# Amazon Reviews Scraper: Sentiment + Pros/Cons Extraction (`dltik/amazon-reviews-scraper`) Actor Scrape Amazon product reviews with built-in sentiment scoring and automatic pros/cons extraction. Get rating, full text, author, verified flag, helpful votes, date. Supports amazon.com, .fr, .de, .co.uk, .es, .it. For brand monitoring, product research, competitor analysis. $2/1K reviews. - **URL**: https://apify.com/dltik/amazon-reviews-scraper.md - **Developed by:** [dltik](https://apify.com/dltik) (community) - **Categories:** E-commerce, AI, Marketing - **Stats:** 2 total users, 1 monthly users, 88.9% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $2.00 / 1,000 review scrapeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Amazon Reviews Scraper — Sentiment + Pros/Cons Extraction Extract Amazon product reviews with **automatic pros/cons extraction** and **sentiment analysis**. The only Amazon scraper that breaks down each review into positive and negative aspects automatically. **HTTP-only with stealth (curl_cffi + Chrome TLS), 256MB. Apify Residential proxy required.** > ⭐ **Found this useful?** Click the **Bookmark** button at the top of [this page](https://apify.com/dltik/amazon-reviews-scraper) — it helps the scraper stay visible to others who need it. Takes 1 click. No signup beyond your existing Apify account. --- ### What makes this unique | Feature | This actor | Other Amazon scrapers | |---------|-----------|----------------------| | Review text + rating + author | Yes | Yes | | **Sentiment score (per review)** | **Yes** | No | | **Pros extraction** (positive sentences) | **Yes** | No | | **Cons extraction** (negative sentences) | **Yes** | No | | **Aspects** (camera, battery...) | **Yes** | No | | Verified purchase flag | Yes | Most | | Multi-marketplace (com/fr/de/uk) | Yes | Some | --- ### Quick start #### Reviews for a product ```json { "asins": ["B0DKJYXTF9"], "marketplace": "com", "maxReviewsPerProduct": 100, "extractProsCons": true, "proxyConfig": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ```` #### Critical reviews only (1-2 stars) ```json { "asins": ["B0DKJYXTF9"], "filterByStar": "critical", "maxReviewsPerProduct": 50 } ``` #### Multiple products from URLs ```json { "urls": [ "https://www.amazon.com/dp/B0DKJYXTF9", "https://www.amazon.com/dp/B0CKLMRJ2X" ], "marketplace": "com" } ``` *** ### Input | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `asins` | array | — | List of ASINs (10-char codes) | | `urls` | array | — | Product URLs (ASIN extracted) | | `marketplace` | enum | `com` | `com`, `fr`, `de`, `co.uk`, `es`, `it`, `ca`, `co.jp` | | `filterByStar` | enum | `all` | `all`, `5_star`, `4_star`, `1_star`, `positive`, `critical` | | `sortBy` | enum | `recent` | `recent`, `helpful` | | `extractProsCons` | bool | `true` | Auto-extract pros/cons per review | | `maxReviewsPerProduct` | int | `50` | Max 500 | | `proxyConfig` | object | Residential | **Required** | *** ### Output (per review) ```json { "type": "review", "id": "R3OEHK6S0VOL", "asin": "B0DKJYXTF9", "marketplace": "com", "title": "Great quality but the battery life is short", "body": "I love the build quality and it feels premium in hand. The screen is gorgeous. However, the battery dies after just 4 hours of use. Customer support was unhelpful when I reported it. Would still recommend overall but with caveats.", "rating": 4, "author": "John D.", "date": "March 15, 2026", "country": "the United States", "verified": true, "helpful_count": 23, "variation": "Color: Silver Size: 256GB", "url": "https://www.amazon.com/gp/customer-reviews/R3OEHK6S0VOL", "product_url": "https://www.amazon.com/dp/B0DKJYXTF9", "product_title": "iPhone 15 Pro 256GB", "product_average_rating": 4.5, "product_total_reviews": 12453, "sentiment_score": 1.2, "sentiment_label": "positive", "pros": [ "I love the build quality and it feels premium in hand", "The screen is gorgeous", "Would still recommend overall" ], "cons": [ "the battery dies after just 4 hours of use", "Customer support was unhelpful when I reported it" ], "aspects": ["build quality", "screen", "battery"] } ``` *** ### How pros/cons extraction works 1. **Bullet detection** — phrases marked with `+`, `-`, `Pros:`, `Cons:` are explicitly classified 2. **Sentence splitting** — review body is split into sentences 3. **AFINN-165 scoring** — each sentence gets a sentiment score 4. **Classification** — score > +0.8 → pros, score < -0.8 → cons 5. **Aspect extraction** — noun phrases preceded by "the/its/this" + opinion verb Built-in, no external API. Handles negation ("not good" = negative). *** ### Pricing **$0.002 per review** = **$2 per 1,000 reviews**. | Scenario | Reviews | Cost | |----------|---------|------| | 1 product, 50 reviews | 50 | $0.10 | | 5 products, 100 each | 500 | $1.00 | | 10 products, 200 each | 2,000 | $4.00 | Apify Residential proxy adds ~$0.20/1K to your account (separate billing). *** ### Use cases - **Brand monitoring** — auto-classify pros/cons per review for brand managers - **Product research** — surface top complaints across competitors - **Market intelligence** — track sentiment trends over time - **Customer support** — find recurring issues in negative reviews - **Marketing copy** — extract real customer quotes for ads/landing pages - **Competitor analysis** — compare pros/cons of multiple products *** ### Technical notes - **curl\_cffi** with Chrome 131 TLS impersonation = bypasses Amazon's bot detection at TLS layer - **Apify Residential proxy required** — Amazon blocks datacenter IPs for review pages - **Session bootstrap** — visits homepage first to set cookies before fetching reviews - **Pagination** — 10 reviews per page, max ~5,000 per product (Amazon limit) - **Multi-marketplace** — works on Amazon US, FR, DE, UK, ES, IT, CA, JP *** ### Connect with Make, Zapier & n8n ```python from apify_client import ApifyClient client = ApifyClient("YOUR_TOKEN") run = client.actor("dltik/amazon-reviews-scraper").call(run_input={ "asins": ["B0DKJYXTF9"], "marketplace": "com", "extractProsCons": True }) for r in client.dataset(run["defaultDatasetId"]).iterate_items(): if r.get("sentiment_label") == "negative": print(f"⚠️ {r['title']}") for con in r.get("cons", []): print(f" - {con}") ``` *** ### Other scrapers by dltik | Actor | Description | Price | |-------|-------------|-------| | [Trustpilot](https://apify.com/dltik/trustpilot-scraper) | Reviews + sentiment | $0.50/1K | | [Reddit](https://apify.com/dltik/reddit-scraper) | Posts + sentiment | $2/1K | | [Google Maps Email Extractor](https://apify.com/dltik/google-maps-email-extractor) | B2B leads + WhatsApp | $3/1K | | [Welcome to the Jungle](https://apify.com/dltik/welcome-to-the-jungle-scraper) | Tech jobs FR | $0.50/1K | | [HelloWork](https://apify.com/dltik/hellowork-scraper) | French job board | $1/1K | # Actor input Schema ## `asins` (type: `array`): List of Amazon product ASINs (10-character codes like B0DKJYXTF9). Found in product URL. ## `urls` (type: `array`): Amazon product URLs. ASINs will be extracted automatically. ## `marketplace` (type: `string`): Amazon country: com (US), fr (France), de (Germany), co.uk (UK), es (Spain), it (Italy), ca (Canada). ## `extractProsCons` (type: `boolean`): Auto-extract positive and negative phrases from each review using sentence-level sentiment analysis. ## `maxReviewsPerProduct` (type: `integer`): Amazon's PDP shows 3-8 top reviews per product (no login required). For >8 reviews, you need to scrape the full reviews page (requires login cookies). ## `proxyConfig` (type: `object`): Optional proxy. Amazon's PDP page works without proxy in most cases. Add Residential proxy if you hit rate limits or blocks. ## Actor input object example ```json { "asins": [ "B07XJ8C8F5" ], "urls": [], "marketplace": "com", "extractProsCons": true, "maxReviewsPerProduct": 8, "proxyConfig": { "useApifyProxy": false } } ``` # Actor output Schema ## `results` (type: `string`): Reviews with title, body, rating, sentiment, pros, cons. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "asins": [ "B07XJ8C8F5" ] }; // Run the Actor and wait for it to finish const run = await client.actor("dltik/amazon-reviews-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "asins": ["B07XJ8C8F5"] } # Run the Actor and wait for it to finish run = client.actor("dltik/amazon-reviews-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "asins": [ "B07XJ8C8F5" ] }' | apify call dltik/amazon-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dltik/amazon-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Reviews Scraper: Sentiment + Pros/Cons Extraction", "description": "Scrape Amazon product reviews with built-in sentiment scoring and automatic pros/cons extraction. Get rating, full text, author, verified flag, helpful votes, date. Supports amazon.com, .fr, .de, .co.uk, .es, .it. For brand monitoring, product research, competitor analysis. $2/1K reviews.", "version": "1.0", "x-build-id": "WvnfSxMOOhWaRGZZL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dltik~amazon-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dltik-amazon-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dltik~amazon-reviews-scraper/runs": { "post": { "operationId": "runs-sync-dltik-amazon-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dltik~amazon-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-dltik-amazon-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "asins": { "title": "Amazon ASINs", "type": "array", "description": "List of Amazon product ASINs (10-character codes like B0DKJYXTF9). Found in product URL.", "items": { "type": "string" }, "default": [] }, "urls": { "title": "Amazon product URLs (alternative)", "type": "array", "description": "Amazon product URLs. ASINs will be extracted automatically.", "items": { "type": "string" }, "default": [] }, "marketplace": { "title": "Amazon marketplace", "enum": [ "com", "fr", "de", "co.uk", "es", "it", "ca", "co.jp" ], "type": "string", "description": "Amazon country: com (US), fr (France), de (Germany), co.uk (UK), es (Spain), it (Italy), ca (Canada).", "default": "com" }, "extractProsCons": { "title": "Extract pros & cons", "type": "boolean", "description": "Auto-extract positive and negative phrases from each review using sentence-level sentiment analysis.", "default": true }, "maxReviewsPerProduct": { "title": "Max top reviews per product", "minimum": 1, "maximum": 8, "type": "integer", "description": "Amazon's PDP shows 3-8 top reviews per product (no login required). For >8 reviews, you need to scrape the full reviews page (requires login cookies).", "default": 8 }, "proxyConfig": { "title": "Proxy (optional)", "type": "object", "description": "Optional proxy. Amazon's PDP page works without proxy in most cases. Add Residential proxy if you hit rate limits or blocks.", "default": { "useApifyProxy": false } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```