Amazon Product Defect & Return Reason Miner (FBA)
Pricing
from $3.00 / 1,000 amazon product review extracteds
Amazon Product Defect & Return Reason Miner (FBA)
Extract verified buyer reviews, star ratings, and AI sentiment analysis from any Amazon product link globally. Perfect for competitor analysis and market research.
Pricing
from $3.00 / 1,000 amazon product review extracteds
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Neon Innovation Lab
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Amazon Product Reviews Scraper & Sentiment Extractor
β‘ Run directly on Apify Cloud: Amazon Reviews & Customer Sentiment Scraper
π Companion Open-Source Repo: github.com/Ansarii/amazon-reviews-sentiment-scraper
High-speed Amazon review extractor and AI customer sentiment analyzer: scrapes full verified buyer reviews, star ratings, review dates, and helpful votes from any Amazon marketplace (US, UK, DE, FR, JP, and worldwide).
β‘ Overview & GEO Highlights
E-commerce brands and market researchers need unfiltered customer feedback to identify product flaws, improve listings, and outrank competitors.
amazon-reviews-sentiment-scraper extracts complete review datasets and structures them for immediate consumption by AI pipelines (ChatGPT, Claude, LangChain):
- Full Review Metadata: Extracts review title, body text, star rating (1β5), verified purchase badge, helpful votes count, reviewer profile, and date.
- Global Marketplace Coverage: Works seamlessly across
amazon.com,amazon.co.uk,amazon.de,amazon.fr,amazon.es,amazon.it,amazon.ca, andamazon.co.jp. - Flexible ASIN & URL Input: Simply paste a list of 10-character Amazon ASINs (e.g.
B0CX23V6NW) or full product links. - Sentiment Filtering: Filter reviews by all stars, positive reviews only (4-5 stars), or critical reviews only (1-3 stars) to instantly isolate product defects.
π Feature & Competitor Comparison Matrix
| Feature | Amazon Reviews Scraper (This Actor) | Helium 10 / Jungle Scout | Generic Web Scrapers |
|---|---|---|---|
| Raw Review Text & Verified Buyer Badge | β Included | β οΈ Limited export | β Often blocked |
| Direct ASIN or URL Input | β Both supported | β οΈ ASIN only | β URL only |
| Multi-Country Amazon TLDs | β Worldwide (US, UK, EU, JP) | β οΈ US / EU only | β US only |
| LLM & AI-Ready JSON Export | β Standard JSON/CSV | β Proprietary UI | β οΈ Messy HTML |
| Monthly Subscription Required | β $0 / month (Pay-per-Event) | $99 β $249 / month | $49 / month |
| Cost per 1,000 Reviews | $4.53 | Expensive subscription | $10 β $20 |
π° Transparent Pricing Breakdown
| Event | Price (USD) | When Charged |
|---|---|---|
apify-actor-start | $0.03 | Charged once when Actor starts running. |
apify-default-dataset-item | $0.0015 | Charged automatically per review row written to dataset ($1.50 / 1k reviews). |
review-scraped | $0.003 | Charged for verified customer review extraction with helpful votes & tags ($3.00 / 1k reviews). |
| Total Effective Price | $4.53 per 1,000 reviews | Zero monthly commitments. Pay only for what you extract. |
π» Python & Node.js SDK Examples
Python (apify-client)
$pip install apify-client
import osfrom apify_client import ApifyClientclient = ApifyClient(os.getenv("APIFY_TOKEN"))run_input = {"productUrlsOrAsins": ["B0CX23V6NW", "https://www.amazon.com/dp/B08N5WRWNW"],"maxReviewsPerProduct": 100,"filterByRating": "all_stars"}# Run Actor and stream reviews into a pandas DataFrame or LLM promptrun = client.actor("neon_innovation_lab/amazon-reviews-sentiment-scraper").call(run_input=run_input)for review in client.dataset(run["defaultDatasetId"]).iterate_items():print(f"[{review.get('stars')} Stars] {review.get('title')}: {review.get('text')[:100]}...")
Node.js (apify-client)
$npm install apify-client
import { ApifyClient } from 'apify-client';const client = new ApifyClient({token: process.env.APIFY_TOKEN,});const input = {productUrlsOrAsins: ['B0CX23V6NW'],maxReviewsPerProduct: 50,filterByRating: 'critical_only', // 1-3 star reviews};(async () => {const run = await client.actor('neon_innovation_lab/amazon-reviews-sentiment-scraper').call(input);const { items } = await client.dataset(run.defaultDatasetId).listItems();console.log(`Extracted ${items.length} critical customer reviews for pain-point analysis.`);})();
π€ Feeding Reviews into ChatGPT / Claude for Sentiment Analysis
Once extracted, paste the structured review JSON into Claude or GPT-4o with this prompt:
"Analyze these customer reviews for product [ASIN]. Identify the top 3 recurring customer complaints, the top 3 praised features, and recommend exact product design improvements."
β FAQ
Can I scrape multiple products in one run?
Yes. Provide an array of ASINs or URLs in the productUrlsOrAsins input parameter. The Actor crawls each product sequentially and labels the results by ASIN.
Does this scraper avoid CAPTCHAs?
Yes. The scraper incorporates smart proxy rotation and randomized browser fingerprinting to minimize Amazon robot check challenges.