Resy Email Scraper

Resy Email Scraper

The Resy Email Scraper collects publicly indexed contact emails connected to resy.com, the reservation platform used by chef-driven and upscale American restaurants. It builds Google queries with the site:resy.com operator, fetches them through the Apify GOOGLE_SERP proxy, and extracts emails from the result blocks. No login, no browser, no Resy 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 9 rows with a usable venue identity, 9 resolvable profile URLs and 8 unique emails. That is one of the strongest profiles in this restaurant family, and it reflects how cleanly Resy's venue and city pages are indexed.

The audience matters as much as the numbers. Resy skews to tasting menus, wine programmes and independent groups — venues that publish an events or press inbox because private dining and collaborations are a real revenue line for them.

What one run of the Resy 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 Resy 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 Resy 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 Resy Email Scraper and push results straight into your CRM.

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

The Resy 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:resy.com "tasting menu" "@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.

There is no browser, no JavaScript rendering, no authentication and no cookies. The Resy Email Scraper never signs into Resy and never requests pages from Resy's own servers. Everything it returns was already public in Google's search index.

Resy Email Scraper features

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

Feature	What it means in practice
Query expansion	Base, quoted, intitle: and one variant per modifier; base queries run first
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

Resy Email Scraper input fields

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

Field	Type	Default	Meaning
keywords	array (required)	["restaurant","tasting menu"]	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 is the natural value
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 Resy Email Scraper input

{
  "keywords": ["tasting menu", "wine bar", "chef counter"],
  "location": "Brooklyn",
  "customDomains": ["@gmail.com", "@yahoo.com", "@outlook.com"],
  "maxEmails": 200,
  "countryCode": "US",
  "expandQueries": true,
  "queryModifiers": ["email", "contact", "events", "press", "owner"],
  "maxPagesPerQuery": 30,
  "maxConcurrency": 5
}

City-level prospecting with location

location is the most valuable input in the Resy Email Scraper, because Resy's own footprint is organised by city. It appends a quoted phrase to every query, so you can produce one dataset per market and hand each rep a territory rather than a national dump.

The metros where Resy is densest are the ones worth running first: New York, Brooklyn, Los Angeles, San Francisco, Chicago, Austin, Miami, Washington DC, Seattle. Neighbourhood values work well too — Williamsburg, Silver Lake, Wynwood — when you want a walkable list.

Leave location empty for a first exploratory run to see what the index holds, then narrow. Because Resy venues are already routed under a city segment, a location value and the resulting profileUrl usually agree, which makes territory tagging trivial.

Keyword suggestions for the Resy Email Scraper

The defaults, restaurant and tasting menu, are a good start. These terms match the parts of the index where upscale venues actually live.

Keyword	Why it works on Resy
chef counter	Omakase and counter-service formats concentrated on this platform
wine bar	Small independents that publish an owner or beverage-director inbox
omakase	High-ticket, reservation-only venues
natural wine	A strong Resy-specific cohort in NY, LA and Chicago
private dining	Directly targets pages that publish an events address
cocktail bar	Bar programmes with press and partnership inboxes
new american	A broad cuisine label used heavily on Resy listings
pop up	Residencies and temporary concepts run by contactable operators

Pair a format noun with an intent modifier — wine bar events, chef counter press — rather than searching a bare noun.

Resy Email Scraper output fields

Every dataset item the Resy 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 Resy Email Scraper output

[
  {
    "network": "Resy",
    "keyword": "tasting menu",
    "query": "site:resy.com \"tasting menu\" \"@gmail.com\" events \"Brooklyn\"",
    "title": "Oxalis - Brooklyn | Resy",
    "accountName": "Oxalis",
    "fullName": "Oxalis - Brooklyn",
    "username": "ny",
    "profileUrl": "https://resy.com/cities/ny",
    "url": "https://resy.com/cities/ny",
    "description": "Seasonal tasting menu in Prospect Heights. Events and buyouts: oxalis.events@gmail.com",
    "email": "oxalis.events@gmail.com",
    "emailDomain": "@gmail.com",
    "possiblyTruncated": false,
    "foundAt": "2026-08-31T12:04:11Z"
  },
  {
    "network": "Resy",
    "keyword": "wine bar",
    "query": "site:resy.com \"wine bar\" \"@outlook.com\" contact \"Brooklyn\"",
    "title": "Fromage Wine Room - Brooklyn | Resy",
    "accountName": "Fromage Wine Room",
    "fullName": "Fromage Wine Room - Brooklyn",
    "username": "ny",
    "profileUrl": "https://resy.com/cities/ny",
    "url": "https://resy.com/cities/ny",
    "description": "Natural wine and small plates. Press and partnerships: fromage.wineroom@outlook.com",
    "email": "fromage.wineroom@outlook.com",
    "emailDomain": "@outlook.com",
    "possiblyTruncated": true,
    "foundAt": "2026-08-31T12:06:29Z"
  }
]

Note the profileUrl shape carefully. Resy routes every venue under a city segment, so the canonical link the Resy Email Scraper can construct from Google's breadcrumb is https://resy.com/cities/{city} — a city page, not a per-venue page. The venue itself is identified by accountName and fullName, which is why the strong identity rate on this platform matters so much.

What a measured Resy Email Scraper run looked like

Per roughly 10 parsed results in a live test: 9 rows with a usable identity, 9 resolvable profile URLs, 8 unique emails. Nearly every row came back with a named venue attached to the address.

That is unusually clean for SERP-based contact discovery. It makes the Resy Email Scraper a good first choice when you need names, not just addresses, for an upscale US restaurant list.

Restaurant lead generation use cases for the Resy Email Scraper

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

Use case	How to configure it
Reservation and table-management sales	keywords: ["restaurant","tasting menu"], one metro per run
Premium POS and payments prospecting	Add the owner modifier; independents make fast decisions
Wine, spirits and beverage distribution	keywords: ["wine bar","natural wine","cocktail bar"]
Specialty food and produce supply	keywords: ["chef counter","tasting menu"] for ingredient-led kitchens
Private dining and events sourcing	queryModifiers: ["events","private dining","buyout"]
Tableware, glassware and uniform suppliers	Target omakase and new american for design-conscious venues
Hospitality PR and press outreach	Add a press modifier; Resy venues publish these inboxes
Chef and front-of-house recruitment	Use owner and contact for decision-maker inboxes
Local agency client acquisition	One neighbourhood per run; pitch photography, web or social work
CRM enrichment	Match on email, then use fullName to reconcile venue names

Practical Resy Email Scraper recipes

NYC baseline. location: "New York", countryCode: "US", upscale format keywords, maxEmails: 200. Resy's index is deepest here, so this is the run most likely to fill a dataset.

Events-intent sweep. Replace the default modifiers with events, private dining, buyout and press. These are the pages most likely to publish a monitored inbox.

Neighbourhood tour. Six runs, one neighbourhood each in location, identical keywords. Territory-tagged datasets are far easier for a field team to work than one merged file.

Widen before you deepen. Google caps a single query at roughly 300 results, so more format keywords beat more pages per query. Raise maxPagesPerQuery last.

Pair for coverage. Run the OpenTable Email Scraper beside this one — the two reservation networks overlap far less than you would expect — and add the Caviar Email Scraper for premium delivery partners in the same metros.

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. Commercial email into the United States falls under CAN-SPAM; if any recipient is in the EU or UK, the GDPR applies too.

Practical steps that keep a Resy Email Scraper workflow defensible:

• Prefer role addresses (info@, events@, press@) 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.
• Include a valid physical postal address in commercial email, as CAN-SPAM requires.
• Delete data you are not actively using rather than warehousing scraped lists.

This is operational guidance, not legal advice.

Related Actors

The Resy Email Scraper is one of 35 Actors in a Travel, Hospitality and Food family that all share this engine. For broader US coverage, pair it with the OpenTable Email Scraper and the Toast Restaurant Email Scraper; for Europe, use the TheFork Email Scraper.

Actor	What it collects
Resy Email and Phone Number Scraper	Emails and phone numbers from Resy
Resy Phone Number Scraper	Public phone numbers from Resy
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
OpenTable Email Scraper	Public contact emails from OpenTable
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

Resy Email Scraper limitations

Read these before planning anything around Resy Email Scraper output.

• Publicly indexed emails only. The Resy Email Scraper finds addresses already visible in Google's index. Anything behind a booking 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.
• profileUrl is a city page, not a venue page. Resy routes venues under a city segment, so the canonical link the Resy Email Scraper can build is https://resy.com/cities/{city}. Use accountName and fullName to identify the venue.
• username and profileUrl can be empty. They are populated only when Google's result exposes a resolvable path; identity coverage was strong in testing, but a page-level match will still have username: null. That is a Google limitation, not a bug.
• Narrow market. Resy's footprint is concentrated in major US metros, so smaller cities will return little.
• Apify GOOGLE_SERP proxy required. The Resy 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 Resy. This is an independent tool, not supported, endorsed by or connected to Resy.

Resy Email Scraper FAQ

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

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

In a live test, roughly 10 parsed results produced 9 identified venues, 9 profile URLs and 8 unique emails — among the strongest ratios in this family. Total volume still depends on your keywords, domains and location, and no row count is guaranteed.

Does the Resy Email Scraper log into Resy?

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

Why is profileUrl a city link rather than a venue link?

Because Resy routes venue pages under a city segment, so the handle Google exposes in its breadcrumb is the city. The venue name lives in accountName and fullName.

Which keywords work best?

Upscale format terms: tasting menu, chef counter, omakase, wine bar, natural wine, cocktail bar, private dining, new american. Pair them with events, press or owner modifiers.

How do I use location for city-level prospecting?

Put a metro or neighbourhood in it — New York, Brooklyn, Los Angeles, Williamsburg — and run one job per territory. Resy is organised by city, so this maps neatly onto how the platform itself is structured.

What should I set countryCode to?

US. Resy's footprint is overwhelmingly American, and a US vantage point gives Google the best chance of surfacing its pages.

Whose emails am I actually finding?

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

Does the Resy 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 format keywords, add domains such as @outlook.com and @hotmail.com, run more metros, 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 Resy contact emails legal?

The Resy Email Scraper only reads publicly indexed Google results. Whether you may then contact those addresses is a separate CAN-SPAM and GDPR 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 Resy Email Scraper? Contact neurodata.apify@gmail.com.