into.
Track organic (free listing) rank vs paid placement for any product or keyword — and monitor position changes over time as Google's algorithm shifts.
Extract Google's aggregated product rating, review count, price range, typical price label, and merchant count from the product knowledge panel.
Capture merchant promotion text, coupon codes, and special offer labels surfaced within Google Shopping listings — a signal most price comparison tools miss.
Scrape Google Shopping results for any country, locale, and zip code combination — capturing local inventory ads, local pricing, and geo-specific merchant sets.
Detect price drop badges, 'typical price' labels, and sale event badging as Google surfaces them — valuable for consumer sentiment and retail demand signals.
Run structured keyword programmes across product names, model numbers, categories, and brand terms — with full SERP pagination for high-volume Shopping results.
One-off keyword sweeps or continuous monitoring pipelines at hourly, daily, or real-time cadences with change-detection diffing.
Brief in. Clean data out.
Provide keyword sets, product model numbers, brand terms, or category URLs. Specify target countries and locales.
We configure Scrapy / Playwright crawlers with geo-targeted proxies, locale headers, and CAPTCHA handling for Google Shopping.
Merchant coverage audits, price-outlier checks, ad vs organic classification validation, and sample records before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Google's bot detection is among the most sophisticated in the industry. Geo-personalised results and dynamic SERP layouts require infrastructure built specifically for Shopping data.
Google's bot detection is among the hardest in web scraping — including CAPTCHA challenges, TLS fingerprinting, and behavioural analysis. Our pipeline uses residential ISP proxies with realistic browser sessions, randomised timing, and CAPTCHA solver integration tuned specifically for Google properties.
Google Shopping results vary substantially by country, language, and even zip code — different merchants, prices, and ad sets. We configure proxy sessions with precise geo-targeting so your dataset reflects what real shoppers in any target market actually see.
Google Shopping mixes sponsored (PLA) and free organic listings in the same carousel and grid. Our parser reliably classifies listing type, ad position type (top carousel vs sidebar), and organic rank — a distinction that most scrapers collapse incorrectly.
Google A/B-tests Shopping SERP layouts constantly. Our selector strategy uses multiple fallback chains per field, trained across layout variants — so an interface experiment doesn't break your merchant pricing feed.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, merchant coverage drops, ad classification drift, and schema changes — and respond before you notice. SLA uptime is contractual, not aspirational.
Brands and retailers monitor how their products are priced across every merchant appearing in Google Shopping — surfacing the competitive pricing picture that real consumers see at the top of their search.
Performance marketing teams track which competitors are running Shopping ads for their target keywords, their ad positions, promotion copy, and pricing — informing bid strategy and creative decisions.
Brands monitor Google Shopping for merchants selling below MAP, surfacing unauthorised resellers and grey-market channels before they erode brand pricing integrity.
Price comparison sites and consumer apps use Google Shopping data as a fast, broad-coverage alternative to individual retailer scraping — one source covering hundreds of merchants.
Agency teams audit client Shopping feed visibility, organic free listing coverage, and promotion copy effectiveness across keyword programmes — identifying gaps and opportunities.
Analysts use Google Shopping cross-retailer pricing data to build category price distributions, map merchant concentration, and track promotional intensity over time.
"Google Shopping is the single largest cross-retailer pricing dataset in existence — and the first place consumers look when comparing prices. If you don't know what it shows for your products, your competitors do."
Scraping Google reliably is categorically harder than scraping any retailer. Their bot detection, CAPTCHA systems, and geo-personalised results require specialised infrastructure, constant proxy maintenance, and daily selector validation. DataFlirt absorbs that complexity so your team can focus on pricing decisions — not fighting Google's defences.
Everything supported by our shopping.google.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles Google's JavaScript-rendered Shopping carousels, product panels, and merchant comparison pages.
We maintain pools of residential ISP proxies across US, UK, IN, DE, AU, CA, and FR. Proxies are geo-targeted to the country and locale of each query — ensuring results match what real consumers see.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About shopping.google.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available search results and Shopping listings from Google is a contested legal area. The hiQ v. LinkedIn ruling and similar cases broadly support the legality of scraping public web data. DataFlirt targets only public, non-authenticated Shopping result data — not personal data, logged-in results, or paid product feeds. We recommend clients review Google's ToS independently and consult legal counsel for their specific use case.
Google's bot detection is among the most sophisticated in web scraping. We use residential ISP proxies with realistic browser fingerprints, randomised request timing, and 2Captcha/CapSolver integration. Our pipeline is tuned specifically for Google properties — including session warm-up patterns and query rate management to avoid triggering challenges.
Yes. We support Google Shopping results for US, UK, IN, DE, FR, AU, CA, and 20+ other markets. Each query is issued from a residential proxy in the target country with the correct locale and language parameters — capturing local merchant sets, local pricing, and local inventory ads.
Google Shopping mixes PLAs (paid) and free organic listings in the same carousel. Our parser classifies each result by listing type — sponsored, free listing, or organic grid position — based on structural signals in the rendered page. This classification is validated per run.
Yes. We run structured keyword programmes and record the merchant name, ad position type, carousel slot, price, and promotion copy for every placement. This gives you a competitor Shopping ad presence map across any keyword set.
Our smallest packages start at a defined keyword list (typically 500–5,000 queries) with daily delivery across a target country. For multi-country programmes or sub-hourly monitoring cadences, we price based on query volume and frequency.
Yes. Google's product knowledge panels surface aggregated ratings, review counts, price ranges, and merchant counts — often distinct from any individual retailer's data. We capture these panel-level signals separately from individual merchant listing data.
Absolutely. We run a sample keyword programme of up to 100 queries across your target country as part of the pre-engagement scoping process — so you can validate merchant coverage, ad classification accuracy, and schema fit before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need cross-retailer pricing across 10,000 keywords or a real-time competitor Shopping ad monitor — we scope, build, and operate the pipeline. Tell us what you need.
