
ProductReview.com.au Scraper
hipersoft/productreview-scraper
Scrape reviews and ratings from ProductReview.com.au, Australia's biggest review site. Star rating, title, text, date, likes, verified purchase, incentivised flag, purchase price, store and date, sub-ratings, photos; plus listing rating, review count and star breakdown. Export CSV/JSON.
Total users
2Monthly users
1Total runs
4Per result
$0.001Last rebuilt
Oct 26, 2026Overview
ProductReview.com.au Scraper extracts customer reviews and ratings from ProductReview.com.au, Australia's largest consumer review platform, covering products, brands, retailers, insurers, banks, telcos, energy providers, airlines, mattresses, appliances, cars, phones and local businesses. For every review you get the star rating, title, full review text, publish date, likes and dislikes, verified purchase flag, incentivised review flag, purchase price (AUD), store where it was bought, purchase date, sub-ratings (value for money, ease of use, customer service, battery life…), photos and company reply count. In listings mode you get a summary per product or business: average rating, total reviews, questions, 1–5 star breakdown, brand, categories, release date and image. Search by keyword or paste listing links, filter by star rating, and export to CSV, Excel or JSON. Ideal for brand monitoring, competitor analysis, sentiment analysis, product research, customer-experience teams and AI training data in Australia.
What does ProductReview.com.au Scraper do?
- ⭐ Full reviews with star rating, title, text and date.
- 🛒 Purchase details: price paid, store and purchase date.
- ✅ Verified purchase and incentivised review flags.
- 📊 Sub-ratings such as value for money, ease of use, customer service.
- 🖼️ Review photos and company reply counts.
- 🔎 Search by keyword or paste listing links.
- 📈 Listings mode: rating, review count and star distribution for many products or businesses at once.
- 🎯 Star filter: collect only 1-star or 5-star reviews.
What data can you scrape from ProductReview.com.au?
| Field | Description |
|---|---|
| Review | ID, link, stars, title, text, published and modified dates |
| Engagement | Likes, dislikes, company replies |
| Trust | Verified purchase, incentivised review |
| Purchase | Price paid (AUD), store, purchase date |
| Sub-ratings | Value for money, ease of use, service and other criteria |
| Media | Photo count and photo links |
| Listing | Name, link, overall rating |
Use cases for Australian review data
- Brand monitoring: track new reviews about your products or company.
- Competitor analysis: compare ratings and complaints across competitors.
- Sentiment analysis and NLP: build datasets of Australian consumer opinions.
- Product research: find what buyers love or hate before launching or stocking a product.
- Pricing insights: see what customers actually paid and where they bought.
- Customer experience: surface recurring issues from 1- and 2-star reviews.
How to scrape ProductReview.com.au
- Click Try for free to open the actor in Apify Console.
- Paste listing links or enter search terms.
- Choose Reviews or Listings mode and optional star filter.
- Click Start and download the data as CSV, Excel or JSON.
Input
Example input
{
"mode": "reviews",
"listingUrls": ["https://www.productreview.com.au/listings/koala-mattress"],
"searchQueries": ["robot vacuum"],
"maxListingsPerSearch": 5,
"maxReviewsPerListing": 300,
"starFilter": ["1", "2"]
}
| Field | Description |
|---|---|
| What to scrape | Reviews or Listings (summary). |
| Listing links | ProductReview.com.au listing URLs or slugs. |
| Search terms | Keywords to find listings. |
| Listings per search | Listings taken from each search. |
| Max reviews per listing | 0 = as many as available. |
| Only these star ratings | Optional star filter. |
| Max results | 0 = no limit. |
Output
Review example
{
"reviewId": "dc87d9a6-955c-5276-bffc-e5454712e991",
"reviewUrl": "https://www.productreview.com.au/reviews/dc87d9a6-955c-5276-bffc-e5454712e991",
"listingName": "Apple iPhone 15",
"listingRating": 4.4,
"rating": 5,
"body": "5th iPhone purchase from Reebelo and the products have all been first class...",
"publishedAt": "2026-08-05T04:47:54Z",
"likes": 0,
"verifiedPurchase": false,
"incentivised": false,
"purchasePrice": 700,
"purchaseLocation": "Reebelo Australia",
"purchaseDate": "2026-06-01",
"detailRatings": { "Value for Money": 5, "Ease of Use": 5 },
"photoCount": 0
}
Listing example (listings mode)
{
"name": "Dyson V8",
"brand": "Dyson",
"categories": ["Products", "Appliances", "Vacuum Cleaners", "Stick & Cordless Vacuum Cleaners"],
"rating": 4.1,
"reviewCount": 1722,
"questionCount": 523,
"ratingDistribution": { "1": 143, "2": 99, "3": 111, "4": 324, "5": 1045 },
"releaseDate": "2016-08-30",
"url": "https://www.productreview.com.au/listings/dyson-v8"
}
Output schema
| Field | Type | Description |
|---|---|---|
reviewId, reviewUrl, rating, title, body |
mixed | Review. |
publishedAt, modifiedAt |
string | Dates (ISO). |
likes, dislikes, companyReplyCount |
number | Engagement. |
verifiedPurchase, incentivised |
boolean | Trust flags. |
purchasePrice, purchaseLocation, purchaseDate |
mixed | Purchase details. |
detailRatings, tags |
object | Sub-ratings and tags. |
photoCount, photos |
mixed | Review photos. |
listingName, listingUrl, listingRating |
mixed | Listing. |
Reviewer names are not collected.
How much does it cost?
The scraper uses pay-per-result pricing: a small fixed price per review or listing, with automatic discounts on higher Apify plans. See the Pricing tab for the exact price.
More review data
- Trusted Shops Scraper: European shop reviews.
- Judge.me Reviews Scraper: Shopify product reviews.
FAQ
How many reviews can I get per listing? Up to several thousand for large listings. For the biggest listings, use the star filter to target specific ratings.
Can I monitor new reviews? Yes. Schedule the actor daily with a small "Max reviews per listing"; reviews come newest first.
What formats can I export? CSV, Excel, JSON, XML, HTML and RSS, or read the results through the Apify API.
Can I integrate it with other apps? Yes. The actor can be connected with almost any cloud service or web app thanks to integrations on the Apify platform. It works with Make, Zapier, Slack, Airbyte, GitHub, Google Drive and many more, plus the Apify API, JS/Python clients and MCP. Or use webhooks to trigger an action whenever a run finishes.
Is it legal to scrape ProductReview.com.au? The scraper only collects publicly visible review content and no reviewer names or contact details. You are responsible for using the data in line with the site's terms and privacy law.
Notes
Original clean-room implementation. Returns only public data. Not affiliated with ProductReview.com.au.
Input
| Field | Type | Description |
|---|---|---|
modeWhat to scrape | string · reviews, listings | Reviews: every review of the listings. Listings: one summary row per product or business (rating, review count, star breakdown). Default: "reviews" |
listingUrlsListing links | array | ProductReview.com.au listing links or slugs, e.g. https://www.productreview.com.au/listings/koala-mattress or dyson-v8. |
searchQueriesSearch terms | array | Find listings by keyword (product, brand, business or service), e.g. robot vacuum, health insurance, Telstra. |
maxListingsPerSearchListings per search | integer | How many listings to take from each search. Default: 10 |
maxReviewsPerListingMax reviews per listing | integer | Stop after this many reviews for each listing (0 = as many as available). Default: 200 |
starFilterOnly these star ratings | array | Optional: collect only reviews with these star ratings. |
maxItemsMax results | integer | Stop after this many results in total (0 = no limit). Default: 1000 |
proxyConfigurationProxy configuration | object | Not needed in most cases. Default: {"useApifyProxy": false} |
API
curl -X POST "https://api.apify.com/v2/acts/hipersoft~productreview-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"listingUrls": [
"https://www.productreview.com.au/listings/apple-iphone-15"
]
}'from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("hipersoft/productreview-scraper").call(run_input={
"listingUrls": [
"https://www.productreview.com.au/listings/apple-iphone-15"
]
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('hipersoft/productreview-scraper').call({
"listingUrls": [
"https://www.productreview.com.au/listings/apple-iphone-15"
]
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);Pricing
| Event | Price | Paid plans from |
|---|---|---|
| Result Charged per review or listing returned | $0.001 | $0.0005 |
You pay only for what the run returns. Set a maximum cost per run and it stops cleanly at that limit.
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