# Sephora Reviews Scraper (`shahidirfan/sephora-reviews-scraper`) Actor Scrape Sephora reviews & ratings to analyze product sentiment, track competitor feedback, and drive beauty e-commerce decisions. Collect detailed customer reviews, ratings, and metadata for market intelligence. - **URL**: https://apify.com/shahidirfan/sephora-reviews-scraper.md - **Developed by:** [Shahid Irfan](https://apify.com/shahidirfan) (community) - **Categories:** E-commerce, AI, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 Reviews Scraper Extract customer reviews for any Sephora product at scale. Provide a product URL or product ID and collect detailed review data including ratings, reviewer profiles, helpfulness votes, verified purchaser status, and customer photos. Perfect for sentiment analysis, product research, and competitive intelligence. ### Features - **Any Product URL** — Paste any Sephora product page URL and reviews are collected automatically - **Product ID Support** — Alternatively supply just the product ID (e.g. `P449116`) - **Full Review Detail** — Captures rating, review title, full text, reviewer name, and submission date - **Reviewer Profiles** — Collects skin type, skin tone, eye color, and hair color when available - **Verified Purchaser Flag** — Identifies reviews from confirmed buyers - **Helpfulness Votes** — Captures positive and negative helpfulness counts per review - **Review Photos** — Extracts URLs of customer-uploaded photos - **Flexible Sorting** — Sort by newest, oldest, most helpful, highest or lowest rated - **Pagination Support** — Automatically pages through all available reviews - **Configurable Limits** — Control exactly how many reviews to collect - **Proxy Ready** — Built-in proxy configuration support for reliable large-scale runs --- ### Use Cases #### Sentiment Analysis Aggregate hundreds of verified customer reviews to understand how shoppers feel about a product. Identify recurring praise or complaints and map them to specific product attributes like scent, longevity, or packaging. #### Competitor Benchmarking Compare review volume, average ratings, and reviewer feedback across competing products in the same category. Understand what drives high ratings and where competitors fall short. #### Product Research & Sourcing Evaluate product quality before sourcing decisions by analysing authentic customer experiences, skin type fit, and repurchase intent signals hidden in review text. #### Brand Monitoring Track review velocity and sentiment over time for your own brand's products on Sephora. Detect sudden drops in rating that may signal quality or fulfilment issues. #### Market Research Reports Build rich datasets of consumer opinions for cosmetics and fragrance market research reports, academic studies, or investor presentations. --- ### Input Parameters | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `productUrl` | String | Recommended | — | Full Sephora product URL (product ID extracted automatically) | | `productId` | String | Optional | — | Sephora product ID (e.g. `P449116`). Used if no URL provided | | `results_wanted` | Integer | No | `20` | Maximum number of reviews to collect | | `max_pages` | Integer | No | `10` | Safety cap on the number of review pages fetched | | `sort` | String | No | `SubmissionTime:desc` | Sort order for reviews | | `proxyConfiguration` | Object | No | disabled | Proxy settings for reliable scraping | #### Sort Options | Value | Description | |-------|-------------| | `SubmissionTime:desc` | Newest reviews first (default) | | `SubmissionTime:asc` | Oldest reviews first | | `Helpfulness:desc` | Most helpful reviews first | | `Rating:desc` | Highest rated first | | `Rating:asc` | Lowest rated first | --- ### Output Data Each item in the dataset contains one review with the following fields: | Field | Type | Description | |-------|------|-------------| | `review_id` | String | Unique review identifier | | `product_id` | String | Sephora product ID | | `product_title` | String | Product name | | `product_url` | String | Link to the product page | | `reviewer_name` | String | Reviewer username or nickname | | `rating` | Number | Star rating out of 5 | | `title` | String | Review headline | | `review_text` | String | Full review body | | `is_recommended` | Boolean | Whether reviewer recommends the product | | `submission_time` | String | ISO datetime of submission | | `helpful_votes` | Number | Positive helpfulness votes | | `not_helpful_votes` | Number | Negative helpfulness votes | | `total_feedback` | Number | Total helpfulness votes | | `verified_purchaser` | Boolean | Confirmed buyer flag | | `skin_type` | String | Reviewer's skin type (if provided) | | `skin_tone` | String | Reviewer's skin tone (if provided) | | `eye_color` | String | Reviewer's eye color (if provided) | | `hair_color` | String | Reviewer's hair color (if provided) | | `rating_details` | Object | Secondary attribute ratings (longevity, value, etc.) | | `review_photos` | Array | URLs of customer review photos | | `scraped_at` | String | ISO timestamp when scraped | > Fields with no value from the source are omitted from the output — no null-filled rows in your dataset. --- ### Usage Examples #### Scrape Reviews for a Product by URL Paste any Sephora product URL and collect the 20 most recent reviews: ```json { "productUrl": "https://www.sephora.com/product/born-in-roma-P449116?skuId=2249696", "results_wanted": 20, "sort": "SubmissionTime:desc" } ```` #### Collect All Reviews for a Product by ID Supply a product ID and collect up to 500 reviews sorted by helpfulness: ```json { "productId": "P449116", "results_wanted": 500, "max_pages": 20, "sort": "Helpfulness:desc" } ``` #### Large-Scale Run with Proxies Collect all available reviews with residential proxy rotation for maximum reliability: ```json { "productUrl": "https://www.sephora.com/product/fragrance-name-P123456", "results_wanted": 1000, "max_pages": 50, "sort": "SubmissionTime:desc", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ``` #### Lowest Rated Reviews First Collect 1-star and 2-star reviews for quality monitoring: ```json { "productUrl": "https://www.sephora.com/product/born-in-roma-P449116", "results_wanted": 100, "sort": "Rating:asc" } ``` *** ### Sample Output ```json { "review_id": "237891234", "product_id": "P449116", "product_title": "Donna Born In Roma Eau de Parfum", "product_url": "https://www.sephora.com/product/born-in-roma-P449116?skuId=2249696", "reviewer_name": "FragranceLover88", "rating": 5, "title": "My absolute signature scent", "review_text": "I have been wearing this for two years and always get compliments. The longevity is incredible — 8+ hours on my skin. Worth every penny.", "is_recommended": true, "submission_time": "2025-11-14T18:32:00.000+00:00", "helpful_votes": 47, "not_helpful_votes": 2, "total_feedback": 49, "verified_purchaser": true, "skin_type": "Combination", "skin_tone": "Light", "rating_details": { "Longevity": 5, "Value": 4 }, "scraped_at": "2026-05-21T08:45:00.000Z" } ``` *** ### Tips for Best Results #### Use the Full Product URL Pasting the complete Sephora product URL (including `skuId`) is the easiest and most reliable way to start — the product ID is extracted automatically. #### Start with a Small Test Run Set `results_wanted` to `20` for an initial run to confirm data quality before scaling up to hundreds of reviews. #### Use Proxies for Large Runs For collections over 200 reviews, enabling **Apify Residential Proxies** in the proxy configuration significantly improves reliability and reduces the chance of rate limiting. #### Sort by Helpfulness for Quality Insights Use `Helpfulness:desc` to surface the most informative, community-validated reviews — ideal for product research reports. #### Monitor Review Velocity Schedule the actor to run weekly with `sort: SubmissionTime:desc` and `results_wanted: 50` to track new feedback trends over time without re-collecting old reviews. *** ### Integrations Connect your review data with: - **Google Sheets** — Export CSV for instant pivot table analysis - **Airtable** — Build a searchable, filterable review database - **Slack** — Get notified when new negative reviews appear via webhook - **Make (Integromat)** — Automate sentiment reporting pipelines - **Zapier** — Trigger alerts or CRM updates from new review data - **OpenAI / LLMs** — Feed review text into AI models for summarisation and theme extraction #### Export Formats - **JSON** — For developers and API integrations - **CSV** — For spreadsheet tools (Excel, Google Sheets) - **XML** — For system-to-system data exchange - **Excel** — Ready-made business reports *** ### Frequently Asked Questions #### Which Sephora website does this support? This actor supports the US Sephora website (sephora.com). Product reviews are powered by the BazaarVoice platform used by Sephora. #### How do I find the product URL? Navigate to any Sephora product page in your browser and copy the URL from the address bar. Example: `https://www.sephora.com/product/born-in-roma-P449116` #### How many reviews can I collect? You can collect all publicly available reviews for any product. Some products have thousands of reviews — use `max_pages` and `results_wanted` to cap the run size. #### What does the product ID look like? Sephora product IDs start with `P` followed by digits, for example `P449116`. They appear in every product URL. #### Are the reviews verified? The `verified_purchaser` field indicates whether the reviewer is confirmed to have purchased the product through Sephora. #### Can I scrape reviews for multiple products? To scrape multiple products, simply run the actor multiple times — once per product URL. You can use the Apify Scheduler or API to automate this across a list of product URLs. #### Why are some fields missing from a review? Fields like `skin_type`, `skin_tone`, and `rating_details` are only present when the reviewer provided that information. Missing fields are omitted from the output rather than set to null. #### How often is review data updated? Reviews are collected live from Sephora in real time each time the actor runs. There is no caching — every run fetches fresh data. *** ### Support For issues or feature requests, contact support through the Apify Console. #### Resources - [Apify Documentation](https://docs.apify.com/) - [API Reference](https://docs.apify.com/api/v2) - [Scheduling Runs](https://docs.apify.com/schedules) - [Apify Proxy](https://docs.apify.com/proxy) *** ### Legal Notice This actor is designed for legitimate data collection purposes. Users are responsible for ensuring their use complies with Sephora's Terms of Service, BazaarVoice's Terms of Service, and all applicable local and international laws. Collected data should be used responsibly and not redistributed without appropriate permissions. This tool does not bypass authentication and only accesses publicly visible review data. # Actor input Schema ## `productUrl` (type: `string`): Full Sephora product page URL (e.g. https://www.sephora.com/product/born-in-roma-P449116). The product ID is automatically extracted. ## `productId` (type: `string`): Sephora product ID (e.g. P449116). Used if no product URL is provided. ## `results_wanted` (type: `integer`): The maximum number of reviews to collect. Leave at 20 for a quick test. ## `max_pages` (type: `integer`): Safety cap on the number of review pages to fetch. ## `sort` (type: `string`): Sort reviews by submission time or helpfulness. ## `proxyConfiguration` (type: `object`): Proxy settings for reliable scraping. Residential proxies recommended. ## Actor input object example ```json { "productUrl": "https://www.sephora.com/product/born-in-roma-P449116?skuId=2249696", "results_wanted": 20, "max_pages": 10, "sort": "SubmissionTime:desc", "proxyConfiguration": { "useApifyProxy": false } } ``` # 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 = { "productUrl": "https://www.sephora.com/product/born-in-roma-P449116?skuId=2249696", "results_wanted": 20, "max_pages": 10, "sort": "SubmissionTime:desc" }; // Run the Actor and wait for it to finish const run = await client.actor("shahidirfan/sephora-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 = { "productUrl": "https://www.sephora.com/product/born-in-roma-P449116?skuId=2249696", "results_wanted": 20, "max_pages": 10, "sort": "SubmissionTime:desc", } # Run the Actor and wait for it to finish run = client.actor("shahidirfan/sephora-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 '{ "productUrl": "https://www.sephora.com/product/born-in-roma-P449116?skuId=2249696", "results_wanted": 20, "max_pages": 10, "sort": "SubmissionTime:desc" }' | apify call shahidirfan/sephora-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=shahidirfan/sephora-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Sephora Reviews Scraper", "description": "Scrape Sephora reviews & ratings to analyze product sentiment, track competitor feedback, and drive beauty e-commerce decisions. Collect detailed customer reviews, ratings, and metadata for market intelligence.", "version": "0.0", "x-build-id": "97BBqJeCdDrXfBpBz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/shahidirfan~sephora-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-shahidirfan-sephora-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/shahidirfan~sephora-reviews-scraper/runs": { "post": { "operationId": "runs-sync-shahidirfan-sephora-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/shahidirfan~sephora-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-shahidirfan-sephora-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", "properties": { "productUrl": { "title": "Product URL", "type": "string", "description": "Full Sephora product page URL (e.g. https://www.sephora.com/product/born-in-roma-P449116). The product ID is automatically extracted." }, "productId": { "title": "Product ID", "type": "string", "description": "Sephora product ID (e.g. P449116). Used if no product URL is provided." }, "results_wanted": { "title": "Maximum number of reviews", "minimum": 1, "type": "integer", "description": "The maximum number of reviews to collect. Leave at 20 for a quick test.", "default": 20 }, "max_pages": { "title": "Maximum number of pages", "minimum": 1, "type": "integer", "description": "Safety cap on the number of review pages to fetch.", "default": 10 }, "sort": { "title": "Sort order", "enum": [ "SubmissionTime:desc", "SubmissionTime:asc", "Helpfulness:desc", "Rating:desc", "Rating:asc" ], "type": "string", "description": "Sort reviews by submission time or helpfulness.", "default": "SubmissionTime:desc" }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Proxy settings for reliable scraping. Residential proxies recommended.", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```