# Vagaro Reviews Scraper (`getdataforme/vagaro-reviews-scraper`) Actor Automate review extraction with the Vagaro Reviews Scraper to gain detailed insights into customer feedback, service ratings, and business responses from Vagaro's platform.... - **URL**: https://apify.com/getdataforme/vagaro-reviews-scraper.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 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 ## README.md ### Vagaro Reviews Scraper #### Introduction The **Vagaro Reviews Scraper** is an automated tool designed to extract detailed reviews from Vagaro's platform. It efficiently gathers data on customer feedback, service ratings, and business responses, providing valuable insights for market research, competitive analysis, and customer experience evaluation. #### Features - **Automated Data Extraction**: Seamlessly scrape reviews with minimal setup. - **High-Quality Data**: Ensures accurate and reliable information retrieval. - **Customizable Parameters**: Tailor the scraping process to specific needs. - **Efficient Performance**: Optimized for speed and resource management. - **Comprehensive Output**: Detailed review data including ratings, text, and business responses. #### Input Parameters | Parameter | Type | Required | Description | Example | |---------------|---------|----------|-----------------------------------------------------------------------------|----------------------------------------------| | `startUrls` | array | Yes | URLs to start with. | `[{"url": "https://www.vagaro.com/dupontlashandbrowbarcom/reviews"}]` | | `maxItems` | integer | No | Maximum number of items to scrape. | `100` | #### Example Usage ##### Input JSON ```json { "startUrls": [ { "url": "https://www.vagaro.com/dupontlashandbrowbarcom/reviews" } ], "maxItems": 100 } ```` ##### Output JSON ```json [ { "review_id": 2635676, "reviewer_name": "Justice J", "reviewer_initials": "JJ", "reviewer_photo": "https://1a96a36bae7c8550901a-274b8a70320bb26e7a1e0ea7836ee429.ssl.cf2.rackcdn.com//Images/user-female-img_155.jpg", "reviewer_gender": 3, "reviewer_id": 96512971, "reviewer_first_name": "", "reviewer_last_name": "", "service_provider_name": "Anne Nguyen", "date_published": "2026-06-27", "date_formatted": "Jun 27, 2026", "average_rating": 5, "venue_rating": 5, "punctuality_rating": 5, "value_rating": 5, "service_provider_rating": 5, "review_text": "Anne did a great job on my laminate and tint on my brows. It was my first time getting them done and I was skeptical at first. But the results were better than I expected! Will be back! Even after a week, they still look good.", "review_title": "", "appointment_id": 0, "verified_appointment": true, "business_response_text": "We appreciate your positive feedback and are delighted to hear that Anne Nguyen provided you with exceptional service. It's gratifying to know your initial skepticism transformed into satisfaction. Thank you for trusting us with your brow laminate and tint. We look forward to welcoming you back for your next appointment.", "business_response_date": "Jun 27, 2026", "business_cdn_url": "https://490a0979be23ff94229e-0b531b67caf3bd4a9888808446e5fc53.ssl.cf2.rackcdn.com/", "scraped_at": "2026-07-03T08:23:24.673Z" } ] ``` #### Use Cases - **Market Research and Analysis**: Understand customer sentiment and trends. - **Competitive Intelligence**: Gain insights into competitors' service quality. - **Price Monitoring**: Track pricing strategies through reviews. - **Content Aggregation**: Compile review data for analysis or reporting. - **Academic Research**: Utilize structured review data for studies. - **Business Automation**: Integrate with CRM systems for enhanced customer insights. #### Installation and Usage 1. Search for "Vagaro Reviews Scraper" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters as needed. 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 output is a JSON array of review objects, each containing: - `review_id`: Unique identifier for the review. - `reviewer_name`, `reviewer_initials`, `reviewer_photo`: Reviewer details. - `service_provider_name`: Name of the service provider. - `date_published`, `date_formatted`: Publication dates. - Ratings: `average_rating`, `venue_rating`, `punctuality_rating`, `value_rating`, `service_provider_rating`. - `review_text`: Full review content. - `business_response_text`, `business_response_date`: Business response details. - `scraped_at`: Timestamp of when the data was scraped. #### Error Handling The Actor is designed to handle common errors such as network issues or changes in page structure. If an error occurs, it will be logged for review. Users are encouraged to check logs and adjust parameters if necessary. #### Rate Limiting and Best Practices - **Rate Limiting**: The Actor respects Vagaro's rate limits to prevent IP blocking. - **Best Practices**: Use a diverse set of start URLs to distribute requests evenly and avoid triggering anti-scraping mechanisms. #### Support Section For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: [Contact Us](https://getdataforme.com/contact/) We're here to help you get the most out of this Actor! *** ## Description Maximize your insights with the **Vagaro Reviews Scraper**. This powerful tool automates the extraction of detailed reviews, ratings, and business responses from Vagaro's platform. Ideal for market research, competitive analysis, and customer experience evaluation, it offers high-quality data and customizable parameters. Start extracting valuable insights today! # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## `maxItems` (type: `integer`): Maximum number of items to scrape. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.vagaro.com/dupontlashandbrowbarcom/reviews" } ], "maxItems": 100 } ``` # Actor output Schema ## `results` (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 = { "startUrls": [ { "url": "https://www.vagaro.com/dupontlashandbrowbarcom/reviews" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/vagaro-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 = { "startUrls": [{ "url": "https://www.vagaro.com/dupontlashandbrowbarcom/reviews" }] } # Run the Actor and wait for it to finish run = client.actor("getdataforme/vagaro-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 '{ "startUrls": [ { "url": "https://www.vagaro.com/dupontlashandbrowbarcom/reviews" } ] }' | apify call getdataforme/vagaro-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/vagaro-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Vagaro Reviews Scraper", "description": "Automate review extraction with the Vagaro Reviews Scraper to gain detailed insights into customer feedback, service ratings, and business responses from Vagaro's platform....", "version": "0.0", "x-build-id": "9YpeJS9w1KFEABBhQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~vagaro-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-vagaro-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~vagaro-reviews-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-vagaro-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~vagaro-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-vagaro-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of items to scrape.", "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 } } } } } } } } } } ```