# Sephora Data Scraper (Products, Reviews, Questions & Answers) (`ahmed_jasarevic/sephora-data-scraper-products-reviews-questions-answers`) Actor A powerful and scalable Sephora data scraper that extracts structured e-commerce data directly from Sephora’s backend APIs and Bazaarvoice systems. This Actor supports multiple modes for complete data coverage of Sephora products. - **URL**: https://apify.com/ahmed\_jasarevic/sephora-data-scraper-products-reviews-questions-answers.md - **Developed by:** [Ahmed Jasarevic](https://apify.com/ahmed_jasarevic) (community) - **Categories:** E-commerce, Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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 ## Sephora Master Scraper A high-performance, production-ready **Sephora scraper** for extracting product data, search results, and verified customer reviews from Sephora and Bazaarvoice APIs. This actor supports **4 powerful scraping modes**: - Product search scraping (keyword-based) - Direct product URL scraping - Product reviews extraction (Bazaarvoice API) - Questions and answers Built for scalability, pagination handling, and real-world e-commerce data extraction. --- ### πŸš€ Features - πŸ” **Search Mode** – scrape Sephora search results by keyword - πŸ”— **Direct URL Mode** – extract full product details from PDP pages - πŸ’¬ **Reviews Mode** – collect all customer reviews via Bazaarvoice API - πŸ’¬ **Questions and answers Mode** – collect all customer questions and answers - πŸ“„ Automatic pagination handling - ⚑ High-speed scraping with `got-scraping` - πŸ’Ž Free vs Paid user limits support - πŸ“¦ Structured JSON output - πŸ” Safe retry-ready architecture --- ### 🧠 Modes Overview #### 1. SEARCH MODE (Keyword Scraping) Extract products from Sephora search results. ```json { "mode": "SEARCH", "queries": ["lipstick", "foundation"], "maxItems": 100 } ```` βœ” Supports pagination βœ” Returns product listings βœ” Fast keyword-based discovery *** #### 2. DIRECT\_URLS MODE (Product Details) Scrape full product information from direct Sephora product URLs. ```json { "mode": "DIRECT_URLS", "urls": [ "https://www.sephora.com/product/rare-beauty-soft-pinch-blush-P97989778" ] } ``` βœ” Product variants βœ” Pricing & images βœ” Cross-sell products βœ” Metadata (eligibility, returnability) *** #### 3. REVIEWS\_ONLY MODE (Bazaarvoice Reviews) Extract all customer reviews for a given Sephora product ID. ```json { "mode": "REVIEWS_ONLY", "urls": [ "https://www.sephora.com/product/rare-beauty-soft-pinch-blush-P97989778" ], "maxItems": 200 } ``` βœ” Full review history βœ” Ratings, comments, metadata βœ” Pagination support (offset-based) βœ” Works with Bazaarvoice API *** #### 4. QUESTIONS\_ONLY MODE (Bazaarvoice Questions AND Answers) Extract all customer questions and answers for a given Sephora product ID. ```json { "mode": "QUESTIONS_ONLY", "urls": [ "https://www.sephora.com/product/rare-beauty-soft-pinch-blush-P97989778" ], "maxItems": 200 } ``` βœ” Full questions and answers history βœ” Pagination support (offset-based) βœ” Works with Bazaarvoice API *** ### πŸ“¦ Input Schema | Field | Type | Description | | -------- | ------ | ----------------------------------------- | | mode | string | SEARCH / DIRECT\_URLS / REVIEWS\_ONLY / QUESTIONS\_ONLY | | queries | array | Search keywords (SEARCH mode) | | urls | array | Product URLs (DIRECT\_URLS / REVIEWS\_ONLY / QUESTIONS\_ONLY) | | maxItems | number | Limit results (free/paid aware) | *** ### πŸ’Ž Free vs Paid Usage This scraper supports intelligent usage limits: - **Free users** β†’ capped results (default: 50 items) - **Paid users** β†’ full access to requested `maxItems` Automatically handled via: ```js process.env.APIFY_USER_IS_PAYING ``` *** ### πŸ“Š Output Example #### Product Review Object ```json { "productId": "P97989778", "Rating": 3, "ReviewText": "Pretty color but doesn't last long", "UserNickname": "user123", "SubmissionTime": "2026-04-14T01:28:31Z" } ``` *** ### βš™οΈ Tech Stack - Node.js (ESM) - Apify SDK - got-scraping - Sephora API (v2/v3) - Bazaarvoice Reviews API - Bazaarvoice Questions API *** ### πŸ”₯ Use Cases - E-commerce data analysis - Beauty product tracking - Review sentiment mining - Price & product monitoring - AI dataset creation - SEO keyword research for beauty niche *** ### ⚠️ Disclaimer This actor is intended for educational and research purposes. Users are responsible for complying with website terms of service. *** ### πŸš€ Modes Summary - SEARCH MODE β†’ keyword-based product scraping - DIRECT\_URLS MODE β†’ full product extraction - REVIEWS\_ONLY MODE β†’ deep customer review scraping - QUESTIONS\_ONLY MODE β†’ deep customer questions and answers scraping *** ### ⭐ SEO Keywords Sephora scraper, beauty scraper, product scraper, reviews scraper, Bazaarvoice scraper, e-commerce scraping, Sephora API scraper, cosmetic data extractor, skincare dataset scraper, makeup review scraper # Actor input Schema ## `mode` (type: `string`): Select what the scraper should do ## `queries` (type: `array`): Keywords used in SEARCH mode ## `urls` (type: `array`): Sephora product URLs (used in DIRECT\_URLS and REVIEWS\_ONLY modes) ## `maxItems` (type: `integer`): Maximum number of results to return ## Actor input object example ```json { "mode": "SEARCH", "queries": [ "lipstick" ], "urls": [ "https://www.sephora.com/product/rare-beauty-by-selena-gomez-soft-pinch-liquid-blush-P97989778" ], "maxItems": 100 } ``` # 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 = { "queries": [ "lipstick" ], "urls": [ "https://www.sephora.com/product/rare-beauty-by-selena-gomez-soft-pinch-liquid-blush-P97989778" ] }; // Run the Actor and wait for it to finish const run = await client.actor("ahmed_jasarevic/sephora-data-scraper-products-reviews-questions-answers").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "queries": ["lipstick"], "urls": ["https://www.sephora.com/product/rare-beauty-by-selena-gomez-soft-pinch-liquid-blush-P97989778"], } # Run the Actor and wait for it to finish run = client.actor("ahmed_jasarevic/sephora-data-scraper-products-reviews-questions-answers").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "queries": [ "lipstick" ], "urls": [ "https://www.sephora.com/product/rare-beauty-by-selena-gomez-soft-pinch-liquid-blush-P97989778" ] }' | apify call ahmed_jasarevic/sephora-data-scraper-products-reviews-questions-answers --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ahmed_jasarevic/sephora-data-scraper-products-reviews-questions-answers", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Sephora Data Scraper (Products, Reviews, Questions & Answers)", "description": "A powerful and scalable Sephora data scraper that extracts structured e-commerce data directly from Sephora’s backend APIs and Bazaarvoice systems.\nThis Actor supports multiple modes for complete data coverage of Sephora products.", "version": "0.0", "x-build-id": "G1VWOfNXJmMdCAL4B" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ahmed_jasarevic~sephora-data-scraper-products-reviews-questions-answers/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ahmed_jasarevic-sephora-data-scraper-products-reviews-questions-answers", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ahmed_jasarevic~sephora-data-scraper-products-reviews-questions-answers/runs": { "post": { "operationId": "runs-sync-ahmed_jasarevic-sephora-data-scraper-products-reviews-questions-answers", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ahmed_jasarevic~sephora-data-scraper-products-reviews-questions-answers/run-sync": { "post": { "operationId": "run-sync-ahmed_jasarevic-sephora-data-scraper-products-reviews-questions-answers", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "mode": { "title": "Mode", "enum": [ "SEARCH", "DIRECT_URLS", "REVIEWS_ONLY", "QUESTIONS_ONLY" ], "type": "string", "description": "Select what the scraper should do", "default": "SEARCH" }, "queries": { "title": "Search queries", "type": "array", "description": "Keywords used in SEARCH mode", "items": { "type": "string" } }, "urls": { "title": "Product URLs", "type": "array", "description": "Sephora product URLs (used in DIRECT_URLS and REVIEWS_ONLY modes)", "items": { "type": "string" } }, "maxItems": { "title": "Max items", "type": "integer", "description": "Maximum number of results to return", "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 } } } } } } } } } } ```