ProductReview.com.au Scraper

Scrape public ProductReview.com.au listings, ratings, review counts, and review metadata from category, search, and listing pages.

Use it to monitor Australian product reputation, compare brands, collect review signals, and build reporting datasets from ProductReview.com.au.

At a glance

• Extracts: listings, ratings, review counts, category data, reviewer names, dates, review ratings, review titles, review text, and source URLs.
• Inputs: ProductReview.com.au category URLs, search/listing URLs, search query, row limits, review toggle, review-per-listing limit, and proxy settings.
• Best for: reputation monitoring, product-category research, competitor comparison, review evidence collection, and Australian market reporting.
• Exports: Apify dataset rows downloadable as CSV, JSON, Excel, XML, RSS, or available through the API.
• Login: no ProductReview.com.au account is required for public pages.

What can it do?

ProductReview.com.au Scraper turns public ProductReview.com.au pages into structured dataset rows.

• Scrape category pages: start from pages such as mobile phones, insurance, appliances, or services.
• Scrape search results: use a keyword when you do not already have exact ProductReview URLs.
• Scrape direct listings: monitor specific products or businesses repeatedly.
• Save listing rows: collect listing names, brands, categories, ratings, review counts, URLs, images, and timestamps.
• Save review rows: optionally collect visible review metadata and text from listing pages.
• Audit every row: keep source URLs and scrape timestamps in the dataset.

Who is it for?

• Ecommerce teams: track how products are reviewed in Australia.
• Brand managers: compare product lines, competitors, and rating trends.
• Reputation analysts: collect review evidence for dashboards and reports.
• Product teams: find positive and negative customer feedback signals.
• Retail teams: monitor categories and competitor listings.
• Automation teams: feed review data into BI tools, CRMs, and alerts.

Why use this scraper?

• Australian review source: ProductReview.com.au is useful for local consumer reputation research.
• Structured exports: avoid slow copy-paste and get clean rows for CSV, JSON, Excel, and API workflows.
• Cost control: cap total rows with maxItems and cap review rows with maxReviewsPerListing.
• Flexible depth: include listing-level data only or add visible review rows when you need text and reviewer context.
• Scheduling: run manually or schedule repeat monitoring jobs on Apify.

Quick start

1. Open the actor on Apify.

2. Paste one or more ProductReview.com.au URLs into Start URLs.

3. Optionally enter a Search query.

4. Set Maximum rows.

5. Choose whether to Include reviews.

6. Click Start.

7. Download the dataset as CSV, JSON, Excel, XML, or RSS.

Output example

{
  "recordType": "listing",
  "sourceUrl": "https://www.productreview.com.au/c/mobile-phones",
  "listingUrl": "https://www.productreview.com.au/listings/apple-iphone-14",
  "listingName": "Apple iPhone 14",
  "brand": "Apple",
  "category": "Best Mobile Phones",
  "rating": 4.1,
  "reviewCount": 69,
  "scrapedAt": "2026-06-28T00:00:00.000Z"
}

Tips for better results

• Use category pages for discovery: category URLs are best when you want multiple listings.
• Use listing pages for repeatability: direct listing URLs are best for dashboards and monitoring.
• Start small: use a low maxItems value for test runs.
• Scale after checking output: increase maxItems for scheduled monitoring after reviewing sample rows.
• Use search for exploration: queries are useful when you do not know exact listing URLs yet.

Common workflows

• Category monitoring: monitor a product category weekly.
• Rating tracking: track star ratings for a shortlist of listings.
• Reputation evidence: collect review authors, dates, titles, and text for analysis.
• Competitor comparison: build a comparison dataset across brands or product lines.
• Alerts: send rating changes to Slack or email using Apify integrations.
• Analytics: export reviews to a warehouse for sentiment analysis.

Integrations

• Use Apify schedules to run the actor automatically.
• Use webhooks to notify your app when a run finishes.
• Use dataset exports for Google Sheets, Excel, Airtable, and BI tools.
• Use the Apify API to trigger runs from your own backend.
• Use Make, Zapier, or n8n to connect datasets to downstream tools.

API usage with 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({
  startUrls: [{ url: 'https://www.productreview.com.au/c/mobile-phones' }],
  maxItems: 25,
  includeReviews: true
});
console.log(run.defaultDatasetId);

API usage with Python

from apify_client import ApifyClient

client = ApifyClient('MY-APIFY-TOKEN')
run = client.actor('fetch_cat/productreview-com-au-scraper').call(run_input={
    'startUrls': [{'url': 'https://www.productreview.com.au/c/mobile-phones'}],
    'maxItems': 25,
    'includeReviews': True,
})
print(run['defaultDatasetId'])

API usage with cURL

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~productreview-com-au-scraper/runs?token=MY-APIFY-TOKEN' \
  -H 'Content-Type: application/json' \
  -d '{"startUrls":[{"url":"https://www.productreview.com.au/c/mobile-phones"}],"maxItems":25,"includeReviews":true}'

MCP and AI agents

Use this actor with Apify MCP tools in Claude Code or Claude Desktop.

MCP URL:

https://mcp.apify.com/?tools=fetch_cat/productreview-com-au-scraper

Add it in Claude Code:

claude mcp add apify-productreview "https://mcp.apify.com/?tools=fetch_cat/productreview-com-au-scraper"

Claude Desktop JSON configuration:

{
  "mcpServers": {
    "apify-productreview": {
      "url": "https://mcp.apify.com/?tools=fetch_cat/productreview-com-au-scraper"
    }
  }
}

Example prompts:

• "Run ProductReview.com.au Scraper for this category and summarize the highest-rated listings."

• "Collect 50 ProductReview rows for mobile phones and export the dataset URL."

• "Compare ratings and review counts for these ProductReview listing URLs."

Scheduling

Create an Apify schedule for weekly category monitoring.

Keep the same start URLs for comparable reports.

Send finished-run webhooks to your reporting workflow.

Store historical datasets to track changes over time.

Troubleshooting

Why did I get fewer rows than requested?

The page may expose fewer listings or reviews than your limit.

The actor stops when it reaches the available visible rows or your maxItems value.

Why is review text empty for some rows?

Some public metadata includes review rating, date, and author without the full body text.

The actor saves fields that are visible in the page data.

Can I scrape private account data?

No. This actor is designed for public ProductReview.com.au pages only.

Limits

The actor is not affiliated with ProductReview.com.au.

Only scrape data you are allowed to use.

Respect ProductReview.com.au terms and applicable laws.

Use reasonable run sizes for monitoring.

Do not overload any website with unnecessary repeated runs.

Legality

This actor extracts publicly available information.

You are responsible for ensuring your use case complies with laws, platform terms, and privacy requirements.

Avoid collecting or processing personal data unless you have a lawful basis.

If in doubt, consult your legal team before running large-scale monitoring.

Support

If a run fails, returns no data, or a field looks wrong, open an issue from the Actor page.

Please include the Apify run ID or run URL, input JSON, one example public URL, query, or input item, what you expected, and what the dataset returned. Small reproducible inputs make parsing or site-layout issues much faster to fix.