OpenTable Scraper — Restaurant Data, Reviews & Prices

OpenTable Scraper extracts restaurant data from OpenTable for restaurant market research, price monitoring, and lead generation. It collects restaurant profiles, menus, diner reviews, and reservation availability as structured JSON — no login, no token, no browser — from Apify's cloud, at under $0.2 per 1,000 restaurant profiles.

Main Use Cases

• Restaurant market research — track ratings, review counts, and price bands across cities, cuisines, and competitors.
• Restaurant price monitoring — watch price-band and menu prices over time for competitive intelligence or dining-app catalog enrichment.
• Restaurant ratings & reviews data — collect individual diner reviews with food/service/ambience/value ratings for sentiment analysis.
• Restaurant lead generation — build prospect lists (name, cuisine, address, coordinates, phone, photos) for marketing agencies and suppliers.
• Reservation availability monitoring — check real-time booking slots for a chosen date and party size, best-effort from cloud IPs.
• Restaurant database building — export a clean city/cuisine restaurant dataset (JSON, CSV, Excel) for dashboards or maps.

How It Works

The actor opens an anonymous web session against OpenTable's public GraphQL API — plain JSON over HTTPS, no browser rendering. It searches by location or cuisine, then scrapes each restaurant profile (typically 1–3 seconds per restaurant), and writes four dedicated datasets: restaurants, reviews, menus, and availability. No token to paste, nothing to refresh, works out of the box from Apify Cloud.

Extract Restaurant Listings for Market Research

Search restaurants by location, cuisine, or name (e.g. "new york", "italian san francisco", "nobu") and rank them by relevance. Each restaurant row includes:

• Name, profile URL, restaurant ID
• Primary cuisine, price band, dining style
• Rating and total review count
• Neighborhood, full address, latitude/longitude
• Photos, features (bar, counter, outdoor), awards

Build Restaurant Prospect Lists Without an Official API

OpenTable has no public API for third-party data access. This actor fills that gap: scrape up to 1,000 restaurants per run and export the dataset for lead generation, agency prospecting, or aggregator catalog enrichment — no API key, no developer account.

Collect Diner Reviews & Ratings Breakdowns

Enable includeReviews to collect individual reviews with full text and per-dimension ratings (food, service, ambience, value), noise level, reviewer name and metro, and dining/submission dates. Ideal for sentiment analysis and trust-signal reporting.

Monitor Restaurant Availability and Prices

Set dateTime and partySize to fetch real-time reservation availability slots. Combine with scheduled runs (daily or weekly) to detect price-band changes, menu-price updates, and booking demand shifts over time. Availability is best-effort from datacenter IPs; a Residential/Static proxy unlocks consistent results.

Input

Field	Type	Required	Default	Notes
searchTerm	string	optional	"new york"	Search query: location, cuisine, or restaurant name. Ignored when startUrls is set.
startUrls	array	optional	—	Direct profile URLs (https://www.opentable.com/r/...); scraped directly instead of searching.
maxRestaurants	integer	optional	50	Max restaurant profiles (1–1000).
maxReviewsPerRestaurant	integer	optional	10	Max individual reviews per restaurant (0–200).
includeAvailability	boolean	optional	true	Fetch real-time reservation slots.
includeReviews	boolean	optional	true	Include individual diner reviews.
includeMenus	boolean	optional	true	Include full menu data (may be blocked from datacenter IPs — see notes).
dateTime	string	optional	today 7 PM local	Reservation date/time, e.g. 2026-09-20T19:00:00.
partySize	integer	optional	2	Party size for availability lookups (1–20).

Output

Each run writes four dedicated datasets so row types never mix. All are downloadable as JSON, CSV, Excel, or HTML from the Storage tab, and exposed as API links in the Output tab.

Dataset	Row type	Example fields
Default dataset	restaurant	name, url, primaryCuisine, priceBand, rating, reviewCount, neighborhood, address, latitude, longitude, photos
reviews	review	reviewId, text, ratingOverall/Food/Service/Ambience/Value, noiseLevel, reviewerName, reviewerMetro, dinedDateTime
menus	menu item	menuTitle, sectionTitle, itemTitle, itemDescription, price, currency
availability	slot	dateTime, time, type, points, redemptionTier

Example Input

{
  "searchTerm": "italian new york",
  "maxRestaurants": 100,
  "maxReviewsPerRestaurant": 20,
  "includeReviews": true,
  "includeMenus": false,
  "includeAvailability": true,
  "partySize": 2,
  "dateTime": "2026-09-20T19:00:00"
}

Example Output — restaurant (default dataset)

{
  "_type": "restaurant",
  "restaurantId": 1191640,
  "name": "Ci Siamo",
  "url": "https://www.opentable.com/r/ci-siamo-new-york",
  "primaryCuisine": "Italian",
  "priceBand": "$50 and over",
  "rating": 4.7,
  "reviewCount": 585,
  "neighborhood": "Manhattan West",
  "address": { "line1": "440 W 33rd St", "city": "New York", "state": "NY", "postCode": "10001" },
  "diningStyle": "Casual Dining",
  "latitude": 40.7525,
  "longitude": -73.9989
}

Integrations & Automation

• API — every dataset has a permanent API URL; pull it into any pipeline or BI tool.
• Webhooks — trigger downstream jobs when a run finishes.
• Scheduling — run daily or weekly on Apify's cron scheduler for price/availability monitoring and recurring dataset refreshes.
• Zapier / Make — connect via Apify's official integrations for spreadsheet and CRM updates.
• Recommended recurring schedule: daily for availability monitoring, weekly for price-band and menu tracking.

Related Actors

• Restaurant Review Aggregator — TripAdvisor restaurant reviews at scale (the authoritative actor in the restaurant-reviews cluster).
• OpenTable Scraper by parseforge — alternative OpenTable profile extraction.
• RAG Web Browser — general web search + page fetch for market research context.

FAQ

Is there an OpenTable API? No public third-party API exists. This actor extracts the same restaurant data via OpenTable's public GraphQL endpoint — no login, no token, no developer account.

Can I scrape OpenTable without an API? Yes — that's exactly what this actor does. Run it from Apify Cloud and export the dataset as JSON, CSV, or Excel.

What's the best way to get restaurant reservations data? Set dateTime and partySize and enable includeAvailability. For monitoring, schedule daily runs and compare slot availability over time.

OpenTable vs TripAdvisor data for restaurant market research? OpenTable covers reservations-focused profiles (price bands, dining style, availability); TripAdvisor covers broader review volume. Many projects combine both — pair this actor with the Restaurant Review Aggregator.

How to track competitor restaurant prices? Use startUrls with your competitors' profile URLs, enable includeMenus, and schedule weekly runs to diff menu prices and price bands.

What are OpenTable scraper alternatives? Direct competitors include parseforge's OpenTable scraper and shahidirfan's scraper. This actor additionally covers reviews, menus, and availability in a single run at $0.2/1K profiles.

Why no token? The actor uses an anonymous web session against OpenTable's public GraphQL API — no account data is accessed.

Known limitations

• Menu, hours, phone, and website data come from server-side rendered pages that Akamai blocks from datacenter IPs; a clean Residential/Static proxy unlocks them. Set includeMenus: false for faster cloud runs.
• Availability slots may be intermittently blocked by Akamai rate limiting from datacenter IPs.
• Coverage is primarily US restaurants (databaseRegion: NA).

Competitive Positioning

Capability	Direct competitors	This actor
Price (per restaurant)	$0.02033 (parseforge), $0.00139 (shahidirfan)	$0.0002 (= $0.2 / 1K profiles, pay-per-event)
Datasets in one run	profiles only	restaurants + reviews + menus + availability
Token / login needed	varies	none
Max restaurants per run	varies	1,000
Store rating	as low as 1.83 (parseforge)	n/a (new actor, 2 users)

Verified from competitor Store pages and input schemas on 2026-09-14.

For AI Agents & LLM Apps

• Purpose: returns structured OpenTable restaurant data — profiles, reviews, menus, and reservation availability — from a search term or profile URLs.
• Minimal working input:

{ "searchTerm": "new york", "maxRestaurants": 50 }

• Variant inputs: direct URL scraping via startUrls; review-only via maxReviewsPerRestaurant + includeReviews: true + others false; availability lookup via dateTime + partySize + includeAvailability: true.
• Output fields (4 datasets): restaurants (name, url, primaryCuisine, priceBand, rating, reviewCount, address, latitude, longitude); reviews (reviewId, text, ratingOverall, ratingFood, ratingService, ratingAmbience, ratingValue, reviewerName); menus (itemTitle, sectionTitle, price, currency); availability (dateTime, time, type).
• Behaviors an agent should know:
  • startUrls takes priority over searchTerm when both are provided.
  • includeMenus: true costs extra requests and may 403 from datacenter IPs — disable for cloud runs unless a residential proxy is used.
  • includeAvailability and includeReviews each add billed events per restaurant — budget accordingly.
  • Max result cap: maxRestaurants (up to 1000); per-restaurant review cap: maxReviewsPerRestaurant (up to 200).
• Billing: pay-per-event — $0.00005/run start, $0.0002/restaurant profile, $0.0008/menu item, $0.0008/availability slot, $0.001/review.

Legal & Compliance Disclaimer

This actor is independent and not affiliated with, endorsed by, or sponsored by OpenTable, Inc. It accesses only publicly available restaurant data through OpenTable's public GraphQL endpoint — no login bypass, no CAPTCHA solving, no account data. You are responsible for complying with OpenTable's Terms of Service and applicable data-protection law (GDPR/CCPA where relevant). Do not resell or redistribute data in ways that violate those terms.

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