# Fragrancenet Product Search Scraper (`stealth_mode/fragrancenet-product-search-scraper`) Actor Scrape FragranceNet product listings with precision. Collect SKU, pricing, ratings, inventory status, images, and 21+ fields per product — perfect for price monitoring, fragrance aggregators, and competitive intelligence in the beauty e-commerce space. - **URL**: https://apify.com/stealth\_mode/fragrancenet-product-search-scraper.md - **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community) - **Categories:** Automation, Developer tools, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## FragranceNet Product Scraper: Extract Perfume Data at Scale --- ### What Is FragranceNet? FragranceNet.com is a leading online fragrance retailer offering thousands of perfumes, colognes, and beauty products from premium designers worldwide. It features dynamic product catalogs with variants by size, gender, and formula type. Extracting and monitoring this data manually is inefficient — the **FragranceNet Product Scraper** automates collection, delivering structured, ready-to-analyze product information instantly. --- ### Overview The **FragranceNet Product Scraper** harvests detailed fragrance product listings from search result pages, transforming browsable content into machine-readable records. It is designed for: - **Price monitoring services** tracking competitor pricing and discounts - **Fragrance aggregators** building comprehensive product databases - **E-commerce analysts** benchmarking inventory and trending products - **Retailers** conducting competitive intelligence and market research Key features include configurable scraping limits per page, resilient error handling via `ignore_url_failures`, and extraction of 21+ product fields including pricing, availability, images, and customer ratings. --- ### Input Format The scraper accepts a JSON configuration object specifying target URLs and collection parameters: ```json { "urls": [ "https://www.fragrancenet.com/fn/fragrances?page=2" ], "ignore_url_failures": true, "max_items_per_url": 200 } ```` | Parameter | Type | Description | |---|---|---| | `urls` | Array | FragranceNet product search pages to scrape. Supports paginated category URLs (e.g., `?page=1`, `?page=2`). Paste URLs individually or in bulk. | | `max_items_per_url` | Integer | Maximum products extracted per URL (e.g., `200`). Limits data volume and run time. Default: `20`. | | `ignore_url_failures` | Boolean | If `true`, the scraper continues even if some URLs fail. If `false`, a single failure halts the entire run. Recommended: `true` for large batches. | > **Best practice:** Start with `max_items_per_url: 50` to test, then increase for production runs. Use pagination parameters to target specific product categories or seasons. *** ### Output Format **Example output record:** ```json { "sku": "139842", "status": "200", "designer_url": "/fragrances/calvin-klein", "section": "f", "brand": "Euphoria", "promoted": false, "is_sellable": true, "sizes_available": 7, "rating": { "count": 533, "score": 4.797 }, "out_of_stock": false, "zoomable": 2, "is_low_inventory": false, "is_top_seller": false, "gender": "women", "image_variants": "legacy,legacy_png,zoomable,bottle", "variant_type": "size", "retina_image_url": "//cdn.fragrancenet.com/images/photos/250x250/139842.jpg", "percent_saving": 34, "description": "Eau De Parfum", "designer": "Calvin Klein", "gender_text": "women", "is_trending": false, "product_path": "perfume/calvin-klein/euphoria/eau-de-parfum", "image_url": "//cdn.fragrancenet.com/images/photos/121x121/139842.jpg", "price": "5.99", "from_url": "https://www.fragrancenet.com/fn/fragrances?page=2" } ``` Each product record contains 21+ fields covering identification, pricing, availability, images, and metadata: #### Product Identification | Field | Description | |---|---| | `SKU` | Unique stock-keeping unit for inventory tracking | | `Brand` | Fragrance brand/designer name (e.g., "Calvin Klein", "Dior") | | `Designer` | Brand owner or fragrance house (formal identifier) | | `Designer URL` | Direct link to the brand's profile on FragranceNet | | `Product Path` | Internal URL path to the product detail page | | `Status` | Current product status (active, discontinued, etc.) | #### Pricing & Discounts | Field | Description | |---|---| | `Price` | Current sale price in USD | | `Percent Saving` | Discount percentage off original retail price (e.g., `35%` for savings) | #### Availability & Inventory | Field | Description | |---|---| | `Is Sellable` | Boolean flag: `true` if product can be purchased, `false` if unavailable | | `Out Of Stock` | Boolean flag: `true` if no inventory remains | | `Is Low Inventory` | Boolean flag: `true` if stock is running low (limited supply warning) | | `Sizes Available` | Array of available container sizes (e.g., `["1.7 oz", "3.4 oz", "5.0 oz"]`) | #### Product Details | Field | Description | |---|---| | `Section` | Product category (e.g., "Men's Fragrances", "Women's Fragrances", "Unisex") | | `Gender` | Intended gender (code: `M`, `F`, `U` for unisex) | | `Gender Text` | Human-readable gender category (e.g., "For Men", "For Women", "Unisex") | | `Description` | Full product description including fragrance notes and key features | | `Variant Type` | Type of variation (e.g., concentration level: "Eau de Toilette", "Eau de Parfum") | #### Customer Signals & Popularity | Field | Description | |---|---| | `Rating` | Average customer rating (numeric scale, e.g., `4.5` out of 5) | | `Is Top Seller` | Boolean: `true` if the product ranks in bestseller lists | | `Is Trending` | Boolean: `true` if the product is currently trending on the platform | | `Promoted` | Boolean: `true` if the product has paid promotion or featured placement | #### Visual Assets | Field | Description | |---|---| | `Image URL` | Primary product image URL for listings and catalogs | | `Retina Image URL` | High-resolution image URL for detail pages (optimal for zoom) | | `Image Variants` | Array of available product images (e.g., bottle from multiple angles) | | `Zoomable` | Boolean: `true` if the product image supports zoom-in functionality | *** ### How to Use 1. **Identify target pages** — Visit FragranceNet.com and navigate to product search pages (e.g., "Women's Fragrances", "Designer Fragrances"). Copy the full URL including pagination parameters. 2. **Configure URLs** — Paste search page URLs into the `urls` array. You can target multiple pages, categories, or filtered searches. 3. **Set collection limits** — Adjust `max_items_per_url` based on your needs: - `50` for quick tests - `100–150` for moderate datasets - `200+` for comprehensive product catalogs 4. **Enable error tolerance** — Keep `ignore_url_failures: true` to handle temporary site issues or page load failures gracefully. 5. **Run and export** — Start the scraper, monitor the log, and download results as JSON, CSV, or Excel. **Common scenarios:** - **Price monitoring:** Scrape the same pages weekly to track price changes and apply `Percent Saving` for trend analysis. - **Inventory tracking:** Use `Out Of Stock` and `Is Low Inventory` fields to identify product availability shifts. - **Trending analysis:** Filter products by `Is Trending` and `Rating` to discover emerging fragrances. *** ### Use Cases & Business Value - **Price intelligence platforms:** Monitor FragranceNet's competitive pricing for margin analysis - **Fragrance recommendation engines:** Build datasets enriched with ratings, reviews, and product metadata - **E-commerce dropshipping:** Sync product data (prices, images, descriptions) into your own storefront - **Market research:** Analyze fragrance trends by gender, season, or designer popularity - **Retail analytics:** Track best-sellers and trending products to inform purchasing decisions By automating product data collection, the scraper eliminates manual updates and enables real-time competitive insights across thousands of fragrances. *** ### Conclusion The **FragranceNet Product Scraper** is an essential tool for beauty e-commerce professionals, price monitors, and market analysts. With 21+ fields per product and flexible pagination support, it transforms FragranceNet search results into structured data ready for analysis, integration, and business intelligence. Start scraping today and unlock actionable insights from one of the web's largest fragrance catalogs. # Actor input Schema ## `urls` (type: `array`): Add the URLs of the product search list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list. ## `ignore_url_failures` (type: `boolean`): If true, the scraper will continue running even if some URLs fail to be scraped. ## `max_items_per_url` (type: `integer`): The maximum number of items to scrape per URL. ## Actor input object example ```json { "urls": [ "https://www.fragrancenet.com/fn/fragrances?page=2" ], "ignore_url_failures": true, "max_items_per_url": 20 } ``` # 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 = { "urls": [ "https://www.fragrancenet.com/fn/fragrances?page=2" ], "ignore_url_failures": true, "max_items_per_url": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("stealth_mode/fragrancenet-product-search-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 = { "urls": ["https://www.fragrancenet.com/fn/fragrances?page=2"], "ignore_url_failures": True, "max_items_per_url": 20, } # Run the Actor and wait for it to finish run = client.actor("stealth_mode/fragrancenet-product-search-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 '{ "urls": [ "https://www.fragrancenet.com/fn/fragrances?page=2" ], "ignore_url_failures": true, "max_items_per_url": 20 }' | apify call stealth_mode/fragrancenet-product-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=stealth_mode/fragrancenet-product-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Fragrancenet Product Search Scraper", "description": "Scrape FragranceNet product listings with precision. Collect SKU, pricing, ratings, inventory status, images, and 21+ fields per product — perfect for price monitoring, fragrance aggregators, and competitive intelligence in the beauty e-commerce space.", "version": "0.0", "x-build-id": "oCuLKoteYJRFXCtwr" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/stealth_mode~fragrancenet-product-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-stealth_mode-fragrancenet-product-search-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/stealth_mode~fragrancenet-product-search-scraper/runs": { "post": { "operationId": "runs-sync-stealth_mode-fragrancenet-product-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/stealth_mode~fragrancenet-product-search-scraper/run-sync": { "post": { "operationId": "run-sync-stealth_mode-fragrancenet-product-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "urls": { "title": "URLs of the product search list urls to scrape", "type": "array", "description": "Add the URLs of the product search list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.", "items": { "type": "string" } }, "ignore_url_failures": { "title": "Continue running even if some URLs fail to be scraped", "type": "boolean", "description": "If true, the scraper will continue running even if some URLs fail to be scraped." }, "max_items_per_url": { "title": "Max items per URL", "type": "integer", "description": "The maximum number of items to scrape per URL." } } }, "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 } } } } } } } } } } ```