[Blog](https://scrapfly.io/blog) / [python](https://scrapfly.io/blog/tag/python) / [How to Scrape Marriott Hotel Prices and Availability](https://scrapfly.io/blog/posts/how-to-scrape-marriott) # How to Scrape Marriott Hotel Prices and Availability by [Mohab Yousry](https://scrapfly.io/blog/author/mohab-yousry-9396552a) Aug 03, 2026 20 min read [\#python](https://scrapfly.io/blog/tag/python) [\#scrapeguide](https://scrapfly.io/blog/tag/scrapeguide) [ ](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fhow-to-scrape-marriott "Share on LinkedIn") [ ](https://x.com/intent/tweet?url=https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fhow-to-scrape-marriott&text=How%20to%20Scrape%20Marriott%20Hotel%20Prices%20and%20Availability "Share on X") [ ](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fhow-to-scrape-marriott "Share on Facebook") Summarize this article with [ ](https://chat.openai.com/?q=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fhow-to-scrape-marriott) [ ](https://claude.ai/new?q=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fhow-to-scrape-marriott) [ ](https://x.com/i/grok?text=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fhow-to-scrape-marriott) [ ](https://www.perplexity.ai/search/new?q=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fhow-to-scrape-marriott) [ ](https://www.google.com/search?udm=50&aep=11&q=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fhow-to-scrape-marriott) Send a plain request to marriott.com and you do not get hotel prices. You get a 403. Marriott runs Akamai Bot Manager, and the rate data you want is not even in the HTML. It loads as JSON after the page boots inside a Next.js application, so clearing the 403 is only half the job. By the end of this guide, you will be able to send a Marriott city or property search, clear Akamai, and pull structured nightly rates and room availability into a clean record. The path runs through Python and the [Scrapfly Web Scraping API](https://scrapfly.io/products/web-scraping-api) with Anti Scraping Protection enabled. [**Marriott Scraper**github.com/scrapfly/scrapfly-scrapers/tree/main/marriott-scraper](https://github.com/scrapfly/scrapfly-scrapers/tree/main/marriott-scraper) ## Key Takeaways - Marriott runs Akamai Bot Manager. A plain request returns HTTP 403 before you see any hotel rates. - Rate data does not live in the HTML. Marriott is a Next.js application backed by Apollo GraphQL, and prices load as JSON after the page boots. - The `findHotels.mi` search URL accepts destination, dates, and occupancy as query parameters, giving you a deterministic entry point without form automation. - The Web Scraping API with `asp=True`, `render_js=True`, and a US residential proxy clears Akamai and returns a rendered page in one call. - Rates and per-hotel detail come from two separate Apollo GraphQL calls, not one. `wait_for_selector="xhr:..."` captures the search call. The property-detail call is safelisted and needs a signature harvested from the page's own `__NEXT_DATA__`, not guessed by hand. - Datacenter IPs are rejected by Akamai on Marriott. Residential proxies are required, not optional. - Set `country="US"` to get USD rates. Record that value alongside a timestamp on every result when doing geo-specific comparisons. **Get web scraping tips in your inbox**Trusted by 100K+ developers and 30K+ enterprises. Unsubscribe anytime. ## Why Scrape Marriott Hotel Prices and Availability? You scrape Marriott directly when you need the chain's own published rates, not OTA aggregations. Marriott's site exposes nightly prices, room availability, rate types, and property level details for any destination and date combination you search. The most common use cases are: - **Rate monitoring and price drop alerts.** A developer who built a Marriott rate-drop alerting tool explained on [r/marriott](https://www.reddit.com/r/marriott/comments/1rfnpsw/built_a_tool_to_track_marriott_prices_and_alert/) why he scrapes: "Since we book direct, I can't use OTA APIs to pull rates, so I have to rely on scraping public data." Marriott does not publish a rate-drop notification of its own. - **Competitive rate intelligence.** Travel agencies, revenue management teams, and rate-parity auditors need the Marriott direct rate for a given city and date at scale, without manually checking each property. - **Travel app enrichment.** Search tools, rebooking assistants, and cost estimators need live Marriott rates as an input. - **Availability tracking.** Knowing a property is sold out on a given date, or that last-minute inventory has opened up, is useful on its own even without a price attached. This guide covers public nightly rates and room availability only. Bonvoy points, award inventory, and loyalty flows are out of scope. For OTA-style scraping across many hotel brands, see [How to Scrape Booking.com (2026 Update)Tutorial on how to scrape booking.com hotel and pricing data using Python. How to avoid blocking to web scrape data at scale and other tips.](https://scrapfly.io/blog/posts/how-to-scrape-bookingcom) Marriott's published rates are public information visible to visitors without logging in. Scrape at a reasonable rate, target only public endpoints, and avoid account, booking, and personal data. ## Why Does Marriott Block Scrapers? (Akamai Bot Manager) Marriott runs [Akamai Bot Manager](https://scrapfly.io/bypass/akamai), which returns HTTP 403 from its edge layer (`AkamaiGHost`) before the page delivers any content. Every blocking pattern a developer hits on Marriott traces back to one of four causes: - **403 on the first request.** Akamai scores TLS fingerprint, headers, and IP reputation before the page renders, and a script-like profile gets "Pardon Our Interruption" immediately. - **Datacenter IPs are rejected outright.** In testing, a datacenter proxy returned 403 consistently while residential plus ASP cleared the page. Residential is not optional here. - **Missing browser telemetry fails validation.** Akamai expects a follow-up request with fingerprint and behavioral signals; skip it and sessions die with a 403 or 418, as one [r/webscraping](https://www.reddit.com/r/webscraping/comments/1qofvmx/akamai_antibot_blocking_flight_search_scraping/) developer described on a similar travel site. - **Rates are not in the first response anyway.** Even past Akamai, prices load as JSON after the app boots. Clearing the wall is necessary but not sufficient. Marriott updates its protections regularly, so the durable answer is a managed bypass that maintains itself rather than a header set you tune by hand. For the full Akamai mechanism (TLS fingerprinting, IP reputation, JS telemetry), the guide below covers every layer. [How to Bypass Akamai when Web Scraping in 2026In this article we'll take a look at a popular anti bot service Akamai Bot Manager. How does it detect web scrapers and bots and what can we do to prevent our scrapers from being detected?](https://scrapfly.io/blog/posts/how-to-bypass-akamai-anti-scraping) ## Project Setup for Scraping Marriott The minimum setup is Python, a Scrapfly account with an API key, and the Scrapfly SDK. If you are not on Python, the SDK is also available in TypeScript, Go, and Rust, and there is a Scrapy extension for teams already running a Scrapy pipeline. Any of those can follow the same approach. Install the SDK: bash```bash pip install scrapfly-sdk ``` Three settings make Marriott work: - `asp=True` enables Anti Scraping Protection, which handles Akamai's fingerprint and telemetry checks without you maintaining any of that logic. - `render_js=True` boots a real browser to execute Marriott's JavaScript so rate data actually loads. - `country="US"` pins the residential proxy to a US exit node, satisfying Akamai's geography checks and returning USD pricing. Without all three, requests will fail at some point in the chain. python```python from scrapfly import ScrapflyClient, ScrapeConfig client = ScrapflyClient(key="YOUR_API_KEY") config = ScrapeConfig( url="https://www.marriott.com/search/findHotels.mi", asp=True, render_js=True, country="US", proxy_pool="public_residential_pool", ) result = client.scrape(config) print(result.scrape_result["status"]) ``` This config shape is what every Marriott request in this guide uses. The search and parsing sections build on it by targeting the correct URL with verified parameters and extraction logic. For full SDK install options and authentication details, see the [Scrapfly Python SDK docs](https://scrapfly.io/docs/sdk/python) and the [Web Scraping API getting started guide](https://scrapfly.io/docs/scrape-api/getting-started). With setup done, the next step is figuring out what URL to point the scraper at. ## How to Find Marriott Hotels and Rates to Scrape Marriott rates come from a search, not a fixed list of hotel URLs. Destination, dates, and occupancy are exposed directly as query parameters in the search results URL, so you can construct it from your inputs and request it directly, no search form needed. ### Marriott Search Inputs: Destination, Dates, and Occupancy Every Marriott search needs four inputs in the URL. Omit any of them and you get either an empty result set or Marriott's default location view. Currency is not a URL parameter, it follows the proxy country. | Input | Example value | Why it matters | |---|---|---| | Destination | `New York, NY` | Determines which property set Marriott searches | | Check-in date | `2026-08-10` | Changes both availability and rate. Always explicit. | | Check-out date | `2026-08-13` | Defines the stay length. Rates vary by length of stay. | | Occupancy | `2 adults, 1 room` | Affects room type availability and pricing tiers. | | Currency (via proxy) | `country="US"` → `USD` | Set on the ScrapeConfig, not in the URL. Controls which rate is returned. | Occupancy and dates are not cosmetic. Marriott's rate engine treats a two-night stay differently from a five-night stay, and a single adult differently from two adults in the same room. Set them explicitly in every request, or your results will not be comparable across runs. Pick one consistent sample search for development and keep it fixed across all test requests in your project. Any change in results then points to the site, not to varying inputs. ### The Marriott Search URL and Availability Calendar Marriott's search results live at the `findHotels.mi` path under `www.marriott.com/search/`. The URL accepts destination, dates, and occupancy as query parameters, which means you build the URL from your inputs and pass it directly to the Web Scraping API. There is no form to fill in and no JavaScript interaction required to reach the search results page. Marriott also exposes a date-range availability calendar view for individual properties. That view shows lowest available rates per night across a multi-week window and is useful when your goal is date flexibility rather than a fixed check-in. Record the destination, dates, occupancy, country, currency, and a timestamp with every result you save. Without those fields, comparing two results across time or across regions is not reliable. ## Scraping Marriott Search Results with the Web Scraping API The main scraping workflow sends the `findHotels.mi` search URL through the Web Scraping API with `asp=True`, `render_js=True`, and a residential proxy, then waits for the specific background call that actually carries the rates. The flow runs in four steps: 1. Build the search URL from your destination, dates, and occupancy inputs. 2. Send it through the Web Scraping API using the ASP config from setup, with `wait_for_selector` set to the name of the GraphQL call Marriott's app fires for a dated search, not a DOM selector. 3. Pull the matching entry out of the response's captured XHR calls and parse its JSON body. 4. Feed that JSON into `parse_search()` (shown in Marriott Rate and Availability Fields to Extract below) to flatten each property into a clean record. Step 2 is where most scrapers fail on Marriott: clearing Akamai and catching a background request both take real work to replicate by hand. ASP handles the first; `wait_for_selector` with an `xhr:` prefix handles the second, holding the response until the matching call completes and exposing it in `browser_data`. python```python import json from datetime import datetime from urllib.parse import urlencode from scrapfly import ScrapeConfig, ScrapflyClient SCRAPFLY = ScrapflyClient(key="YOUR_API_KEY") BASE_CONFIG = { "asp": True, "render_js": True, "country": "US", "proxy_pool": "public_residential_pool", } _SEARCH_XHR = "phoenixShopDatedSearchByDestinationQuery" def build_search_url(city: str, from_date: str, to_date: str, num_rooms: int = 1, num_adults: int = 2) -> str: def fmt(d): return datetime.strptime(d, "%Y-%m-%d").strftime("%m/%d/%Y") return "https://www.marriott.com/search/findHotels.mi?" + urlencode({ "searchType": "InCity", "destinationAddress.destination": city, "fromDate": fmt(from_date), "toDate": fmt(to_date), "numberOfRooms": num_rooms, "numAdultsPerRoom": num_adults, }) async def scrape_search(city: str, from_date: str, to_date: str) -> dict: url = build_search_url(city, from_date, to_date) response = await SCRAPFLY.async_scrape( ScrapeConfig(url, **BASE_CONFIG, wait_for_selector=f"xhr:{_SEARCH_XHR}") ) xhr_calls = response.scrape_result.get("browser_data", {}).get("xhr_call", []) call = next((c for c in xhr_calls if _SEARCH_XHR in c.get("url", "")), None) if not call: raise RuntimeError(f"XHR call for '{_SEARCH_XHR}' not found") return json.loads(call["response"]["body"]) ``` `findHotels.mi` takes `searchType`, `destinationAddress.destination`, `fromDate`, `toDate` (as `MM/DD/YYYY`), `numberOfRooms`, and `numAdultsPerRoom` as query parameters, which is what `build_search_url` assembles. Marriott's Next.js app fires a background GraphQL request named `phoenixShopDatedSearchByDestinationQuery` to actually load the property list and lead prices. `wait_for_selector=f"xhr:{_SEARCH_XHR}"` holds the response until that call resolves, so you get its JSON body instead of racing the page. For a description of the Web Scraping API's broader capabilities beyond Akamai, see the [getting started docs](https://scrapfly.io/docs/scrape-api/getting-started). The search request gets you the rendered property list with a lead price per property. The next step is pulling structured records, and the fuller per-hotel detail, from the data these calls loaded. Scrapfly #### Scale your web scraping effortlessly Scrapfly handles proxies, browsers, and anti-bot bypass — so you can focus on data. [Try Free →](https://scrapfly.io/register)## Parsing Marriott Hotel Prices and Availability ### Where Marriott Rate Data Lives (Internal JSON, Not Static HTML) Marriott's prices are not in the HTML. The page is a Next.js app backed by Apollo GraphQL, and two separate calls load the data: - `phoenixShopDatedSearchByDestinationQuery` returns the property list and lead price. - `phoenixShopHQVPropertyInfoCall` returns per-property detail such as address, phone, check-in/out, policies, and airports. The detail call is safelisted. It needs a `graphql-operation-signature` header matching one Marriott issues, so a guessed value fails. The maintained scraper harvests it from the `operationSignatures` list in a rendered search page's `__NEXT_DATA__` payload. python```python import json import re _HQV_OP = "phoenixShopHQVPropertyInfoCall" _OPERATION_SIGNATURES = {} def parse_operation_signatures(html: str) -> dict: match = re.search(r'', html) if not match: return {} data = json.loads(match.group(1)) signatures = (data.get("props", {}).get("pageProps", {}) or {}).get("operationSignatures") or [] return {s["operationName"]: s["signature"] for s in signatures if s.get("operationName") and s.get("signature")} ``` Run this against any rendered search response and `_OPERATION_SIGNATURES[_HQV_OP]` gives you the header value the detail call needs. Pass it in `graphql-operation-signature` alongside `graphql-require-safelisting: true` on a direct POST to the HQV endpoint. No browser rendering is needed once you hold a valid signature. The payoff: once you have a rendered page, the cleanest data is the JSON Marriott's own application already loaded (or a signature it already issued), not text scraped from DOM elements or a query you invented yourself. For the general technique of locating and extracting JSON embedded in a rendered page, the guide below explains the method across multiple real-world site patterns. [How to Scrape Hidden Web DataThe visible HTML doesn't always represent the whole dataset available on the page. In this article, we'll be taking a look at scraping of hidden web data. What is it and how can we scrape it using Python?](https://scrapfly.io/blog/posts/how-to-scrape-hidden-web-data) ### Marriott Rate and Availability Fields to Extract The two calls produce two record shapes, and the maintained [marriott-scraper](https://github.com/scrapfly/scrapfly-scrapers/tree/main/marriott-scraper) parses each into its own structure. `parse_search()` walks the `edges` list from the dated-search JSON captured in `scrape_search()` and flattens each property node into a record, converting the lowest rate's integer amount and decimal point into a plain price string along the way: python```python def parse_search(data: dict) -> list[dict]: edges = data["data"]["search"]["lowestAvailableRates"]["searchByDestination"]["edges"] results = [] for edge in edges: node, prop = edge["node"], edge["node"]["property"] basic, reviews, rates = prop.get("basicInformation") or {}, prop.get("reviews") or {}, node.get("rates") or [] descriptions = basic.get("descriptions") or [] media = ((prop.get("media") or {}).get("primaryImage") or {}).get("edges") or [] thumbnail = (media[0]["node"].get("imageUrls") or {}).get("wideHorizontal") if media else None amount = (rates[0]["rateModes"]["lowestAverageRate"].get("amount") or {}) if rates else {} lead_price = ( f"{amount['amount'] / (10 ** amount.get('decimalPoint', 2)):.2f}" if amount.get("amount") is not None else None ) results.append({ "marriott_id": prop["id"], "name": basic.get("name"), "url": f"https://www.marriott.com/en-us/hotels/{prop['seoNickname']}/overview/", "brand": (basic.get("brand") or {}).get("name"), "latitude": basic.get("latitude"), "longitude": basic.get("longitude"), "distance_meters": node.get("distance"), "description": descriptions[0].get("text") if descriptions else None, "review_rating": (reviews.get("stars") or {}).get("count"), "review_count": (reviews.get("numberOfReviews") or {}).get("count"), "thumbnail": thumbnail, "bookable": basic.get("bookable"), "currency": basic.get("currency"), "lead_price": lead_price, }) return results ``` This is a trimmed version of the function in the scraper's [marriott.py](https://github.com/scrapfly/scrapfly-scrapers/blob/main/marriott-scraper/marriott.py). The full version also normalizes protocol-relative image URLs and prefers the marketing-caption description when one is tagged. Run it against the JSON from `scrape_search()` and each edge becomes a record like this: json```json { "marriott_id": "NYCMD", "name": "Courtyard by Marriott New York Manhattan/Times Square", "url": "https://www.marriott.com/en-us/hotels/nycmd-courtyard-new-york-manhattan-times-square/overview/", "brand": "Courtyard", "latitude": 40.75352, "longitude": -73.98625, "distance_meters": 445.5174, "description": "Find inspiration at our Times Square hotel in Manhattan", "review_rating": 4, "review_count": 1917, "thumbnail": "https://cache.marriott.com/content/dam/marriott-renditions/NYCMD/nycmd-view-0043-hor-wide.jpg", "bookable": true, "currency": "USD", "lead_price": "626.42" } ``` The detail call, run per property ID against the property IDs from your search results, fills in the fields the search response does not carry: json```json { "marriott_id": "NYCMD", "name": "Courtyard by Marriott New York Manhattan/Times Square", "address": "114 West 40th Street", "city": "New York", "state": "NY", "postal_code": "10018", "country": "US", "phone": "+1 212 391 0088", "check_in": "15:00", "check_out": "12:00", "smoke_free": true, "pets_allowed": true, "pets_policy": "Pets welcome with USD 100 non-refundable cleaning fee per stay", "parking": ["Valet parking, fee: 75.00 USD daily", "Off-site parking, fee: 50.00 USD daily"], "airports": [ {"id": "LGA", "name": "LaGuardia Airport (LGA)", "distance": "8.8 mi SW", "url": "https://www.laguardiaairport.com/", "complimentary_shuttle": false} ] } ``` Availability lives in `bookable`: a property with no sellable room for your dates comes back `false` with no `lead_price`, which is how you detect a sell-out without a separate request. For rate monitoring, `lead_price`, `currency`, and `bookable` from the search call are usually enough on their own. Reach for the detail call only when you need address, phone, or policy fields to enrich a result. ## Web Scraping API vs Cloud Browser for Marriott: Which Should You Use? Use the Web Scraping API for the search URL and rate pulls. Use Cloud Browser when you need to drive an interactive multi-step flow, such as clicking through a date picker or stepping through a property's availability calendar page by page. If the data is reachable from the `findHotels.mi` query-param URL, the Web Scraping API with ASP is simpler and cheaper. If you need to click through dates, choose room types, or navigate a multi-step availability flow, Cloud Browser gives you a real stealth browser over CDP to drive with Playwright. | | Web Scraping API | Cloud Browser | |---|---|---| | **Best for** | Search URL rate pulls and property list extraction | Interactive date-search flows and multi-step availability browsing | | **How it works** | Single API call with `asp=True` and `render_js=True`; returns rendered HTML | Managed stealth browser session over CDP; you drive it with Playwright | | **Akamai handling** | Built into ASP | Built into the Cloud Browser session | | **When to reach for it** | Marriott exposes a query-param search URL, so this covers most rate-pull jobs | When you need to pick dates on a calendar widget or navigate availability in steps | | **Complexity** | Low. One config object, one call. | Higher. Requires Playwright code for each page interaction. | Some Marriott data, like the calendar view, is only reachable after a multi-step interaction the query param URL cannot drive. In our Air France guide you will find a similar case: Air France has no stable results URL, so Cloud Browser is the only path there. Marriott is more accessible, but Cloud Browser covers the cases where the search URL falls short. [How to Scrape Air France Flights with Python in 2026Scrape Air France round-trip flight offers with Python and the Scrapfly Cloud Browser API: walk the booking widget, capture the GraphQL booking response, and return structured records with price, times, layovers, aircraft, seats, and CO2.](https://scrapfly.io/blog/posts/how-to-scrape-air-france-flights) For Cloud Browser setup, authentication, and Playwright integration, see the [Cloud Browser getting started docs](https://scrapfly.io/docs/cloud-browser-api/getting-started) and the [Playwright integration guide](https://scrapfly.io/docs/cloud-browser-api/playwright). With the tool choice clear, the next section covers what to do when Marriott's Akamai wall pushes back at scale. ## How to Bypass Marriott Blocking at Scale At scale, Marriott's blocking shows up as a few specific symptoms. Address each one specifically rather than changing everything at once: ### Residential Proxies and Geo-Targeted Marriott Rates Residential proxies are required, not optional. In testing, a datacenter proxy returned 403 even with correct headers, while the same request through residential with ASP cleared the page, consistent with Scrapfly's general guidance for Akamai-protected targets. The `country` parameter also controls locale and currency. A US proxy returns USD, a UK proxy returns GBP. For multi-region research, run separate requests per country and record the country code on every result. Without it, cross-region comparisons are meaningless. | Symptom | Likely cause | Fix | |---|---|---| | 403 on first request | Datacenter IP or ASP not enabled | Set `asp=True` and use `proxy_pool="public_residential_pool"` | | Empty result set | Wrong destination encoding or locale mismatch | Verify destination param and match `country` to the search locale | | Wrong currency in results | Proxy country does not match requested currency | Set `country` to the target market and record it on each result | | Session works once then fails | Session reuse without continuity or aggressive rotation | Use Scrapfly sessions for continuity or start a fresh session per search | ### Handling 403s, Retries, and Session Continuity When a 403 comes back: - Check that `asp=True` is set and the proxy is residential. If both are correct, a retry with a fresh session resolves most cases. - If 403s start appearing after a period of working scrapes, Marriott has likely tightened its Akamai rules. A managed bypass updates itself to match: if you are maintaining headers manually, you will need to reverse-engineer the change and update your code every time Marriott deploys. Scrapfly reports 97% success on Akamai-protected targets, a number based on real traffic through its residential network and verified on the [Akamai bypass page](https://scrapfly.io/bypass/akamai). ## FAQ Is there a Marriott API for prices and availability?Marriott does not offer a public rate API for general use; third-party hotel-data APIs (such as the Amadeus Hotel Search API or other aggregators) cover some inventory, but scraping marriott.com directly is the way to get the chain's own published rates when API coverage, fields, or freshness do not fit. Can BeautifulSoup alone scrape Marriott prices?No. Marriott's rates load as JSON in a JavaScript app after the page boots, so BeautifulSoup on the initial HTML returns no prices; you need JS rendering (and to clear Akamai) first, then parse the JSON. Is it legal to scrape Marriott hotel prices?US courts have treated scraping publicly visible data as distinct from accessing private or account-gated data: in hiQ Labs v. LinkedIn (9th Circuit, 2022) the court found that scraping public data likely does not violate the Computer Fraud and Abuse Act, though breaching a site's terms of service can still create separate liability. Legality depends on jurisdiction and the site's terms; this guide covers public rate data only and excludes login, booking, and personal data. See the disclaimer below. Does this approach work for other hotel chains like Hilton or Hyatt?The same pattern (ASP plus residential to clear anti-bot, then parse the internal JSON) transfers to other hotel chains such as Hilton, Hyatt, or Choice Hotels, but each site has its own search inputs, data shape, and anti-bot behavior, so selectors and field paths differ. ### Web Scraping API Scrape any website with our powerful API. Anti-bot bypass, JavaScript rendering, and rotating proxies built-in. [Try Web Scraping API](https://scrapfly.io/docs/scrape-api/getting-started) ## Conclusion Scraping Marriott is two problems in sequence: Akamai's 403 blocks you first, then the rates that were never in the HTML load as JSON after the app boots. Solve both and you have structured rates and availability for any city, property, and date range. The workflow: build the search URL, send it through the Web Scraping API with ASP, a residential proxy, and `render_js=True`, capture the search XHR, and parse it into records. The maintained [marriott-scraper](https://github.com/scrapfly/scrapfly-scrapers/tree/main/marriott-scraper) runs this end to end, including the safelisted detail call, if you want working code to start from. For production use, the [Scrapfly Web Scraping API](https://scrapfly.io/products/web-scraping-api) is the reliable path through Akamai. This guide covers public rate and availability data only. Exclude account, booking, payment, and personal data from any collection you run. Legal Disclaimer and PrecautionsThis tutorial covers popular web scraping techniques for education. Interacting with public servers requires diligence and respect: - Do not scrape at rates that could damage the website. - Do not scrape data that's not available publicly. - Do not store PII of EU citizens protected by GDPR. - Do not repurpose *entire* public datasets which can be illegal in some countries. Scrapfly does not offer legal advice but these are good general rules to follow. For more you should consult a lawyer. [ Add as a preferred source ](https://google.com/preferences/source?q=scrapfly.io) Table of Contents Table of Contents- [Key Takeaways](#key-takeaways) - [Why Scrape Marriott Hotel Prices and Availability?](#why-scrape-marriott-hotel-prices-and-availability) - [Why Does Marriott Block Scrapers? (Akamai Bot Manager)](#why-does-marriott-block-scrapers-akamai-bot-manager) - [Project Setup for Scraping Marriott](#project-setup-for-scraping-marriott) - [How to Find Marriott Hotels and Rates to Scrape](#how-to-find-marriott-hotels-and-rates-to-scrape) - [Marriott Search Inputs: Destination, Dates, and Occupancy](#marriott-search-inputs-destination-dates-and-occupancy) - [The Marriott Search URL and Availability Calendar](#the-marriott-search-url-and-availability-calendar) - [Scraping Marriott Search Results with the Web Scraping API](#scraping-marriott-search-results-with-the-web-scraping-api) - [Parsing Marriott Hotel Prices and Availability](#parsing-marriott-hotel-prices-and-availability) - [Where Marriott Rate Data Lives (Internal JSON, Not Static HTML)](#where-marriott-rate-data-lives-internal-json-not-static-html) - [Marriott Rate and Availability Fields to Extract](#marriott-rate-and-availability-fields-to-extract) - [Web Scraping API vs Cloud Browser for Marriott: Which Should You Use?](#web-scraping-api-vs-cloud-browser-for-marriott-which-should-you-use) - [How to Bypass Marriott Blocking at Scale](#how-to-bypass-marriott-blocking-at-scale) - [Residential Proxies and Geo-Targeted Marriott Rates](#residential-proxies-and-geo-targeted-marriott-rates) - [Handling 403s, Retries, and Session Continuity](#handling-403s-retries-and-session-continuity) - [FAQ](#faq) - [Conclusion](#conclusion) Join the Newsletter Get monthly web scraping insights Scale Your Web Scraping Anti-bot bypass, browser rendering, and rotating proxies, all in one API. Start with 1,000 free credits. No credit card required 1,000 free API credits Anti-bot bypass included [Start Free](https://scrapfly.io/register) [View Docs](https://scrapfly.io/docs/onboarding) Not ready? Get our newsletter instead. ## Related Articles [ ### How to Bypass Akamai when Web Scraping in 2026 In this article we'll take a look at a popular anti bot service Akamai Bot Manager. How does it detect web scrapers and ... ](https://scrapfly.io/blog/posts/how-to-bypass-akamai-anti-scraping) [ blocking ### How to Bypass Imperva Incapsula when Web Scraping in 2026 In this article we'll take a look at a popular anti bot service Imperva Incapsula anti bot WAF. How does it detect web s... ](https://scrapfly.io/blog/posts/how-to-bypass-imperva-incapsula-anti-scraping) [ python blocking ### How to Bypass Anti-Bot Protection in 2026: All 8 Major Vendors Identify and bypass Cloudflare, DataDome, PerimeterX, Kasada, Akamai, Incapsula, F5, and AWS WAF with Python code exampl... ](https://scrapfly.io/blog/posts/how-to-bypass-anti-bot-protection) Scale your web scraping effortlessly, **1,000 free credits** [Start Free](https://scrapfly.io/register)