# Liquidiv Reviews Spider (`getdataforme/liquidiv-reviews-spider`) Actor The LiquidIV Reviews Spider is an Apify Actor that scrapes customer reviews from LiquidIV product pages, extracting titles, ratings, sentiments, and verified buyer details.... - **URL**: https://apify.com/getdataforme/liquidiv-reviews-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Agents, 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 ## LiquidIV Reviews Spider ### Introduction The LiquidIV Reviews Spider is a powerful Apify Actor designed to scrape and extract customer reviews from LiquidIV product pages on their official website. It provides structured, high-quality data on product feedback, ratings, and user sentiments, enabling businesses and researchers to gain valuable insights into consumer opinions. This tool streamlines the process of gathering review data, saving time and effort while ensuring accuracy and reliability. ### Features - **Comprehensive Review Extraction**: Captures detailed review information including titles, content, ratings, and timestamps from specified LiquidIV product URLs. - **Sentiment Analysis**: Automatically calculates sentiment scores for each review to gauge overall customer satisfaction. - **Verified Buyer Tracking**: Identifies verified purchases to highlight authentic feedback. - **Product Variant Details**: Extracts specific product attributes like size and flavor for targeted analysis. - **High Reliability**: Built with robust error handling to ensure consistent data extraction even from dynamic web pages. - **Scalable Performance**: Handles multiple URLs efficiently, supporting batch processing for large-scale data collection. - **JSON Output**: Delivers clean, structured JSON data ready for integration into analytics tools or databases. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|------|----------|-------------|---------| | Urls | array | Yes | A list of URLs pointing to LiquidIV product pages from which to scrape reviews. Each URL must be a valid HTTP or HTTPS link. | ["https://www.liquid-iv.com/products/pomegranate-punch-hydration-sugar-free-energy-multiplier?Flavor=Pomegranate+Punch&Size=14PK&selling_plan=21425094692"] | ### Example Usage #### Input Configuration ```json { "Urls": [ "https://www.liquid-iv.com/products/pomegranate-punch-hydration-sugar-free-energy-multiplier?Flavor=Pomegranate+Punch&Size=14PK&selling_plan=21425094692" ] } ```` #### Example Output ```json [ { "Review_Id": 798754977, "Product_Id": "7987500253220", "Title": "Probably one of my favorite", "Content": "Probably one of my favorite flavors! Was surprised when I tried it and I have gotten a few others that agree it's really good!", "Rating": 5, "Verified_Buyer": true, "Created_At": "2026-01-13T01:48:36", "Sentiment": 0.9790651, "Is_Incentivized": false, "User_Name": "Jessica D.", "Product_Variants": { "Size": "14PK", "Flavor": "Pomegranate Punch" }, "Country": "\ud83c\uddfa\ud83c\uddf8 United States", "actor_id": "9ADxA9VQTgv5MhW3i", "run_id": "sj9yhoIZcaaCVUsbZ" } ] ``` ### Use Cases - **Market Research**: Analyze customer feedback to identify trends in product preferences and satisfaction levels for LiquidIV beverages. - **Competitive Intelligence**: Compare review data across similar hydration products to benchmark performance and uncover competitive advantages. - **Price Monitoring**: Track user sentiments related to pricing and value, informing dynamic pricing strategies. - **Content Aggregation**: Collect and aggregate reviews for content creation, such as blog posts or social media campaigns. - **Academic Research**: Study consumer behavior and sentiment in the health and wellness industry using real-world data. - **Business Automation**: Integrate review data into dashboards for automated reporting on product performance and customer loyalty. ### Installation and Usage 1. Search for "LiquidIV Reviews Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters by providing the list of URLs. 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 data in JSON format as an array of review objects. Each object includes fields such as Review\_Id (unique identifier), Product\_Id (associated product), Title and Content (review text), Rating (numerical score), Verified\_Buyer (boolean for authenticity), Created\_At (timestamp), Sentiment (analysis score), Is\_Incentivized (incentive flag), User\_Name, Product\_Variants (size and flavor details), Country, and metadata like actor\_id and run\_id. This structured format ensures easy parsing and integration into downstream applications. ### 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! *** # Actor input Schema ## `Urls` (type: `array`): The urls for the spider. ## Actor input object example ```json { "Urls": [ "https://www.liquid-iv.com/products/pomegranate-punch-hydration-sugar-free-energy-multiplier?Flavor=Pomegranate+Punch&Size=14PK&selling_plan=21425094692" ] } ``` # 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("getdataforme/liquidiv-reviews-spider").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("getdataforme/liquidiv-reviews-spider").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 '{}' | apify call getdataforme/liquidiv-reviews-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/liquidiv-reviews-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Liquidiv Reviews Spider", "description": "The LiquidIV Reviews Spider is an Apify Actor that scrapes customer reviews from LiquidIV product pages, extracting titles, ratings, sentiments, and verified buyer details....", "version": "0.0", "x-build-id": "knte35ns8UoCzvkZz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~liquidiv-reviews-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-liquidiv-reviews-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~liquidiv-reviews-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-liquidiv-reviews-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~liquidiv-reviews-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-liquidiv-reviews-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Urls": { "title": "Urls", "minItems": 1, "type": "array", "description": "The urls for the spider.", "default": [ "https://www.liquid-iv.com/products/pomegranate-punch-hydration-sugar-free-energy-multiplier?Flavor=Pomegranate+Punch&Size=14PK&selling_plan=21425094692" ], "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```