# The 1916 Company / WatchBox Pre-Owned Watch Listings Scraper (`jungle_synthesizer/the-1916-company-watchbox-preowned-watch-listings-scraper`) Actor Scrape pre-owned luxury watch listings from The 1916 Company (formerly WatchBox), the largest US CPO watch dealer. Extracts price, brand, model, reference number, condition, year, and box/papers status for every pre-owned and Rolex Certified Pre-Owned listing. Powered by the XML product sitemap. - **URL**: https://apify.com/jungle\_synthesizer/the-1916-company-watchbox-preowned-watch-listings-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## The 1916 Company / WatchBox Pre-Owned Watch Listings Scraper Scrapes pre-owned luxury watch listings from [The 1916 Company](https://www.the1916company.com/) (formerly WatchBox + Govberg + Radcliffe) — the largest certified pre-owned luxury watch dealer in the United States. Delivers a complete inventory snapshot with pricing, condition, and spec-table details for every pre-owned and Rolex Certified Pre-Owned listing. ### What You Get Each record includes: | Field | Description | |-------|-------------| | `product_url` | Canonical listing URL | | `sku` | Internal product ID | | `name` | Full product name | | `brand` | Watch brand (Rolex, Patek Philippe, TUDOR, H. Moser, Oris, etc.) | | `model` | Model family | | `reference_number` | Manufacturer reference number | | `price_usd` | Listed price in USD | | `currency` | Always USD | | `availability` | InStock or OutOfStock | | `condition` | Pre-Owned / Rolex Certified Pre-Owned | | `description` | Full product description | | `image_url` | Primary product image (watchbox-cdn.imgix.net) | | `image_urls` | All gallery image URLs | | `year` | Production year (where listed) | | `box_papers` | Box and papers status (e.g. "Box: Yes, Papers: Yes") | | `lastmod` | Sitemap lastmod timestamp (price/availability freshness signal) | | `scraped_at` | ISO timestamp of when this record was scraped | ### How It Works The actor walks The 1916 Company's XML product sitemaps (`sitemap-products-1.xml` through `sitemap-products-N.xml`), which contain the full product URL set with per-URL `` freshness timestamps and primary `` thumbnails. It filters to pre-owned paths (`/pre-owned/` and `/rolex-certified-pre-owned/`) and crawls each detail page to extract: - **JSON-LD `@type:Product`** — name, brand, model, SKU, price, currency, availability, condition, description, and primary image - **PDPSpecs spec table** — year, box/papers status, and reference number for standard pre-owned listings - **RlxCpoSpecs spec table** — reference number for Rolex Certified Pre-Owned listings No JavaScript rendering or proxy is required — all pages are server-side rendered. ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `maxItems` | Integer | Yes | Maximum number of listings to return (default: 10) | ### Sample Output ```json { "product_url": "https://www.the1916company.com/pre-owned/tudor/pelagos/pelagos-25717n-0001/", "sku": "5046635", "name": "TUDOR Pelagos", "brand": "TUDOR", "model": "Pelagos", "reference_number": "25717N-0001", "price_usd": 4250, "currency": "USD", "availability": "InStock", "condition": "Pre-Owned", "description": "Pre-Owned Tudor Pelagos FXD (25717N) self - winding automatic watch...", "image_url": "https://watchbox-cdn.imgix.net/posted-product-images/...", "image_urls": ["https://watchbox-cdn.imgix.net/posted-product-images/..."], "year": "2023", "box_papers": "Box: Yes, Papers: Yes", "lastmod": "2026-05-28T13:14:34-05:00", "scraped_at": "2026-05-28T18:46:00.000Z" } ```` ### Use Cases - **Watch arbitrage** — Compare 1916 CPO pricing against Chrono24 resale and Jomashop grey-market listings to identify flip opportunities - **Price intelligence** — Track pricing trends for specific references across the CPO market - **Inventory monitoring** — Monitor availability changes using the `lastmod` freshness signal and `availability` field - **Brand research** — Survey the full pre-owned inventory for a specific brand or model family ### Notes - Covers the full pre-owned and Rolex Certified Pre-Owned inventory (approximately 5,000–10,000 active listings across multiple sitemap shards) - The `lastmod` timestamp from the XML sitemap reflects when the listing was last updated (price change, availability change, or new listing) - The Rolex Certified Pre-Owned section uses a different page layout — year and box/papers are embedded in the description rather than the spec table - New (non-pre-owned) Rolex and brand-new watch pages are excluded; the actor targets only pre-owned inventory paths # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of records to scrape ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10 } ``` # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/the-1916-company-watchbox-preowned-watch-listings-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/the-1916-company-watchbox-preowned-watch-listings-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10 }' | apify call jungle_synthesizer/the-1916-company-watchbox-preowned-watch-listings-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/the-1916-company-watchbox-preowned-watch-listings-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "The 1916 Company / WatchBox Pre-Owned Watch Listings Scraper", "description": "Scrape pre-owned luxury watch listings from The 1916 Company (formerly WatchBox), the largest US CPO watch dealer. Extracts price, brand, model, reference number, condition, year, and box/papers status for every pre-owned and Rolex Certified Pre-Owned listing. Powered by the XML product sitemap.", "version": "0.1", "x-build-id": "ALQY3BpCsn51chtev" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~the-1916-company-watchbox-preowned-watch-listings-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-the-1916-company-watchbox-preowned-watch-listings-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/jungle_synthesizer~the-1916-company-watchbox-preowned-watch-listings-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-the-1916-company-watchbox-preowned-watch-listings-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/jungle_synthesizer~the-1916-company-watchbox-preowned-watch-listings-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-the-1916-company-watchbox-preowned-watch-listings-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": [ "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of records to scrape" } } }, "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 } } } } } } } } } } ```