DoorDash Scraper: Stores, Menus, Reviews & Search

DoorDash Scraper turns DoorDash into structured restaurant and store data. Search any keyword or paste store links or IDs, and get one record per store with rating, price tier, cuisines and location, plus the full menu, contact details and review insights when you switch them on. Export to JSON, CSV or Excel, or pull results straight into your app through the API.

Why This Scraper?

• Two ways to find stores. Run keyword searches localized to a city, or paste store links or bare numeric IDs directly. No need to build URLs by hand.
• One rich record per store. Meta (name, rating, price tier, cuisines, geo) is always included; menu, contact info and reviews are added on top when you turn them on.
• The exact numeric rating count. Not a rounded bucket like "500+": the real count, plus the full 1 to 5 star histogram, review theme highlights and the Google rating aggregate. The written review text itself is capped at roughly the 5 most recent public reviews per store; see the reviews note under Input Parameters.
• Full menu with markdown detection. Item names, prices, photos and dietary tags, with isOnSpecial, savingsAmount and discountPercent derived from the store's own listed price and strikethrough price.
• Pay only for what you turn on. Menu, contact info and reviews all come from one store-detail fetch, billed as a single surcharge per returned store no matter how many of the three you enable; a lean search with all three off skips that fetch and surcharge entirely.
• Opening hours by day, phone number, website and precise latitude and longitude for every enriched store.
• Resume and recurring updates. Continue one interrupted run with resumeFromRunId, or turn on Incremental mode for scheduled runs that return only new and changed stores.

Use Cases

• Food delivery market research: compare pricing tiers, delivery fees and ETAs for a cuisine across a city or a whole metro area.
• Local business directories: republish store contact details, opening hours and menus for a region.
• Competitive intelligence for restaurants: track a competitor's menu prices, specials and rating trends over time with Incremental mode.
• Data science and demand modeling: build historical datasets of ratings, reviews and menu changes for machine learning.
• Lead generation and outreach: find stores that are missing a website or offering deals right now.

Data You Get

Besides the default Stores overview, the Apify Console's dataset Overview tab also offers a Reviews view (one row per review), a Menu items view (one row per menu item), a Contact & hours view (one row per store's contact block) and, in Incremental mode, a Changes view (what's new, updated, back or gone since the last run). Each is just a different slice of the same underlying rows: nothing is scraped twice, and switching views never changes what is in the dataset or what you're billed.

Sample shape: values are illustrative placeholders, not from a live listing.

Field	Example
storeId	"1673363"
name	"Sample Pizza Place"
url	"https://www.doordash.com/store/1673363/"
rating	4.5
ratingCount	1234
priceTier / priceRange	"$$" / 2
cuisines	["Pizza", "Italian"]
city / state	"Sampleton" / "CA"
latitude / longitude	25.0000 / 55.0000
phone	"+10000000000"
website	"https://example.com"
etaMinutes	25
deliveryFee	"$0 delivery fee"
isSponsored / isDashpass / pickupAvailable	false / true / true (last is search mode only; null in URL mode)
businessName	"Sample Restaurant Group"
distance	"1.1 mi"
menuItemCount	42
menu.categories[]	[{ "name": "Most Ordered", "numItems": 6 }]
menu.items[]	[{ "name": "Sample Item", "price": "$7.99", "isOnSpecial": true, "savingsAmount": 2.0, "discountPercent": 20, "dietaryTags": ["Vegetarian"] }]
contact.hours[]	[{ "day": "MONDAY", "slots": ["10 AM - 10 PM"] }]
reviewCount	18
reviews.histogram	{ "1": 5, "2": 3, "3": 4, "4": 20, "5": 90 }
reviews.items[]	[{ "reviewer": "Jane D", "stars": 5, "text": "Sample review text.", "markedUpReviewText": "Sample review <<taggedItemId=123>> text.", "taggedItemIds": ["123"] }]
reviews.themes[]	[{ "label": "Great value", "count": 12, "sentiment": "POSITIVE" }]
scrapedAt	"2026-10-06T12:00:00.000Z" (this row's own read time; excluded from change detection)

How to Use

1. Pick a mode: search (keyword) or url (paste store links or numeric IDs).
2. For search mode, add search terms and, optionally, a location, a store type and the well-rated, deals-only, minimum rating or fast delivery filters.
3. Toggle Include menu, Include contact and hours and Include reviews for the detail you need, and set Max stores to control run size and cost.
4. Click Start, then download the dataset as JSON, CSV or Excel, or read it through the API.

Search by keyword, lean (no detail fetch):

{
  "mode": "search",
  "search": ["pizza"],
  "maxStores": 50,
  "includeMenu": false,
  "includeBusiness": false,
  "includeReviews": false
}

Search a specific city with full detail:

{
  "mode": "search",
  "search": ["sushi", "ramen"],
  "location": "Brooklyn, NY",
  "maxStores": 20,
  "includeMenu": true,
  "includeBusiness": true,
  "includeReviews": true
}

Specific stores by URL or ID:

{
  "mode": "url",
  "urls": ["https://www.doordash.com/store/673363/", "1673363"],
  "includeMenu": true,
  "includeBusiness": true,
  "includeReviews": true
}

URL mode: supported link shapes

If you switch to URL mode and leave Store URLs or IDs untouched, the run scrapes the example links listed in that field (one for each supported shape below), so a first run always returns real stores; replace them with your own links. Search mode ignores the field.

Every shape below was verified live. A store id is read from the start of the URL's path only, so the locale prefix and query string never change what gets scraped. Links copied from page source with & or ' escapes (for example /store/domino's-easley-33931599) are decoded first.

Shape	Example	Resolves to
Canonical, with name slug	https://www.doordash.com/store/juniors-restaurant-new-york-704090/	store 704090
Canonical, bare id	https://www.doordash.com/store/673363/	store 673363
Bare numeric id (no URL)	673363	store 673363
Canonical + query string (pickup, cursor, tracking params, ...)	https://www.doordash.com/store/673363/?pickup=true&cursor=abc123	store 673363
A specific menu (breakfast, lunch, dinner, ...)	https://www.doordash.com/store/2691971/1531826/	store 2691971, served with menu 1531826
Convenience/grocery store page	https://www.doordash.com/convenience/store/370903/	store 370903
The store's reviews page	https://www.doordash.com/reviews/store/2691971/	store 2691971
Any locale prefix (en-CA, fr-CA, en-AU, en-GB, es-US, en, es, fr, it, ...)	https://www.doordash.com/en-CA/store/673363/	store 673363

Not a single store, skipped with a warning in the log, never silently dropped:

Shape	Example	Why it's skipped
Business/chain page	https://www.doordash.com/business/kfc-4477/, https://www.doordash.com/b/new-york-ny/burger-king-10171/	Lists every location of a chain; the trailing number is a business id, a different id space from a store id (verified live: feeding it in as a store id returns a real but unrelated store). Open one of the individual store links from that page instead.
Category / cuisine / dish / city page	https://www.doordash.com/cuisine/pizza-near-me/, https://www.doordash.com/dish/brookie-near-me/, https://www.doordash.com/food-delivery/new-york-ny-restaurants/	A listing of many stores, not one. Use Search mode with a keyword and/or location.
Search-results page	https://www.doordash.com/search/store/pizza/	Same reason: store here is a path segment of the search feature, not an id (so /search/store/7-eleven/ is never mistaken for store 7). Use Search mode.
drd.sh short link	https://drd.sh/tF5uns/	DoorDash's generic marketing short-link domain (referral links, promo/legal terms, app-store "restrictions apply" links); real examples resolve to a help-center or legal page, not reliably a store page. Paste the resolved doordash.com store URL instead.
A link to another website	https://www.example.com/store/123/	Not a DoorDash page.

Well-rated restaurants with active deals in a city:

{
  "mode": "search",
  "search": ["burgers"],
  "location": "Austin, TX",
  "storeType": "restaurant",
  "ratedOnly": true,
  "dealsOnly": true,
  "maxStores": 30
}

Run it from your code

Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("abotapi/doordash-scraper").call(run_input={"mode": "search", "search": ["pizza"], "maxStores": 20})
for store in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(store["name"], store["rating"], store["priceTier"])

JavaScript:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('abotapi/doordash-scraper').call({ mode: 'search', search: ['pizza'], maxStores: 20 });
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Or connect it to Make, Zapier, n8n, Google Sheets or webhooks from the Integrations tab.

Detail fetch and cost by mode

Search mode only fetches, and only charges for, store detail (menu, contact and reviews) when at least one of the three include toggles is on; leave all three off for a lean, meta-only search that skips the detail fetch entirely. URL mode always fetches the full store detail for every store you list, regardless of those toggles, since the toggles only decide which of menu, contact and reviews end up in the output record, not whether the detail page is loaded.

Resume and recurring updates

• Resume (resumeFromRunId) continues one specific interrupted or previous run: paste its run or dataset ID and this run skips stores already collected there, so you don't pay twice. An automatic same-run checkpoint also protects against platform migrations without any input needed. An invalid or unresolvable id stops the run before anything is scraped or charged.

• Incremental mode (incrementalMode) is for a schedule, for example daily, over the same search or URLs. The actor remembers the previous run of the same search itself, so you never paste a run id. The first run returns everything as NEW. Later runs return NEW, UPDATED (with changedFields) and, if you turn on emitUnchanged, UNCHANGED stores that did not change (suppressed and not billed by default). EXPIRED rows for stores no longer found are only produced when emitExpired is on and the run scanned the full tracked search (not capped by Max stores or Max pages, and not a Resume run). REAPPEARED is only produced for a store a previous run already marked EXPIRED this way; if a monitoring campaign has never turned emitExpired on, no store can ever come back as REAPPEARED, because none was ever marked gone in the first place.

• What counts as changed: these fields are excluded from change detection by default, built into the actor, not something you need to configure: they still appear in the row, they just never drive UPDATED or appear in changedFields by themselves:

  • nextOpenTime, nextCloseTime: tick with each request's clock even for an always-open store, never a real change.
  • scrapedAt: this row's own read time; always differs between runs by construction.
  • asapAvailable: flips with the store's open/closed clock, the same wall-clock dependence as nextOpenTime/nextCloseTime above.
  • searchEtaMinutes: the search card's live ETA to the searched address; measured drifting run to run with no store change (load-driven, not store-driven). etaMinutes (the store-detail ETA) is NOT excluded and always drives UPDATED.
  • menuId, menuName, menuHours: which menu the store is currently serving (e.g. Breakfast vs. Dinner); each menu's own schedule stays tracked via menus, and switching menus already changes menu.
  • reviews.items.reviewerDescription: the reviewer's own profile line, not a fact about this store.
  • storeName: a pure duplicate of name (kept only as a stable identity column for the reviews/menu output views); name itself stays tracked.

  Small GPS-distance floating point noise is rounded away too. Rating, price tier, delivery fee, etaMinutes, menu items, reviews and business contact info were all measured byte-identical across two live fetches of the same store minutes apart and are real data that always drives UPDATED. If a field in your own monitoring setup still turns out noisy, add it (or a dotted path into a nested field, e.g. reviews.items) to ignoreFieldsForChanges and it is excluded from then on, on top of the list above; it still appears in the row, just never flags a change by itself.

• A search page that comes back with zero stores on its very first page is treated the same as a connection problem for EXPIRED purposes, not as "this search is empty now": EXPIRED detection is skipped for that run (the previous baseline is kept untouched) rather than risk marking real, still-open stores as gone.

• stateKey names or shares one monitoring campaign's stored state; maxStores and maxPages never affect it, so raising your cap keeps the same baseline instead of re-billing everything. maxStores counts stores scanned (collected and detail fetched), not stores actually returned, so a quiet monitoring run where nothing changed still scans up to the cap.

Send results into your apps (MCP connectors)

Optionally pipe the scraped results into the apps you already use, via Model Context Protocol (MCP) connectors. This is an extra delivery step after the scrape, and the Apify dataset is never changed.

What gets written to the connector: a condensed, human-readable summary of each record, not the full JSON. Each item becomes one entry with a title and its key fields flattened to plain text. The complete record always stays in the Apify dataset.

1. Authorize a connector once under Apify → Settings → Integrations (Notion, Linear, Airtable, or Apify).
2. Select it in the "Pipe results into your apps" input field. If the picker is empty, you haven't authorized a connector yet.
3. For Notion, also set notionParentPageUrl to the page where items should be created.

The connection is mediated by Apify's MCP proxy, so this actor never sees your third-party credentials. Leave the field empty to skip.

Input Parameters

Parameter	Type	Default	Description
mode	string	search	search for keyword search, url for store links or IDs.
search	array	none (prefill: ["pizza"])	Keywords to search on DoorDash. One search runs per term. Search mode only.
location	string	none	City or address to localize search, for example "Brooklyn, NY". If empty, a default city for your proxy country is used: New York (Manhattan, New York, NY 10001) for US, Toronto for CA, Sydney for AU, Auckland for NZ. DoorDash lists no stores in other countries, so any other proxy country searches New York and logs a warning. A location DoorDash cannot place stops the run with a message saying so; another place is never guessed. Search mode only.
storeType	string	any	Limit search to a category: any, restaurant, grocery, retail. restaurant excludes convenience/grocery stores. Search mode only.
ratedOnly	boolean	false	Only return stores that have a customer rating. Search mode only.
dealsOnly	boolean	false	Only return stores currently offering deals. Search mode only.
minRating	string	any	Only return stores rated at least this many stars, using DoorDash's own rating filter: any, 4, 4.5, 4.6, 4.7, 4.8 or 4.9 (the values DoorDash's own Ratings filter offers). When set, this overrides the ratedOnly filter above. Search mode only.
fastDeliveryOnly	boolean	false	Only return stores with a delivery estimate of 30 minutes or less for your location, using DoorDash's "Under 30 min" filter. Search mode only.
urls	array	one example of each supported shape (the same list is the prefill)	Store links or bare numeric store IDs, see "URL mode: supported link shapes" above for every supported shape and the ones that are skipped with a warning instead. URL mode only.
includeMenu	boolean	true	Add the full menu. Requires a store-detail fetch (always made in URL mode; made in search mode only if this or another include toggle is on).
includeBusiness	boolean	true	Add phone, website and opening hours.
includeReviews	boolean	true	Add reviews, star histogram, themes and the Google rating aggregate. The written review text is DoorDash's own public preview, up to ~5 most recent reviews per store, logged out; see "Why does reviews.items only have a few entries?" in the FAQ.
maxReviews	integer	20	Maximum written reviews kept in reviews.items per store. DoorDash serves at most about 5 to a logged-out visitor, so the default keeps everything it serves; lower it to keep fewer, or 0 for none (the star histogram, review counts, themes and Google rating are still included). Adds no charge.
maxStores	integer	20	Max stores across all searches/URLs. 0 means no limit. Counts stores scanned (collected and detail fetched), before any Incremental mode suppression.
maxPages	integer	none, unlimited when omitted (prefill: 0, also unlimited)	Optional bound on result pages walked per search query. Leave empty or 0 to walk every result page. Search mode only.
resumeFromRunId	string	none	Previous run ID or dataset ID from this actor. Stores already collected there are skipped, so this run only returns new ones.
incrementalMode	boolean	false	Turn on for scheduled monitoring of the same search or URLs; see "Resume and recurring updates" above.
stateKey	string	none	Name a monitoring campaign, so its state stays stable, or deliberately share it across differently configured runs. Auto derived when left empty.
emitUnchanged	boolean	false	Incremental mode only. Also return (and bill) stores unchanged since the last run, marked UNCHANGED.
emitExpired	boolean	false	Incremental mode only. Also return (and bill) stores from a previous run no longer found, marked EXPIRED, once a run has fully scanned the tracked search.
ignoreFieldsForChanges	array	[]	Incremental mode only. Extra field names to exclude from UPDATED change detection, on top of the built-in defaults: nextOpenTime, nextCloseTime, scrapedAt (wall-clock state, never a real store change), asapAvailable (ticks with the open/closed clock), searchEtaMinutes (load-driven search-card ETA noise; etaMinutes is NOT excluded), menuId/menuName/menuHours (which menu is currently being served), reviews.items.reviewerDescription (the reviewer's own profile line) and storeName (a duplicate of name). See "What counts as changed" above for the full reasoning. Accepts a top-level field (e.g. rating) or a dotted path into a nested field (e.g. reviews.items). Use this if a field in your own setup turns out to be noisy.
proxy	object	Residential, US	Apify Residential proxy is required.
mcpConnectors	array	none	Optional: send a summary of each store to apps you authorized under Integrations.
notionParentPageUrl	string	none	Notion connector only: page under which store pages are created.
maxNotifyListings	integer	50	Cap on items written to each connector per run. Does not affect the dataset.

Output Example

Sample shape: values are illustrative placeholders, not from a live listing.

{
  "storeId": "1673363",
  "name": "Sample Pizza Place",
  "url": "https://www.doordash.com/store/1673363/",
  "rating": 4.5,
  "ratingCount": 1234,
  "priceTier": "$$",
  "cuisines": ["Pizza", "Italian"],
  "city": "Sampleton",
  "state": "CA",
  "latitude": 25.0000,
  "longitude": 55.0000,
  "etaMinutes": 25,
  "deliveryFee": "$0 delivery fee",
  "isSponsored": false,
  "isDashpass": true,
  "phone": "+10000000000",
  "website": "https://example.com",
  "contact": {
    "phone": "+10000000000",
    "website": "https://example.com",
    "hours": [{ "day": "MONDAY", "slots": ["10 AM - 10 PM"] }],
    "address": { "street": "1 Sample St", "city": "Sampleton", "state": "CA" }
  },
  "menu": {
    "categories": [{ "name": "Most Ordered", "numItems": 6 }],
    "items": [{ "name": "Sample Item", "price": "$7.99", "strikethroughPrice": "$9.99", "isOnSpecial": true, "savingsAmount": 2.00, "discountPercent": 20, "dietaryTags": ["Vegetarian"] }],
    "popularItems": [{ "name": "Sample Item", "price": "$9.99", "strikethroughPrice": "", "isOnSpecial": false, "savingsAmount": null, "discountPercent": null }]
  },
  "menuItemCount": 42,
  "reviews": {
    "avgRating": 4.5,
    "numRatings": 1234,
    "numReviews": 18,
    "histogram": { "1": 5, "2": 3, "3": 4, "4": 20, "5": 90 },
    "items": [{ "reviewer": "Jane D", "stars": 5, "text": "Sample review text.", "isVerified": true }],
    "themes": [{ "label": "Great value", "count": 12, "sentiment": "POSITIVE" }],
    "google": { "avgRating": 4.4, "numRatings": 500 }
  },
  "reviewCount": 18
}

Incremental mode only. When incrementalMode is on, every returned record also carries:

Field	Description
changeType	NEW, UPDATED, UNCHANGED, REAPPEARED or EXPIRED
changedFields	Top-level fields that changed since last seen; non-empty only for UPDATED
firstSeenAt	When this store was first observed by this monitoring campaign
lastSeenAt	When this store was last observed

Plan Requirement

This actor needs Apify Residential proxy, available on the Starter plan and above. Residential is the default and recommended setting; set the proxy country to the region you want search results localized to, for example US. The store-detail surcharge applies once per returned store whenever the detail page is loaded: in search mode only if at least one include toggle is on, in URL mode always. A lean search with all three toggles off costs the least.

FAQ

How much does it cost?

You pay per record returned, plus one detail surcharge per returned store whose detail page was loaded (search mode: only when at least one include toggle is on; URL mode: always). An unchanged store suppressed by Incremental mode is fetched to check but not billed for that surcharge. The Pricing tab shows current rates. Use Max stores to cap the size of any run.

Is it legal to scrape DoorDash?

This actor collects only publicly available store, menu and review data. You are responsible for how you use it: follow DoorDash's terms and the laws that apply to you, and get legal advice if you plan commercial redistribution. Store names, menus and prices are generally facts, but photos and review text may be subject to third-party rights.

Can I get only new or changed stores on a schedule?

Yes. Schedule the actor from the Schedules tab and turn on Incremental mode. Each run then returns only new and updated stores, and unchanged ones are suppressed and not billed unless you turn on Emit unchanged.

What is the difference between Resume and Incremental mode?

Resume (resumeFromRunId) continues one specific interrupted or previous run: paste its run or dataset id once and this run skips what it already collected. Incremental mode is for running the exact same search or URLs again and again on a schedule; the actor remembers the previous run itself, with nothing to paste. Turning both on together for a search that already has saved incremental state is rejected before any scraping happens; pick one. Also note that REAPPEARED only ever appears for a store a previous run already marked EXPIRED, which itself requires emitExpired to have been on for that campaign.

Which city does a search use when Location is empty?

The default city for your proxy country: New York for US, Toronto for CA, Sydney for AU and Auckland for NZ. Since the October 2026 update the US default is the precise New York, NY 10001 (Manhattan). Earlier versions sent the bare New York, NY, which DoorDash placed near Binghamton, NY, so empty-Location US searches returned upstate stores; a scheduled Incremental search with an empty Location therefore sees one round of NEW Manhattan stores after the update. Proxy countries DoorDash does not serve (for example GB, IE, DE, AT) used to resolve to same-named North American towns (London, Ontario; Berlin, Wisconsin); they now search New York and log a warning telling you to set Location.

Why did my run fail instead of returning an empty dataset?

The run fails before any scraping happens if your input cannot make sense: an invalid or unresolvable resumeFromRunId, or turning on Incremental mode together with Resume for a search that already has saved incremental state. It also fails, with a clear status message instead of a silent zero-result success, whenever every proxy connection the run tried was refused or exhausted and no page was ever read:

• The proxy connection was refused outright for your account (no plan access, or your own proxy URLs are invalid): the message points you to upgrading at https://apify.com/pricing or checking your proxy credentials.
• Residential proxies were unavailable on a Free plan and the backup connection also could not load the requested pages (including a backup connection that came up but never delivered a page): the message tells you to upgrade or supply your own proxy URLs.
• Every request failed for some other connection reason, with no proxy entitlement signal either way: the message says this is a connection problem, not an empty search, and to try again later.

A first results page that could not be fetched at all is reported the same way, so a connection failure never masquerades as "no stores found". A first page that is fetched fine but holds zero stores is a different case: an unfiltered zero-match search normally still returns this site's own fallback results, and restrictive filters (for example rating + deals + fast-delivery together) remove those fallbacks, so a genuinely empty result completes as a normal zero-result run with a ZERO_RESULTS status message instead of a failure. One exception is checked separately: when you set a location and every first page comes back empty, the run repeats your first search once at the default city for your proxy country. If that returns stores, the location is the cause (DoorDash could not place it, or does not deliver there), and the run fails with a message naming your location and how to fix it ("City, ST", a full street address, or an empty Location). In URL mode, a run in which none of your store links or IDs ever loaded a store page also never ends as a silent success: if a page request failed it fails with the messages above, and if the pages answered but none was a store it completes with a ZERO_RESULTS status message saying so. An ordinary site-side block or a single failed fetch on one store, by contrast, still completes as a normal run with partial results and a status message explaining what was skipped.

Can I use it with AI agents or MCP?

Yes. Call it from any Apify integration or MCP client, and use the connector field to push results into Notion, Linear or Airtable.

Why does reviews.items only have a few entries?

DoorDash itself only serves a public preview of written reviews, up to about 5 of the most recent, to a logged-out visitor; the full list only loads after the visitor signs in to a DoorDash consumer account on doordash.com, which this actor does not do (no login/cookies are accepted as input). reviewCount and the reviews.histogram 1-to-5 star breakdown are the real site-wide totals, not capped, so they will usually be larger than reviews.items.length: that gap is DoorDash's own preview limit, not a bug or an artificial cutoff on our side. The maxReviews input (default 20) can only keep fewer of the served reviews, never fetch more; reviews never add a charge of their own, they ride on the store's single detail fetch.

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