ProductReview.com.au Scraper

Extract ProductReview.com.au listing names, ratings, review counts and available review text into an exportable dataset. Start from a category, a search term or a direct listing URL to research Australian products and businesses without copying rows by hand.

Category and search pages provide listing summaries. To request review text, supply listing URLs. Only reviews available on those pages are included, not every historical review.

Quick start

1. Open the Actor and paste a ProductReview.com.au listing URL, or enter a search term.
2. Set Maximum rows to a small sample and run the Actor.
3. Open the dataset and export JSON, CSV or Excel. Check recordType to distinguish listings from reviews.

{
  "startUrls": [{ "url": "https://www.productreview.com.au/listings/apple-iphone-14" }],
  "maxItems": 20,
  "includeReviews": true,
  "maxReviewsPerListing": 10
}

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

• Browse mobile-phone listing summaries — Start with the mobile-phones category and a 20-row limit.
• Export available iPhone 14 reviews — Request a listing and up to ten available review rows, within a 20-row total limit.
• Search for NBN provider listings — Search for “nbn provider” with a 20-row limit.

What you get

• Listing names, aggregate ratings and review counts from available category, search and listing pages.
• Available review samples from direct listing URLs, with separate listing and review rows.
• Product metadata when present, plus per-page outcome reasons in the run summary.

Who is it for?

• Product researchers: compare listing ratings and review counts across Australian products.
• Brands and agencies: collect available review samples for qualitative analysis.
• Data teams: join listing URLs and review rows with other reputation datasets.

This Actor returns source data. It does not calculate sentiment scores or provide a built-in monitoring service.

Input settings

Setting	API key	Purpose
Start URLs	startUrls	HTTPS ProductReview.com.au category, search or listing URLs.
Search query	query	A search term, added to any supplied URLs.
Maximum rows	maxItems	Combined listing and review row limit, from 1 to 10,000.
Include reviews	includeReviews	Include available review rows on direct listing pages. Normally enabled.
Maximum reviews per listing	maxReviewsPerListing	Per-page review sample limit, from 0 to 200. Normally 10.
Proxy configuration	proxyConfiguration	Existing proxy settings. See the field help for available options.

Provide at least one URL or a nonempty query. Neither alternative is globally required. When both are supplied, both are processed. Clear unwanted prefilled examples before running. Console's row default is 20. Raw inputs that omit maxItems use the existing runtime limit of 25.

For a category-only dataset, use a category URL and set includeReviews to false. For a keyword search, an input such as {"query":"iphone","maxItems":20} is sufficient.

Output data

The default dataset contains flat listing and review rows. Optional values may be absent, depending on the page. The following is an illustrative shape only, not a current scraped result:

{
  "recordType": "listing",
  "sourceUrl": "https://www.productreview.com.au/listings/example-product",
  "listingUrl": "https://www.productreview.com.au/listings/example-product",
  "listingName": "Example product",
  "rating": 4,
  "reviewCount": 2,
  "scrapedAt": "2026-10-25T00:00:00.000Z"
}

Fields	Meaning
recordType	listing or review.
sourceUrl, listingUrl, listingName	Origin page and listing identity.
brand, category, rating, reviewCount	Available listing metadata. rating is the listing aggregate, not an individual review rating.
productUrl, imageUrl, mpn	Additional product metadata when available on a listing page.
reviewId, reviewerName, reviewDate	Available review identifier, public author name and date.
reviewRating, reviewTitle, reviewText	Available individual review content.
position	Local encounter order within the source page, not a global ranking.
scrapedAt	Run extraction timestamp.

reviewerLocation, verified and fairIncentive are reserved schema fields and are not currently populated. Review rows repeat available listing metadata so they can be filtered independently.

The key-value store's RUN_SUMMARY records counts and per-page outcome reasons. Expected unavailable targets or completed pages without usable records can succeed with an empty dataset. No synthetic listing is substituted. Access failure alone does not establish that a page is private or deleted. PENDING_URLS, when present, lists pages left at the run's time limit.

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

Pricing is pay per event. The start event is charged once after valid setup.

The item event is charged for each saved listing or review row. An empty run can incur the start event but has no saved-row events.

See the live Pricing tab for current rates and discounts.

Tips for best results

• Start with a small sample. Keep maxItems small for exploratory runs.
• Choose direct listing URLs for review text. Category and search pages provide summaries rather than deeper reviews.
• Limit your review sample. Disable includeReviews when only listing summaries are needed, or lower maxReviewsPerListing for fewer review rows.

Limits and caveats

Row limits do not guarantee that every input page will be reached.

• Coverage: category and search results are summaries. Discovered listing links are not automatically opened for deeper reviews.
• Review depth: only reviews supplied by each fetched listing page are available. There is no complete-review-history guarantee.
• Ordering: results follow source encounter order. There is no selectable sort or cross-page ranking.
• Partial batches: isolated unavailable pages can be skipped while useful rows from other pages remain. Check RUN_SUMMARY before interpreting a small or empty result.
• Availability: layouts and access restrictions can change. Invalid configuration and fatal execution failures still fail the run.

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.

Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/productreview-com-au-scraper').call({
  query: 'iphone', maxItems: 20,
});
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/productreview-com-au-scraper').call(
    run_input={'query': 'iphone', 'maxItems': 20})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)

cURL

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~productreview-com-au-scraper/runs' \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"query":"iphone","maxItems":20}'

MCP and AI agents

You can ask your AI assistant to collect data with ProductReview.com.au 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 ProductReview.com.au 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

• Claude and Claude Code (Anthropic): Apify setup guide.
• ChatGPT and Codex (OpenAI): Apify setup guides.
• Grok Bot (xAI): Apify plugin guide.
• Gemini CLI (Google): MCP server setup guide. Use the server URL below with the HTTP configuration supported by Gemini CLI.

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/productreview-com-au-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 ProductReview.com.au Scraper by Fetch Cat, or give it the identifier fetch_cat/productreview-com-au-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

• “Collect up to 20 mobile-phone listing summaries from ProductReview.com.au and compare the returned ratings and review counts.”
• “Get available reviews from this ProductReview.com.au iPhone listing, using a small sample, and summarize themes in the returned text.”
• “Search ProductReview.com.au for NBN providers and organize up to 20 returned listing summaries into a comparison table.”

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

A successful empty result is not evidence that no reviews exist on the entire site.

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

Does it need a ProductReview.com.au login?

No. It uses public pages, without account cookies or private data access.

Can I export ProductReview.com.au reviews to CSV?

Yes, when review rows are available from the supplied listing pages. Export the dataset and filter recordType to review if you do not want listing summaries.

Is this an official ProductReview.com.au API?

No. It is an independent scraper with Apify API access, not an official ProductReview.com.au integration.

Why are reviews or fields missing?

Category and search inputs generally provide summaries. Supply direct listing URLs for available reviews, check the review settings and inspect RUN_SUMMARY. Optional fields are not guaranteed, and an inaccessible page does not establish deletion.

Related Actors

• Trustpilot Reviews Scraper — Collect public Trustpilot business reviews, ratings and available company details.
• Google Maps Reviews Scraper — Collect available public Google Maps review text, ratings and reviewer fields.
• Amazon Reviews Scraper — Collect available public Amazon product reviews, ratings and review metadata.
• Yelp Reviews Scraper — Collect available public Yelp business reviews and ratings.
• Tripadvisor Reviews Scraper — Collect available public Tripadvisor review text, ratings and visit details.

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. ♥