🍽️ OpenTable Scraper: Restaurants, Ratings & Reviews

🚀 Export OpenTable restaurant listings in seconds. Ratings, reviews, cuisine, hours, menus, prices, and exact coordinates for any city OpenTable indexes, ready to drop into your spreadsheet, BI tool, or AI pipeline.

OpenTable is the long-running reservations network that restaurant operators have used since the late 1990s, with active listings in cities from New York to Tokyo to Madrid. The structured data sitting behind each restaurant page is far richer than the booking widget you see on the front end: rating breakdowns by food, service, ambience, value, and noise, cuisine tags, dining style, hours of operation, price band, accepted payment methods, accessibility flags, neighborhood and metro, exact latitude and longitude, contact phone, and a recent reservation count. This Actor pulls all of it into clean JSON or CSV so you can analyze restaurants the way OpenTable's own analytics team does.

The Actor accepts plain-English search terms ("New York", "Greenwich Village italian", "Paris brunch") and walks the OpenTable search results page by page, enriching each restaurant with the full profile data fetched from its dedicated page. You can also pass direct restaurant URLs if you already have a target list. Output is the same flat record shape regardless of input mode, so it merges cleanly into existing datasets, and the run finishes whether the user is on a free preview or a paid plan up to a million items.

🎯 Target Audience	💡 Primary Use Cases
Restaurant operators, food critics, hospitality investors, marketing agencies, travel planners, data journalists, academic researchers, location analytics teams	Competitive analysis, market entry research, restaurant scoring and ranking, neighborhood food density studies, menu trend tracking, review monitoring, deal sourcing for hospitality M&A, dataset enrichment for travel apps

📋 What the OpenTable Scraper does

• 🔍 Searches OpenTable by city, neighborhood, or cuisine. Pass any term OpenTable's search bar accepts and the Actor paginates through every result page until your maxItems cap is hit.
• 💰 Filters by price band. Restrict the output to $, $$, $$$, or $$$$ tiers, alone or combined.
• 📊 Sorts by Featured or Distance. Match the order users actually see on the OpenTable site.
• 🍽️ Enriches each restaurant with its full profile. Hours, executive chef, dress code, parking, payment options, full address, public transit, and accessibility flags all pulled from the restaurant's detail page.
• 🔗 Accepts direct restaurant URLs. Drop in a list of /r/... or /restaurant/profile/... links and the Actor scrapes those directly without the search step.
• 📷 Captures every gallery photo. All restaurant photos available on OpenTable's CDN are returned as a deduplicated URL list.

Each record stands on its own with 48 named fields covering identification (restaurant ID, slug, OpenTable URL), commerce (price band, accepted payments, delivery partners, private dining flags), reputation (overall plus 5 sub-ratings, review count, recent reservation count, one recent review text), and geography (street address, neighborhood, metro, latitude, longitude, cross street, public transit). The output is the same shape whether you searched a city or fed a list of URLs.

💡 Why it matters: OpenTable is the booking layer that runs a meaningful share of dinner reservations in the English-speaking world. The data sitting behind it is the closest public proxy for actual restaurant traffic in many markets, and it includes detail you cannot get from a generic mapping service: granular sub-ratings, recent reservation counts, and the operator-curated cuisine tags and amenities.

📊 Data fields

Each record includes: additionalDetails, address, awards, crossStreet, cuisines, deliveryPartners, description, diningStyle, dressCode, executiveChef, features, hasDeliveryDirect, hasDeliveryPartners, hasPrivateDining, hasTakeout, hoursOfOperation, imageUrl, inPremiumMarketplace, latitude, longitude, metro, neighborhood, orderOnlineLink, parkingDetails, parkingInfo, paymentOptions, phoneNumber, photoUrls, priceRange, priceTier, primaryCuisine, publicTransit, rating, ratingAmbience, ratingFood, ratingNoise, ratingService, ratingValue, recentReservationCount, restaurantId. All 40 field names come from a real production run, so what you see here is what lands in your dataset.

⚠️ Good to Know: OpenTable serves slightly different result sets per region. Searches default to a US viewpoint. If you want France, Spain, or Japan results, include the country or city name explicitly in searchTerms (e.g. "Paris", "Tokyo Ginza"). The enrichWithProfile step adds roughly 1 second per restaurant.

🚀 How to use

1. ✅ Sign up for a free Apify account. Use this referral link to get started with $5 in free credit. Free accounts can preview 10 records per run.
2. 🍽️ Open the OpenTable Scraper. Find it on your dashboard or in the Apify Store.
3. 🛠️ Paste your input. A list of cities, neighborhoods, or direct restaurant URLs. Pick a price band if you want. Set maxItems.
4. ▶️ Click Start. The Actor walks search pages and enriches every record. Output appears in the dataset tab as records land.
5. 📥 Download CSV, Excel, JSON, or XML. Or stream the dataset into Make, Zapier, Airbyte, or your own webhook.

⏱️ Total time: under 2 minutes to first record, around 1 minute per 50 enriched records after that. A 1,000-restaurant pull typically completes in 20-25 minutes.

🔗 Recommended Actors

• ⭐ Yelp Reviews Scraper - restaurant and business reviews from Yelp with star ratings, reviewer profiles, and photo counts.
• 🗺️ Yellow Pages Scraper - business listings including phone, address, categories, and rating across any US city.
• 🏨 Hostelworld Scraper - hostel and budget accommodation listings for the same travel destinations your restaurant searches cover.
• 🍲 Allrecipes Scraper - recipe data to pair with restaurant cuisine analysis, covering ingredients, ratings, and nutrition.
• 👗 Depop Scraper - marketplace listings for second-hand goods, useful for lifestyle and consumer behavior datasets alongside dining data.

💡 Pro Tip: browse the complete ParseForge collection for more hospitality, travel, and review scrapers.

⚠️ Disclaimer: Independent tool, not affiliated with OpenTable. Only publicly available restaurant data is collected. Users are responsible for compliance with applicable laws and OpenTable's terms of use.

🆘 Need Help?

If you hit a bug, have questions about setup, or need a scraper we haven't built yet, open our contact form or write to parseforge@protonmail.com. We also take on paid custom data projects.

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