OpenTable Email Scraper

OpenTable Email Scraper

The OpenTable Email Scraper collects publicly indexed contact emails connected to opentable.com and opentable.co.uk, the reservation network that most established US and UK restaurants list on. It builds Google queries with the site: operator against both domains, fetches them through the Apify GOOGLE_SERP proxy, and extracts emails from the result blocks. No login, no browser, no OpenTable API — only what Google has already published in its index.

Start with the measured part. In a live test run, roughly 10 parsed results produced 5 rows with a usable venue identity, 5 resolvable profile URLs and 4 unique emails. That is a moderate, middle-of-the-pack profile: cleaner venue identity than review-driven platforms, lower raw email density than the highest-yield Actors in this family.

The upside is that when the OpenTable Email Scraper does return a row, it usually comes with a real restaurant name and a working reservation URL. Restaurants list on OpenTable precisely to be contacted for bookings, private dining and events — so the addresses in the index are business inboxes by design.

What one run of the OpenTable Email Scraper produces

Each dataset row is one unique email plus whatever venue context Google printed around it. You get the raw title, an account label, a cleaned snippet, the exact query used and a truncation flag. The OpenTable Email Scraper pushes rows to the Apify dataset as they are found, so you can export CSV, JSON or Excel mid-run.

Exporting and integrating the OpenTable Email Scraper dataset

Because rows are written incrementally, an aborted or migrated run still leaves a usable dataset behind. Export from the Apify console, pull the dataset over the API, or schedule the OpenTable Email Scraper and push results straight into your CRM.

How the OpenTable Email Scraper works: SERP parsing, not an API

The OpenTable Email Scraper runs the same six steps on every query it builds.

1. It reads your input: keywords, location, email domains and limits.
2. It builds Google queries with the site: operator, for example site:opentable.com OR site:opentable.co.uk "fine dining" "@gmail.com" events.
3. It fetches result pages through the Apify GOOGLE_SERP proxy using async aiohttp requests.
4. It parses each result block structurally — locating the <h3> and the smallest surrounding block — rather than by CSS class name.
5. It extracts emails with a domain-filtered regex and normalises obfuscated forms.
6. It deduplicates globally and pushes each lead to the dataset immediately.

Both OpenTable domains are searched in a single site: alternation, so a UK-focused run and a US-focused run read the same index from different country vantage points. There is no browser, no JavaScript rendering, no authentication and no cookies. The OpenTable Email Scraper never signs into OpenTable and never requests pages from OpenTable's own servers.

OpenTable Email Scraper features

Everything listed below is implemented in the OpenTable Email Scraper today.

Feature	What it means in practice
Query expansion	Base, quoted, intitle: and one variant per modifier; base queries run first
Dual-domain search	opentable.com and opentable.co.uk are covered by every query
Global deduplication	An email found by several queries is stored exactly once
Email normalisation	Understands name [at] domain [dot] com, name (at) domain, name @ domain, domain .com, zero-width characters and the full-width ＠
Junk filter	Rejects placeholders such as email@, yourname@, test@, xxx@ and single-character locals
Boundary-correct matching	@gmail.com will not match inside @gmail.company or @gmail.com.br
Soft-wrap repair	Drops a hit that is only the tail of another email in the same block
Structural parsing	Independent of Google's obfuscated CSS class names
Whole-page fallback	A markup change degrades to "emails without account details" rather than "no emails"
Block detection	CAPTCHA, "unusual traffic" and consent pages are detected and retried, not counted as empty
Retries	Up to 3 attempts per page with exponential backoff and a fresh proxy session per request
Failed-query requeue	Blocked or failed queries are re-queued once at the end of the run
Concurrency	An asyncio worker pool with a shared stop signal on maxEmails
Resumable state	Key-value store state keyed by an input hash; saves on PERSIST_STATE, MIGRATING and ABORTING
Run summary	Logs pages fetched, blocked pages, retries and emails per page

OpenTable Email Scraper input fields

These are the exact input fields the OpenTable Email Scraper accepts, with the defaults it ships with.

Field	Type	Default	Meaning
keywords	array (required)	["restaurant","fine dining"]	Search terms describing the venues you want
location	string	""	Optional location phrase added to every query
customDomains	array	["@gmail.com","@yahoo.com"]	Only emails on these domains are kept; @ optional
maxEmails	integer 1-10000	20	Stop after this many unique emails
countryCode	string	""	Two-letter country for the search proxy — US or GB here
expandQueries	boolean	true	Search each keyword x domain in several phrasings
queryModifiers	array	["email","contact","catering","reservations","owner"]	Extra words combined with each keyword when expansion is on
maxPagesPerQuery	integer 1-50	30	Page cap per query
maxConcurrency	integer 1-20	5	Parallel queries

Example OpenTable Email Scraper input

{
  "keywords": ["fine dining", "steakhouse", "private dining"],
  "location": "Chicago",
  "customDomains": ["@gmail.com", "@yahoo.com", "@outlook.com"],
  "maxEmails": 150,
  "countryCode": "US",
  "expandQueries": true,
  "queryModifiers": ["email", "contact", "events", "private dining", "owner"],
  "maxPagesPerQuery": 30,
  "maxConcurrency": 5
}

City-level prospecting with location

location is the highest-leverage field in the OpenTable Email Scraper for any territory-based sales team. It appends a quoted phrase to every query, so you get one dataset per market instead of one undifferentiated national file.

Strong values on this platform are the metros where OpenTable is densest: New York, Chicago, San Francisco, Los Angeles, Boston, Washington DC, London, Manchester, Edinburgh. Neighbourhood phrases work too — West Loop, Soho, Mayfair — when you want a walkable prospecting route rather than a metro-wide list.

Leave location empty for a first exploratory run to see what the index holds. Then narrow, and set countryCode to match: US with a US city, GB with a UK one.

Keyword suggestions for the OpenTable Email Scraper

The shipped defaults, restaurant and fine dining, are broad. Cuisine and service-format terms match a much larger slice of the index.

Keyword	Why it works on OpenTable
steakhouse	High-density, high-ticket category with events inboxes
italian restaurant	One of the largest cuisine cohorts on the platform
sushi	Dense in US metros and central London
brunch	Surfaces neighbourhood venues that fine-dining terms miss
private dining	Directly targets pages that publish an events address
tasting menu	Chef-led venues with a named contact
gastropub	Strong UK term when countryCode is GB
wine bar	Small independents that publish an owner inbox

Pair a format noun with an intent modifier — steakhouse events, private dining contact — rather than searching a bare noun.

OpenTable Email Scraper output fields

Every dataset item the OpenTable Email Scraper writes carries all fourteen of these fields.

Field	Meaning
network	Platform name
keyword	The keyword that produced the lead
query	The exact Google query used
title	Raw result title
accountName	Account label Google prints
fullName	Display name parsed from a profile-style title; empty for post captions
username	URL-safe handle when the platform exposes one; otherwise null
profileUrl	Canonical account URL when a handle is known; otherwise empty
url	Direct platform link when exposed, else the profile URL
description	Bio or snippet text, cleaned of labels and engagement counters
email	Lower-cased email address
emailDomain	The matched domain
possiblyTruncated	true when Google's snippet ellipsis touched the email
foundAt	ISO 8601 UTC timestamp

Example OpenTable Email Scraper output

[
  {
    "network": "OpenTable",
    "keyword": "steakhouse",
    "query": "site:opentable.com OR site:opentable.co.uk steakhouse \"@gmail.com\" events \"Chicago\"",
    "title": "Prime & Provisions - Chicago, IL | OpenTable",
    "accountName": "Prime & Provisions",
    "fullName": "Prime & Provisions - Chicago, IL",
    "username": "prime-and-provisions-chicago",
    "profileUrl": "https://www.opentable.com/r/prime-and-provisions-chicago",
    "url": "https://www.opentable.com/r/prime-and-provisions-chicago",
    "description": "Steakhouse - West Loop. Private dining and events: events.primeprov@gmail.com",
    "email": "events.primeprov@gmail.com",
    "emailDomain": "@gmail.com",
    "possiblyTruncated": false,
    "foundAt": "2026-08-31T11:21:07Z"
  },
  {
    "network": "OpenTable",
    "keyword": "gastropub",
    "query": "site:opentable.com OR site:opentable.co.uk gastropub \"@outlook.com\" contact \"London\"",
    "title": "The Anchor Tavern - London | OpenTable",
    "accountName": "The Anchor Tavern",
    "fullName": "The Anchor Tavern - London",
    "username": "the-anchor-tavern-london",
    "profileUrl": "https://www.opentable.com/r/the-anchor-tavern-london",
    "url": "https://www.opentable.co.uk/r/the-anchor-tavern-london",
    "description": "British gastropub in Southwark. Group bookings: anchortavern.bookings@outlook.com",
    "email": "anchortavern.bookings@outlook.com",
    "emailDomain": "@outlook.com",
    "possiblyTruncated": true,
    "foundAt": "2026-08-31T11:23:40Z"
  }
]

Note the profileUrl shape: OpenTable routes venue pages under /r/, so the canonical link the OpenTable Email Scraper builds is https://www.opentable.com/r/{venue-slug}. Note also that the second row's url points at the .co.uk domain Google actually indexed, while profileUrl is normalised to the canonical .com form.

What a measured OpenTable Email Scraper run looked like

Per roughly 10 parsed results in a live test: 5 rows with a usable identity, 5 resolvable profile URLs, 4 unique emails. About half of what Google returns for these queries resolves to a named venue, and the email density is moderate.

Practically, that means you should widen rather than deepen. More cuisine keywords, more modifiers and more cities will move your row count far more than raising maxPagesPerQuery.

Restaurant lead generation use cases for the OpenTable Email Scraper

Here is where the OpenTable Email Scraper fits into real B2B prospecting and market research workflows.

Use case	How to configure it
Reservation and table-management sales	keywords: ["fine dining","steakhouse"], one metro per run
POS and payments prospecting	Add owner and contact modifiers to reach decision-maker inboxes
Catering, events and private dining suppliers	keywords: ["private dining"] with an events modifier
Wine, spirits and beverage distribution	keywords: ["wine bar","tasting menu"] in high-ticket metros
Restaurant equipment and furniture	Target independents via gastropub and brunch
Hospitality recruitment	Use owner and contact; fine dining publishes named inboxes more often
UK territory building	countryCode: "GB", location: "London", keywords: ["gastropub","british restaurant"]
Local agency client acquisition	One neighbourhood per run; pitch photography, SEO or menu design
CRM enrichment	Match your existing venue list on profileUrl — it is stable and canonical
Competitive market mapping	Compare row counts per cuisine keyword across cities

Practical OpenTable Email Scraper recipes

US metro baseline. Cuisine keywords, countryCode: "US", one city in location, maxEmails: 150. This is the configuration most likely to return a clean, named dataset.

UK run. Same keywords plus gastropub and british restaurant, countryCode: "GB", location: "London". Run it separately from the US job so the country vantage point is not diluted.

Events-intent sweep. Replace the default modifiers with events, private dining, functions and enquiries. These are the pages most likely to publish a real address.

Widen before you deepen. Google caps a single query at roughly 300 results, so keyword breadth beats page depth. Raise maxPagesPerQuery last.

Pair for coverage. Run the Resy Email Scraper beside this one for upscale venues that skew to Resy, and the Tripadvisor Restaurants Email Scraper for venues that are not on any reservation network.

Responsible use, GDPR and CAN-SPAM

An email that identifies a natural person is personal data even when it was published publicly. Public availability is not consent to send. UK and EU recipients are covered by the GDPR and PECR; commercial email into the United States falls under CAN-SPAM.

Practical steps that keep an OpenTable Email Scraper workflow defensible:

• Prefer role addresses (info@, events@, reservations@) over addresses naming an individual.
• Keep provenance for every lead — the query, url and foundAt fields exist for exactly this.
• Give a clear sender identity, a stated purpose and a working opt-out in every message.
• Honour opt-outs immediately and check suppression lists before each follow-up.
• Delete data you are not actively using rather than warehousing scraped lists.
• Take advice before running UK B2B outreach at scale; PECR treats sole traders and partnerships as individuals.

This is operational guidance, not legal advice.

Related Actors

The OpenTable Email Scraper is one of 35 Actors in a Travel, Hospitality and Food family that all share this engine. For a fuller picture of one city, pair it with the Resy Email Scraper for upscale venues, the Toast Restaurant Email Scraper for online-ordering operators, and the Grubhub Email Scraper for delivery-first restaurants.

Actor	What it collects
OpenTable Email and Phone Number Scraper	Emails and phone numbers from OpenTable
OpenTable Phone Number Scraper	Public phone numbers from OpenTable
Airbnb Email Scraper	Public contact emails from Airbnb
Booking.com Email Scraper	Public contact emails from Booking.com
Caviar Email Scraper	Public contact emails from Caviar
ChowNow Email Scraper	Public contact emails from ChowNow
Contiki Email Scraper	Public contact emails from Contiki
Craigslist Email Scraper	Public contact emails from Craigslist
Delivery.com Email Scraper	Public contact emails from Delivery.com
DoorDash Email Scraper	Public contact emails from DoorDash
EatStreet Email Scraper	Public contact emails from EatStreet
G Adventures Email Scraper	Public contact emails from G Adventures
GetYourGuide Email Scraper	Public contact emails from GetYourGuide
Grubhub Email Scraper	Public contact emails from Grubhub
Hostelbookers Email Scraper	Public contact emails from Hostelworld
HotelsCombined Email Scraper	Public contact emails from HotelsCombined
Intrepid Travel Email Scraper	Public contact emails from Intrepid Travel
Just Eat Email Scraper	Public contact emails from Just Eat
Klook Email Scraper	Public contact emails from Klook
Resy Email Scraper	Public contact emails from Resy
TheFork Email Scraper	Public contact emails from TheFork
Toast Restaurant Email Scraper	Public contact emails from Toast
TourRadar Email Scraper	Public contact emails from TourRadar
Traveloka Email Scraper	Public contact emails from Traveloka
Tripadvisor Attractions Email Scraper	Public contact emails from Tripadvisor
Tripadvisor Hotels Email Scraper	Public contact emails from Tripadvisor
Tripadvisor Restaurants Email Scraper	Public contact emails from Tripadvisor
Uber Eats Email Scraper	Public contact emails from Uber Eats
Viator Email Scraper	Public contact emails from Viator
Wanderlog Email Scraper	Public contact emails from Wanderlog
Wego Email Scraper	Public contact emails from Wego
Zomato Email Scraper	Public contact emails from Zomato
Airbnb Email and Phone Number Scraper	Emails and phone numbers from Airbnb
Booking.com Email and Phone Number Scraper	Emails and phone numbers from Booking.com
Caviar Email and Phone Number Scraper	Emails and phone numbers from Caviar
ChowNow Email and Phone Number Scraper	Emails and phone numbers from ChowNow
Contiki Email and Phone Number Scraper	Emails and phone numbers from Contiki
Craigslist Email and Phone Number Scraper	Emails and phone numbers from Craigslist
Delivery.com Email and Phone Number Scraper	Emails and phone numbers from Delivery.com
DoorDash Email and Phone Number Scraper	Emails and phone numbers from DoorDash
EatStreet Email and Phone Number Scraper	Emails and phone numbers from EatStreet
G Adventures Email and Phone Number Scraper	Emails and phone numbers from G Adventures

OpenTable Email Scraper limitations

Read these before planning anything around OpenTable Email Scraper output.

• Moderate yield. In a live test, roughly 10 parsed results produced 5 identified venues, 5 profile URLs and 4 unique emails. Useful, but not the highest-volume Actor in this family.
• Publicly indexed emails only. The OpenTable Email Scraper finds addresses already visible in Google's index. Anything behind a reservation widget, a contact form or a login is unreachable.
• Google's ~300-result cap. A single query returns roughly 300 results at most, which is why expandQueries defaults to true and why keyword breadth matters more than page depth.
• possiblyTruncated. When true, Google's snippet ellipsis touched the email and it may be cut off. Verify before sending.
• username and profileUrl can be empty. They are populated only when Google's result exposes a resolvable /r/ venue path; roughly half of rows did in testing. That is a Google limitation, not a bug.
• Apify GOOGLE_SERP proxy required. The OpenTable Email Scraper cannot run without Apify proxy credentials.
• Free-plan cap. Free Apify plans stop at 100 emails per run. Paid plans are uncapped.
• No guaranteed volume. Results vary with keywords, domains, location and Google's index on the day.
• Not affiliated with OpenTable. This is an independent tool, not supported, endorsed by or connected to OpenTable.

OpenTable Email Scraper FAQ

Common questions about the OpenTable Email Scraper, its inputs and its output.

How many results should I expect from the OpenTable Email Scraper?

In a live test, roughly 10 parsed results produced 5 identified venues, 5 profile URLs and 4 unique emails — a moderate yield. Total volume depends on your keywords, domains, location and countryCode, and no row count is guaranteed.

Does the OpenTable Email Scraper log into OpenTable?

No. It never logs in, never calls an OpenTable API and never opens opentable.com in a browser. It reads Google results through the Apify GOOGLE_SERP proxy.

Does it cover the UK as well as the US?

Yes. Every query searches opentable.com and opentable.co.uk together. Set countryCode to GB for a UK-vantage run and US for an American one.

Which keywords work best?

Cuisine and service-format terms: steakhouse, italian restaurant, sushi, brunch, private dining, tasting menu, gastropub, wine bar. Pair them with events, contact or owner modifiers.

How do I use location for city-level prospecting?

Put a metro or neighbourhood in it — Chicago, London, West Loop, Mayfair — and run one job per territory. That turns a generic list into a route a rep can work.

Whose emails am I actually finding?

Business inboxes that restaurants publish for reservations, private dining and events enquiries. Treat them as business contacts, not consumer data.

Why is profileUrl an /r/ link?

Because OpenTable routes each venue under /r/{slug}. That is the canonical link shape the OpenTable Email Scraper builds from Google's breadcrumb, and it is stable enough to use as a CRM key.

Does the OpenTable Email Scraper verify deliverability?

No. It extracts and normalises what Google indexed. Check rows flagged possiblyTruncated before using them.

How do I get more rows?

Add cuisine keywords, add email domains such as @outlook.com and @hotmail.com, run more cities, and keep expandQueries on. Raising maxPagesPerQuery is the least effective lever.

Can I resume an interrupted run?

Yes. State lives in the key-value store keyed by a hash of your input, with saves on Apify's PERSIST_STATE, MIGRATING and ABORTING events.

What happens when Google blocks a request?

Block, CAPTCHA and consent pages are detected rather than treated as empty. Pages get up to three attempts with exponential backoff, and failed queries are re-queued once at the end of the run.

Is scraping OpenTable contact emails legal?

The OpenTable Email Scraper only reads publicly indexed Google results. Whether you may then contact those addresses is a separate GDPR, PECR and CAN-SPAM question. See the responsible use section and take your own legal advice.

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Support

Questions, a bug, or you need a custom build of the OpenTable Email Scraper? Contact neurodata.apify@gmail.com.