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Google Shopping Results Scraper

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from $1.39 / 1,000 item extracteds

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Google Shopping Results Scraper

Google Shopping Results Scraper

Export Google Shopping result cards with prices, merchants, ratings and visible shipping or sale signals. Search by keyword, country and language for product research.

Pricing

from $1.39 / 1,000 item extracteds

Rating

0.0

(0)

Developer

Fetch Cat

Fetch Cat

Maintained by Community

Actor stats

0

Bookmarked

15

Total users

6

Monthly active users

10 days ago

Last modified

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Export Google Shopping result cards by keyword, country and language, with prices, merchant snippets, ratings and visible shipping or sale signals. Use the dataset for product research and seller comparisons. This Actor does not visit merchant product pages or guarantee every offer.

Quick start

  1. Add one or more product searches to queries.
  2. Choose country and language, then start with a small maxItems cap.
  3. Run the Actor and download the dataset as JSON, CSV or Excel.
{
"queries": ["coffee maker"],
"country": "US",
"language": "en",
"maxItems": 5
}

Some result cards have no direct product link, image, rating or shipping information. Missing values stay null. A false shipping/returns flag means no matching signal was found, not that the merchant excludes that service.

Prefer a video guide? This short Apify walkthrough shows you how to set up and run an Actor. It uses a different Actor, but the setup steps are the same.

Ready-to-run examples

Choose a public example to see its settings before starting a run:

What you get

One row per saved Shopping result card, with its product title, generated identity, merchant and visible price information, plus any available links, ratings and delivery or sale signals. Query, page, saved order and observation time preserve the search context. Optional snippets are not a complete merchant-offer inventory or product-page export.

Who is it for?

  • Retail and procurement researchers reviewing advertised prices and visible merchant alternatives.
  • Ecommerce analysts assembling focused product-search samples with original source context.
  • Brand and marketplace teams inspecting visible listing and sponsored-card signals.
  • Data teams comparing their own exported snapshots without expecting an automatic price-alert database.

How you can use the data

  • Prepare a coffee-maker comparison sheet. Use the existing US English query with five total rows. Keep productTitle, merchant, priceText, priceValue and source links together, then inspect merchant offers separately because this Actor does not visit their product pages.
  • Compare a market-specific sample carefully. Use the existing UK air-fryer or German sneaker examples and retain the requested locale with original price text. Currency is inferred from the symbol, and a dollar symbol is labeled USD even in other dollar locales. No currency conversion is performed.
  • Review filtered choices without inventing policies. Apply a small price or merchant refinement and inspect the returned unknown values. Missing price or condition can survive filters, while a false free-shipping or free-returns flag means no matching visible signal was found rather than proof of a negative merchant policy.
  • Build your own observation history. Retain query, product identity, merchant, sourceUrl and scrapedAt, then compare your exports downstream. Generated IDs and listings can change. Sorting is page-local, saved positions are not exhaustive Google ranks, and row-level completion labels must be checked against the final summary.

Input settings

Only queries is required. Defaults apply to omitted API fields. The form's example query is not an API default. Use up to 100 distinct nonblank queries, each at most 200 characters.

SettingAPI keyBehavior
Shopping queriesqueriesProduct terms. At least one nonblank string.
Country codecountryTwo-letter code. Default US.
Language codelanguageInterface language. Default en.
Maximum resultsmaxItemsTotal saved-row cap, 1–1,000. Default 20.
Maximum results per querymaxItemsPerQueryDefaults to maxItems. Cannot exceed it.
Price boundsminPrice, maxPriceNonnegative bounds. Unknown-price cards can remain. No currency conversion.
Merchant or storemerchantSearch refinement and visible merchant-name substring filter.
Product conditionconditionany (default), new, used, refurbished. Unknown conditions can remain.
On-sale products onlyonSaleRequires a visible sale/deal/discount signal. Default false.
Free shipping onlyfreeShippingRequires a visible free delivery/shipping signal. Default false.
Free returns onlyfreeReturnsRequires a visible free-returns signal. Default false.
Sort ordersortrelevance (default), priceAsc, priceDesc, rating. Ordering is within each fetched page, not across the entire dataset.
Start pagestartPageFirst requested page, 1–100. Default 1.
Maximum pages per querymaxPagesPage cap, 1–10. Default 1.
Request timeoutrequestTimeoutSecsPer-request limit, 5–120 seconds. Default 45.
Proxy configurationproxyConfigurationProxy access is required. The existing managed default is provided. Custom proxy settings are accepted. See field help for behavior and limitations.

Narrow filters may return fewer records than requested. maxItems is a cap, not a promised count. Multiple queries share the total cap in rounds. Price/rating sorting does not turn saved position values into an exhaustive Google ranking.

Example inputs

Use the Quick start input as a small first run. Adjust the fields described above for your own data.

Output data

Each dataset row represents one saved result card. This shortened example illustrates the shape only. It is not an observed product or price:

{
"query": "coffee maker",
"position": 1,
"queryPosition": 1,
"page": 1,
"pagePosition": 1,
"productId": "gshop_example",
"productTitle": "Example coffee maker",
"priceText": "$50.00",
"priceValue": 50,
"currency": "USD",
"merchant": "Example store",
"productUrl": null,
"rating": null,
"freeShipping": false,
"freeReturns": false,
"sponsored": false,
"resultType": "organic",
"queryStatus": "complete",
"isPartial": false
}
FieldsMeaning
query, position, queryPositionSearch term and global/per-query saved order.
page, pagePositionRequested page and extracted card order before filtering/sorting.
productId, productTitleGenerated identity based on a product URL or title/merchant. Visible title. Not a guaranteed Google catalog ID.
priceText, priceValue, currencyVisible price text and parsed numeric value. Currency is inferred from the symbol. $ is reported as USD even in other dollar locales.
originalPriceValue, savingsValue, savingsPercentOptional original price and detected savings.
merchant, condition, availability, offerCountOptional card snippets, not a complete seller-offer inventory.
productUrl, imageUrlAvailable links or null. No merchant-page enrichment.
rating, reviewCountOptional star rating and review count, not review text.
shipping, freeShipping, freeReturns, onSaleVisible snippets and detected signals. False is not proof of a negative policy.
sponsored, resultTypeDetected ad label. sponsored or organic, without guaranteed ad coverage.
queryRelevanceQuery-token overlap with the title, from 0 to 1. Not Google's relevance score.
queryStatus, isPartialRow-level complete/partial at save time. See the final summary for later query outcomes.
sourceUrl, scrapedAtSource search URL and observation timestamp.

RUN_SUMMARY and OUTPUT in the key-value store contain final run status, saved counts, warnings and per-query diagnostics. Query outcomes can include complete, partial, timeout, blocked, http_error or empty. Diagnostic records are separate from product rows. Useful rows from other queries can remain when a query fails. A run with no saved rows currently fails with an explanation in the summary.

Download your results

Open your run's dataset, choose Export and select JSON, CSV or Excel. JSON keeps nested fields together. CSV and Excel are useful when you want to review the records in a spreadsheet.

See Apify's download and export guide for the available formats and field options.

Pricing

The start event is charged once after input validation and setup. The item event applies to each saved result row, while failed requests and diagnostic records are not items. A run with no saved products can still incur the start charge.

Keep the total cap, per-query cap and page limit small while evaluating a search. Check the live Pricing tab for current rates and discounts.

Tips for best results

  • Use a focused product query with small total and per-query caps. Several queries share the total cap in rounds rather than receiving separate full totals.
  • Keep original price text and locale together. A parsed number and symbol-based currency label are insufficient for critical market comparisons.
  • Inspect the evidence for sale and delivery signals. Missing snippets do not establish a merchant's policy.
  • Compare page-local order rather than assuming a global cheapest-first list. Saved positions and title-overlap scores are not Google's exhaustive ranking or relevance measure.
  • Read final query outcomes after partial work. Row labels reflect their save time, while the final summary can report later failures.

Limits and caveats

Google can change layouts, restrict access or return fewer cards than requested. Locale does not guarantee a particular currency, complete results or the same order as your browser. A run with no saved rows currently fails with an explanation in the summary. Useful rows can remain after another query fails, and diagnostic records are separate from product rows.

Optional links, ratings, images, shipping information and merchant snippets can be absent. Unknown prices and conditions can remain after filtering. Sale, shipping, returns and sponsored labels depend on visible signals rather than complete merchant or advertising coverage. There is no merchant-page enrichment, checkout access, full review text, login or private-account data.

Product IDs are generated from links or title and merchant rather than guaranteed Google catalog identifiers. Currency comes from symbols without conversion, including a USD label for dollar symbols in other locales. Sorting is within fetched pages rather than across the whole dataset. Query relevance is title-token overlap rather than Google's score.

RUN_SUMMARY and OUTPUT hold final counts, warnings and query diagnostics. Review them alongside the dataset before interpreting empty or partial output as a complete product market. Repeated-snapshot comparisons, alerts and integrations are separate steps in your own workflow.

Automation and integrations

Save your settings for next time

Once you have an input that works for you, save it as an Apify task. This keeps your settings together so you can use them again without filling in the form from scratch.

Run on a schedule

Need fresh results regularly? You can schedule the Actor or a saved task to run at a time that suits you.

Each scheduled run collects the data again. If you want to compare results or highlight changes, add that step in your own workflow.

Send results to your other tools

Use n8n, Make or Zapier to connect this scraper to the rest of your workflow. For example, you could pass its results to an AI assistant or add records to a spreadsheet. Follow the Apify integration guides for your chosen tool.

For a custom connection, an Apify webhook can notify your app when a run finishes or fails. Your app can then fetch the results or handle the failure.

API usage

Want to collect this data from your own app or automation? The examples below send input to the scraper and show how to collect its results.

The Node.js and Python examples wait for the run to finish before reading its results. The cURL example starts the run and returns its details. Wait for that run to finish, then use its defaultDatasetId to fetch the results.

For setup instructions, see Apify's JavaScript client guide, Python client guide and Actor runs API reference.

cURL

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~google-shopping-results-scraper/runs' \
-H "Authorization: Bearer $APIFY_TOKEN" \
-H 'Content-Type: application/json' \
--data @- <<'JSON'
{
"queries": [
"coffee maker"
],
"country": "US",
"language": "en",
"maxItems": 5
}
JSON

Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/google-shopping-results-scraper').call({
"queries": [
"coffee maker"
],
"country": "US",
"language": "en",
"maxItems": 5
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

import os
from apify_client import ApifyClient
client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/google-shopping-results-scraper').call(run_input={'queries': ['coffee maker'], 'country': 'US', 'language': 'en', 'maxItems': 5})
print(client.dataset(run['defaultDatasetId']).list_items().items)

API and AI-agent use notes

The asynchronous HTTP call returns a run. Wait for its terminal status, then fetch items from its defaultDatasetId using the Apify API.

MCP and AI agents

You can ask your AI assistant to collect data with Google Shopping Results Scraper and help you work with the results. The scraper returns the data, and your assistant can then summarize it, compare records or prepare notes.

Connect your assistant through the Apify MCP server. MCP gives your assistant a way to find this scraper, run it and read the results. Follow the official setup and sign-in guide for your app.

Easier setup with an Apify plugin

If you use a supported coding assistant, the official Apify plugin can set up the connection for you. It connects your assistant to Apify and includes instructions for common tasks. Follow the guide for your particular app.

Use Apify AI in Console

Prefer to keep everything in Apify? Open Apify AI in Console and ask it to find Fetch Cat's Google Shopping Results Scraper. You can describe the data you want and ask questions about the results.

Apify AI is currently in beta. It asks for confirmation before starting an Actor, and normal run charges apply.

Choose your assistant

Connect just this scraper

To keep your setup focused on this scraper, add this server configuration to a compatible MCP client:

{
"mcpServers": {
"apify": {
"url": "https://mcp.apify.com?tools=fetch_cat/google-shopping-results-scraper"
}
}
}

Sign in to Apify when your client asks. If your client uses a Bearer token instead, follow its setup guide and keep the token in its secure configuration. Configuration formats vary by app, so use the linked guide if your client needs a different format.

Use Apify's general server

Already connected to the general Apify MCP server at https://mcp.apify.com? You can use it to find this scraper without adding another server. Ask your assistant to use Google Shopping Results Scraper by Fetch Cat, or give it the identifier fetch_cat/google-shopping-results-scraper.

Your assistant can check the available settings and retrieve the results from the returned run. If the run is still working, it should follow that run rather than start it again. Both connection options use Apify's hosted service.

Example requests

  • “Use Fetch Cat’s Google Shopping Results Scraper to collect up to 5 coffee-maker cards in the US, in English, from one page. Show merchant names, original price text and available source links, leaving missing fields unknown.”
  • “Collect up to 5 air-fryer result cards in Great Britain, in English, from one page. Keep original price text and requested locale and flag symbol-based currency uncertainty rather than converting prices.”
  • “Retrieve up to 5 sneaker cards in Germany, in German, with the visible free-shipping filter enabled and one page maximum. Show the supporting shipping text and merchant context without claiming complete offers or a guaranteed delivery policy.”

Normal Apify charges apply. Check the live Pricing tab before asking your assistant to run a larger batch.

Pay with x402

If your AI agent has a funded wallet, it can pay for Apify usage through x402. This experimental option lets an agent use Apify without a conventional account.

Apify AGI provides a prepaid API token with a spending cap after payment. Your agent can use that token to run this scraper through the Apify API or an authenticated MCP connection.

Some MCP setups also support paying for each request directly. That is a different payment option, so check the official guide for its availability.

Follow the official guide for wallet setup, supported payment options and current terms. Apify handles the payments. Keep wallet keys and payment tokens in your agent's secure configuration.

Other ways for agents to pay

Apify also supports MPP for prepaid access through AGI and Skyfire for eligible Actors. If your agent already uses one of these, see the agentic payment guide to choose the right setup.

FAQ

Is this a Google Shopping API alternative?

It provides structured snapshots of public Shopping result cards through Apify. It is not Google's official API and does not manage Merchant Center feeds or guarantee a complete offer list.

Why are Google Shopping results in the wrong country or currency?

Set country and language together. Google's regional availability and snippets can vary. The currency field is symbol-based and does not distinguish different dollar currencies. Use the original priceText and locale when interpreting values.

Why are there no Shopping results or fewer rows than requested?

The query may have few matching cards, filters may exclude cards, or Google may block access or change its layout. Inspect RUN_SUMMARY to distinguish empty extraction from request errors. Use a specific query and small limits when reporting a problem. An empty dataset does not establish that no products exist.

Can I export ratings and reviews?

You can export visible ratings and review counts, not review text. Dataset exports include JSON, CSV and Excel.

Are filters and sorting exact?

Merchant and sale/shipping/returns filters depend on visible signals. Missing prices and conditions can survive those filters, and sorting is page-local rather than a global cheapest-first or highest-rated guarantee.

Support and feedback

For custom additions or integrations, email hello@fetchcat.dev.

Found an error or have a feature request? Open an issue with the run URL, a non-sensitive input example and what you expected.

Need help sharing it? See Apify’s guide to sharing a run when reporting an issue. Sharing a run can give the developer access to its input, logs and results, so use a run that contains no sensitive data. Please leave out API tokens, passwords, cookies, private documents and personal data. Use a public sample URL or a redacted example instead.

Tried this scraper? We'd love to hear how it worked for you. Leave a review to help others choose the right tool and help us improve it. Your feedback means a lot to us.

Made with care for curious people, AI agents and the possibilities in data. ♥