# Gabb Reviews Scraper (`getdataforme/gabb-reviews-scraper`) Actor Extract detailed customer reviews from Gabb products with Gabb Reviews Scraper. Gain valuable insights into ratings, sentiments, topics, and user data via reliable web scraping. Features include sentiment analysis, customizable request limits, robust error handling, and clean JSON output.... - **URL**: https://apify.com/getdataforme/gabb-reviews-scraper.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** Automation, Lead generation, E-commerce - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 1,000 results 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 ### PART 1: README.md ## Gabb Reviews Scraper Gabb Reviews Scraper is an Apify Actor designed to extract customer reviews from Gabb products efficiently and reliably. It leverages web scraping technology to gather detailed review data, including ratings, content, user information, and sentiment analysis, directly from Gabb's website. This tool is ideal for businesses, researchers, and analysts seeking insights into product performance and customer feedback without manual effort. ### Features - **Comprehensive Review Extraction**: Scrapes full review details such as scores, votes, content, titles, timestamps, and user profiles. - **Sentiment Analysis**: Includes built-in sentiment scores and topic extraction for deeper insights. - **High Reliability**: Handles dynamic web content with robust error handling and retries. - **Customizable Requests**: Allows setting maximum requests per crawl to control data volume and avoid rate limits. - **Structured Output**: Delivers data in clean JSON format, ready for analysis or integration. - **Fast and Scalable**: Built on Apify's infrastructure for quick execution and handling large-scale scrapes. - **Privacy-Focused**: Respects website terms and focuses on publicly available data. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|------|----------|-------------|---------| | productName | string | Yes | The name of the Gabb product to scrape reviews for. This should match the product's URL slug or identifier on Gabb's site. | "gabb-phone-4" | | maxRequestsPerCrawl | integer | No | Maximum number of HTTP requests the crawler can make during the run. Helps manage costs and avoid overloading the target site. Default is 100. | 50 | ### Example Usage To run the Actor, provide the input parameters in JSON format: ```json { "productName": "gabb-phone-4", "maxRequestsPerCrawl": 100 } ```` Example output (truncated for brevity): ```json [ { "id": 813392437, "score": 5, "votesUp": 1, "votesDown": 0, "content": "Great starter phone for my 10 year old. She loves the feeling of being a \u201cbig\u201d girl with her phone, but this is so locked down and safe for her age. I\u2019m terrible at tech, but even I can figure out how to monitor her activity and the access she has to apps, etc.", "title": "We love our Gabb!", "createdAt": "2026-02-24T22:52:34", "verifiedBuyer": false, "sentiment": 0.97863007, "isIncentivized": false, "incentiveType": null, "isShop": false, "topics": { "feels": { "name": "feels", "sentence": "She loves the feeling of being a \u201cbig\u201d girl with her phone, but this is so locked down and safe for her age." }, "phone": { "name": "phone", "sentence": "Great starter phone for my 10 year old." }, "gabb": { "name": "gabb", "sentence": "We love our Gabb!" }, "girls": { "name": "girls", "sentence": "She loves the feeling of being a \u201cbig\u201d girl with her phone, but this is so locked down and safe for her age." } }, "fieldsHighlights": null, "customFields": null, "metadata": null, "videosData": null, "imagesData": null, "comment": null, "user": { "userId": 66265611, "socialImage": null, "userType": "User", "isSocialConnected": 0, "displayName": "Catherine B." }, "sourceReviewId": null, "syndicationData": null, "groupingData": null, "country": { "code": "US", "label": "\ud83c\uddfa\ud83c\uddf8 United States" }, "productVariants": null, "language": "en", "translatedLanguage": null } ] ``` ### Use Cases - **Market Research**: Analyze customer sentiment and trends for Gabb products to inform product development. - **Competitive Intelligence**: Compare review data across similar products to identify strengths and weaknesses. - **Price Monitoring**: Track review volumes and ratings to gauge market demand. - **Content Aggregation**: Collect reviews for blogs, reports, or dashboards. - **Academic Research**: Study consumer behavior in safe tech products. - **Business Automation**: Integrate review data into CRM systems for customer insights. ### Installation and Usage 1. Search for "Gabb Reviews Scraper" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters (e.g., product name and max requests). 4. Click "Start" to begin extraction. 5. Monitor progress in the log. 6. Export results in your preferred format (JSON, CSV, Excel). ### Output Format The Actor outputs an array of JSON objects, each representing a single review. Key fields include: - `id`: Unique review identifier. - `score`: Rating out of 5. - `content`: Full review text. - `title`: Review title. - `createdAt`: Timestamp in ISO format. - `sentiment`: Numerical sentiment score (positive values indicate positivity). - `topics`: Extracted topics with example sentences. - `user`: Object with user details like ID and display name. - `country`: Reviewer's country code and label. - Other fields like `verifiedBuyer`, `votesUp`, and `language` provide additional context. Data is structured for easy parsing and analysis. ### Error Handling The Actor includes built-in error handling for common issues like network timeouts or invalid product names. If a product is not found, it logs an error and stops gracefully. For rate limiting, it respects delays between requests. Check the run logs for details on any failures. ### Rate Limiting and Best Practices Gabb's site may have rate limits; set `maxRequestsPerCrawl` conservatively (e.g., 50-100) to avoid blocks. Run during off-peak hours and avoid excessive concurrent runs. Best practices: Validate product names beforehand, use the Actor for targeted scrapes, and export data promptly to prevent storage issues. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! *** ### PART 2: Concise Description Unlock valuable customer insights with Gabb Reviews Scraper, the ultimate tool for extracting detailed reviews from Gabb products. Effortlessly scrape ratings, sentiments, topics, and user data in structured JSON format. Key features include: - Comprehensive review extraction with sentiment analysis - Customizable request limits for efficient crawling - High-reliability handling of dynamic content - Ready-to-analyze output for quick integration Perfect for market research, competitive analysis, and business intelligence. Start scraping today and gain the edge in understanding consumer feedback! (148 words) # Actor input Schema ## `productName` (type: `string`): The name of the product. ## `maxRequestsPerCrawl` (type: `integer`): Maximum number of requests that can be made by this crawler. ## Actor input object example ```json { "productName": "gabb-phone-4", "maxRequestsPerCrawl": 100 } ``` # Actor output Schema ## `overview` (type: `string`): No description # 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 = { "productName": "gabb-phone-4" }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/gabb-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 = { "productName": "gabb-phone-4" } # Run the Actor and wait for it to finish run = client.actor("getdataforme/gabb-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 '{ "productName": "gabb-phone-4" }' | apify call getdataforme/gabb-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/gabb-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Gabb Reviews Scraper", "description": "Extract detailed customer reviews from Gabb products with Gabb Reviews Scraper. Gain valuable insights into ratings, sentiments, topics, and user data via reliable web scraping. Features include sentiment analysis, customizable request limits, robust error handling, and clean JSON output....", "version": "0.0", "x-build-id": "G6GTokD2Qz1awT1b0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~gabb-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-gabb-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~gabb-reviews-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-gabb-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~gabb-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-gabb-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "productName" ], "properties": { "productName": { "title": "Product Name", "type": "string", "description": "The name of the product." }, "maxRequestsPerCrawl": { "title": "Max Requests per Crawl", "type": "integer", "description": "Maximum number of requests that can be made by this crawler.", "default": 100 } } }, "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 } } } } } } } } } } ```