# GoodFirms Company Reviews Scraper (`powerai/goodfirms-company-reviews-scraper`) Actor Scrape company reviews from GoodFirms.co with comprehensive review data including ratings, project details, and company responses. - **URL**: https://apify.com/powerai/goodfirms-company-reviews-scraper.md - **Developed by:** [PowerAI](https://apify.com/powerai) (community) - **Categories:** Lead generation, Automation, Integrations - **Stats:** 8 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. 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. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## 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. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## 🏢 GoodFirms Company Reviews Scraper This actor allows you to scrape company reviews from GoodFirms.co by providing a company profile URL with reviews. It automatically handles pagination and extracts comprehensive review information including ratings, reviewer details, project information, and company responses. ### Features - **URL-based Scraping:** Extract reviews by providing a GoodFirms company profile URL with reviews section - **Automatic Pagination:** Automatically navigates through review pages until reaching the end or max items limit - **Comprehensive Review Data:** Extract detailed information about each review including: - Review title and summary - Reviewer information (name, title, company, profile image) - Overall rating and detailed rating breakdown - Project Q\&A responses - Project details (cost, status, industry) - Company responses to reviews - Review dates and share links ### Input Parameters | Field | Type | Required | Description | |------------|---------|----------|------------------------------------------------| | `searchUrl`| string | Yes | GoodFirms company profile URL with reviews section (e.g., https://www.goodfirms.co/company/company-name#review_analytics) | | `maxItems` | integer | No | Maximum number of reviews to fetch (default: unlimited) | | `proxyConfiguration` | object | No | Proxy configuration settings | #### How to Get Search URL 1. Go to [GoodFirms.co](https://www.goodfirms.co) 2. Navigate to a company profile page 3. Click on the reviews section or scroll to reviews 4. Copy the complete URL from your browser's address bar (should include `#review_analytics` or similar anchor) 5. Paste it into the `searchUrl` field Example search URL: ``` https://www.goodfirms.co/company/sdlc-corp#review_analytics ``` ### Output The output is a dataset of review objects, each containing: - `searchUrl`: The original search URL used - `id`: Unique review identifier - `detailPageUrl`: Direct link to the review detail page - `reviewShareTitle`: Share title for the review - `reviewTitle`: Title of the review - `reviewSummary`: Main review text/summary - `reviewer`: Object containing reviewer information: - `name`: Reviewer's name - `image`: Reviewer's profile image URL - `imageAlt`: Alt text for the image - `title`: Reviewer's job title - `company`: Reviewer's company name - `reviewDate`: Date when the review was posted - `overallRating`: Overall rating score (typically 1-5) - `ratingBreakdown`: Object with detailed ratings for different aspects: - `Quality`: Rating for quality - `Schedule & Timing`: Rating for timing - `Communication`: Rating for communication - `Overall Rating`: Overall rating value - `projectQAs`: Object containing project-related Q\&A responses - `projectDetails`: Object containing project information: - `Project Cost`: Cost range of the project - `Project Status`: Current status of the project - `Project Industry`: Industry of the project - `companyResponse`: Object containing company's response (if available): - `company`: Company name - `response`: Response text - `date`: Response date - `image`: Company image URL - `imageAlt`: Alt text for company image - `scrapedAt`: Timestamp of when the review was scraped Example output: ```json [ { "searchUrl": "https://www.goodfirms.co/company/sdlc-corp#review_analytics", "id": "review-80437", "detailPageUrl": "https://www.goodfirms.co/company/sdlc-corp#review-80437", "reviewShareTitle": "Their deep discovery process meant they understood our business needs better than we did. - Reviewed by Tim Launiere for SDLC Corp", "reviewTitle": "Their deep discovery process meant they understood our business needs better than we did.", "reviewSummary": "Our sales team was frustrated with constant errors and delays in the quote process. SDLC Corp started by spending weeks mapping our entire workflow and identifying pain points we'd learned to live with. The solution they built eliminated manual errors and reduced our sales cycle time by nearly 20%. The team now trusts the system completely, and we're closing deals faster without the previous headaches.", "reviewer": { "name": "Tim Launiere", "image": "https://assets.goodfirms.co/profile/thumb/55a1c4154835c7626cb51ce47a27769b.jpg", "imageAlt": "Tim Launiere", "title": "President", "company": "DieBotics" }, "reviewDate": "1 day ago", "overallRating": 5, "ratingBreakdown": { "Quality": 5, "Schedule & Timing": 5, "Communication": 5, "Overall Rating": 5 }, "projectQAs": { "What was the project name that you have worked with SDLC Corp?": "Quote-to-Cash System", "What service was provided as part of the project?": "Software Development", "Describe your project in brief": "SDLC Corp completely redesigned our quote-to-cash process on Salesforce...", "What is it about the company that you appreciate the most?": "Their patience during the discovery phase...", "What was it about the company that you didn't like which they should do better?": "The extensive discovery phase required more time..." }, "projectDetails": { "Project Cost": "$10001 to $50000", "Project Status": "Completed", "Project Industry": "Manufacturing" }, "companyResponse": { "company": "SDLC Corp", "response": "We appreciate your kind words, Tim...", "date": "1 day ago", "image": null, "imageAlt": "SDLC Corp" }, "scrapedAt": "2025-11-11T06:57:44.324Z" }, ... ] ``` ### Use Cases - Competitive analysis and market research - Reputation monitoring for companies - Customer sentiment analysis - Service quality assessment - Project cost and industry trend analysis - Review aggregation and reporting - Brand reputation tracking ### Notes - Results are saved incrementally as they are found - All timestamps are in ISO 8601 format - Reviews are automatically deduplicated based on detail page URLs - Company responses are included when available - Rating breakdowns provide detailed insights into different service aspects *** **Start scraping company reviews from GoodFirms today!** # Actor input Schema ## `searchUrl` (type: `string`): The GoodFirms company profile URL with reviews section (e.g., https://www.goodfirms.co/company/company-name#review_analytics) ## `maxItems` (type: `integer`): Maximum number of reviews to fetch ## `proxyConfiguration` (type: `object`): Proxy settings for the actor ## Actor input object example ```json { "searchUrl": "https://www.goodfirms.co/company/sdlc-corp#review_analytics", "maxItems": 100, "proxyConfiguration": { "useApifyProxy": false, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("powerai/goodfirms-company-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 = {} # Run the Actor and wait for it to finish run = client.actor("powerai/goodfirms-company-reviews-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call powerai/goodfirms-company-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,powerai/goodfirms-company-reviews-scraper" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/HqeIHFCV5OCLI0Tde/builds/lxFZDT2JPasfdRikl/openapi.json