# Hilton Honors Hotel Directory — Rates, Points & Brand Tiers (`jungle_synthesizer/hilton-honors-directory-rates-points-tier-scraper`) Actor Scrapes all ~7,500 Hilton properties across 24 brands from hilton.com. Captures brand tier, address, amenities, room counts, and a dynamic Honors points-rate snapshot across future dates to compute cents-per-point for award optimization. - **URL**: https://apify.com/jungle\_synthesizer/hilton-honors-directory-rates-points-tier-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Travel - **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 ## Hilton Honors Hotel Directory — Rates, Points & Brand Tiers Scrapes all ~7,500 Hilton properties across 24 brands from hilton.com. For each property, captures brand tier, address, coordinates, amenities, room counts, and a dynamic Honors points-rate snapshot for award-optimization analytics. ### What it does 1. **Discovers properties** via Hilton's English sitemap index — walks `sitemap-en-prop-*` child sitemaps to enumerate ~7,500 hotel URLs 2. **Extracts property metadata** from each hotel's info page: brand, tier, location, amenities, room/meeting counts, TripAdvisor ratings 3. **Captures dynamic points rates** across 3 snapshot dates (+30/+60/+90 days) and computes `cents_per_point` — the unit-economic metric for Hilton Honors award optimization ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `maxItems` | integer | 10 | Max properties to scrape (0 with brandCodes for all in that brand) | | `brandCodes` | array | — | Hilton brand code filter (e.g. `["HI","HP","DT"]`). Leave empty to scrape all brands. | | `snapshotDates` | array | auto | ISO check-in dates for rate snapshot. Defaults to +30/+60/+90 days from today. | #### Brand codes | Code | Brand | |------|-------| | WA | Waldorf Astoria Hotels & Resorts | | LX | LXR Hotels & Resorts | | CO | Conrad Hotels & Resorts | | PE | Canopy by Hilton | | SA | Signia by Hilton | | HI | Hilton Hotels & Resorts | | QQ | Curio Collection by Hilton | | DT | DoubleTree by Hilton | | ES | Embassy Suites by Hilton | | UP | Tempo by Hilton | | OU | Tapestry Collection by Hilton | | GI | Hilton Garden Inn | | PY | Graduate by Hilton | | HP | Hampton by Hilton | | TT | Tru by Hilton | | HH | Homewood Suites by Hilton | | HT | Home2 Suites by Hilton | | OL | Motto by Hilton | | GU | Hilton Grand Vacations | ### Output Each record includes: ```json { "hilton_ctyhocn": "NYCHITW", "brand_code": "HI", "brand_name": "Hilton Hotels & Resorts", "brand_tier": "upper_upscale", "property_name": "Hilton New York Times Square", "address_line": "234 W 42nd St", "city": "New York", "state_province": "NY", "country": "United States", "country_code": "US", "lat": 40.7564, "lng": -73.9886, "phone": "+1-212-840-5500", "total_rooms": 460, "has_spa": false, "has_pool": true, "has_executive_lounge": true, "tripadvisor_rating": 4.2, "tripadvisor_review_count": 8420, "lowest_points_rate": 35000, "highest_points_rate": 80000, "median_points_rate": 55000, "lowest_cash_rate_usd": 189.00, "median_cash_rate_usd": 245.00, "cents_per_point": 0.45, "free_night_certificate_eligible": true, "aspire_card_eligible": true, "amenities": "Fitness Center, Restaurant, Business Center, Pool", "hero_image_url": "https://www.hilton.com/...", "rate_snapshot_dates": "2026-06-25,2026-07-25,2026-08-24", "scraped_at": "2026-05-26T19:00:00.000Z" } ```` ### Use cases - **Points/miles optimization**: Track cents-per-point across all Hilton properties to find the best award redemptions - **Brand portfolio analysis**: Compare property density, amenity coverage, and average ratings across Hilton's 24 brands - **Corporate travel management**: Build property databases for TMC negotiations and policy compliance - **Market research**: Analyze Hilton's geographic footprint, brand tier distribution, and competitive positioning ### Notes - **Authentication**: Rate snapshot data (points rates, cash rates) requires Hilton to display pricing. Results may be null for properties where availability isn't shown without a logged-in session - **Dynamic pricing**: Hilton uses dynamic points pricing with no fixed award chart — snapshot values reflect availability at scrape time - **Proxy requirement**: Uses residential proxy to access Hilton's IP-restricted pages # 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 hotel properties to scrape (0 = all ~7,500) ## `brandCodes` (type: `array`): Limit to specific Hilton brand codes (e.g. \["WA","CO","HI","HP"]). Leave empty to scrape all brands. Brand codes: WA=Waldorf Astoria, LX=LXR, CO=Conrad, HI=Hilton, HP=Hampton, GI=Hilton Garden Inn, DT=DoubleTree, ES=Embassy Suites, HH=Homewood, HT=Home2, TT=Tru, QQ=Curio, OU=Tapestry, UP=Tempo, SA=Signia, ND=NoMad, PE=Canopy, PY=Graduate, OL=Motto, GU=Hilton Grand Vacations. ## `snapshotDates` (type: `array`): ISO-format check-in dates to sample for points/cash rates. Leave empty to use the default window: +30, +60, +90 days from today. ## 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, "brandCodes": [ "HI", "HP", "DT", "GI" ] } ``` # 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, "brandCodes": [ "HI", "HP", "DT", "GI" ] }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/hilton-honors-directory-rates-points-tier-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, "brandCodes": [ "HI", "HP", "DT", "GI", ], } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/hilton-honors-directory-rates-points-tier-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, "brandCodes": [ "HI", "HP", "DT", "GI" ] }' | apify call jungle_synthesizer/hilton-honors-directory-rates-points-tier-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/hilton-honors-directory-rates-points-tier-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hilton Honors Hotel Directory — Rates, Points & Brand Tiers", "description": "Scrapes all ~7,500 Hilton properties across 24 brands from hilton.com. Captures brand tier, address, amenities, room counts, and a dynamic Honors points-rate snapshot across future dates to compute cents-per-point for award optimization.", "version": "0.1", "x-build-id": "dJCL5PWMHt4TrVFxs" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~hilton-honors-directory-rates-points-tier-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-hilton-honors-directory-rates-points-tier-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~hilton-honors-directory-rates-points-tier-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-hilton-honors-directory-rates-points-tier-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~hilton-honors-directory-rates-points-tier-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-hilton-honors-directory-rates-points-tier-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": { "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 hotel properties to scrape (0 = all ~7,500)", "default": 10 }, "brandCodes": { "title": "Brand Filter (optional)", "type": "array", "description": "Limit to specific Hilton brand codes (e.g. [\"WA\",\"CO\",\"HI\",\"HP\"]). Leave empty to scrape all brands. Brand codes: WA=Waldorf Astoria, LX=LXR, CO=Conrad, HI=Hilton, HP=Hampton, GI=Hilton Garden Inn, DT=DoubleTree, ES=Embassy Suites, HH=Homewood, HT=Home2, TT=Tru, QQ=Curio, OU=Tapestry, UP=Tempo, SA=Signia, ND=NoMad, PE=Canopy, PY=Graduate, OL=Motto, GU=Hilton Grand Vacations.", "items": { "type": "string" } }, "snapshotDates": { "title": "Rate Snapshot Dates (optional)", "type": "array", "description": "ISO-format check-in dates to sample for points/cash rates. Leave empty to use the default window: +30, +60, +90 days from today.", "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 } } } } } } } } } } ```