Yelp Scraper

Yelp Scraper creates a structured dataset of business listings collected from Yelp. Each dataset item can include business identifiers, ratings, review counts, price range, categories, address and coordinates, and — when business details are enabled — phone, hours, attributes, and review text. Query the source using start URLs, a search term and location, or searchQueries, control the result limit with maxItems, and retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, XML, or another supported format.

Dataset at a glance

Property	Value
Source	Yelp (yelp.com and regional sites such as yelp.de, yelp.co.uk, yelp.com.au)
Record unit	One business listing
Input methods	startUrls, searchTerm + location, searchQueries
Main identifiers	businessId, url, alias
Delivery	Apify Dataset and API
Export formats	JSON, CSV, Excel, XML, HTML
Update model	Fresh records per Actor run
Pricing	$1.50 per 1,000 listings; $3.00 per 1,000 additional for full business details

Coverage and available records

The Actor collects business listings from Yelp search and category pages, and from direct business-page URLs. Supported behavior:

• Search by term and location — searchTerm plus location resolves through Yelp's own search/autocomplete.
• Search queries — searchQueries accepts strings like "Pizza in Berlin" or "term | location".
• Regional sites — countryCode selects among 31 Yelp sites (US, DE, AT, CH, FR, IT, ES, NL, BE, IE, GB, CA, AU, NZ, SG, JP, MX, BR, SE, NO, DK, FI, PL, CZ, PT, AR, CL, HK, MY, PH, TW). Ignored when a start URL already includes a host.
• Listing-only vs. details — scrapeDetails (default false) returns listing fields only; when enabled, each business is enriched with phone, hours, attributes, full address, and up to a page of review text.
• Pagination and limits — maxItems caps the number of businesses (0 = unlimited).

Not currently collected: menu data, photos beyond the primary thumbnail, owner responses, and full review history (the Actor returns the review snippet visible on the page, not every review).

Data dictionary

Listing fields (always present when available):

Field	Type	Nullable	Description	Example
businessId	string	no	Yelp internal business identifier; recommended deduplication key	_n0Awcf8FFjXBJaCgXXROw
name	string	no	Business name	Café Bondi
alias	string	yes	Yelp URL slug	café-bondi-berlin-2
url	string	no	Business page URL	https://www.yelp.de/biz/café-bondi-berlin-2
rating	number	yes	Average star rating	4.2
reviewCount	integer	yes	Number of reviews	117
priceRange	string	yes	Price range symbols	€€
categories	array	yes	Display category names	["Frühstück & Brunch","Café"]
categoryAliases	array	yes	Normalized category slugs	["breakfast_brunch","cafes"]
photo	string	yes	Primary photo URL	https://s3-media0.fl.yelpcdn.com/...jpg
isAd	boolean	yes	Whether the listing is paid placement	false
ranking	integer	yes	Position within the search result set	1
searchTerm	string	yes	Term used for the query	Lunch
searchLocation	string	yes	Resolved location	Berlin, Deutschland
sourceQuery	string	yes	Combined query string	Lunch in Berlin, Deutschland
domain	string	yes	Yelp site host	www.yelp.de
snippet	string	yes	Highlighted review snippet	...lots of lunch menu items...
detailsFetched	boolean	no	Whether detail enrichment succeeded	true

Detail fields (present when scrapeDetails is enabled and the page yields them):

Field	Type	Nullable	Description	Example
address	string	yes	Full street address	Eichendorffstr. 6, Berlin, BE, 10115
addressLine1	string	yes	First address line	Eichendorffstr. 6
city	string	yes	City	Berlin
region	string	yes	State/region code	BE
postalCode	string	yes	Postal code	10115
country	string	yes	Country code	DE
neighborhoods	array	yes	Neighborhood names	["Mitte"]
latitude / longitude	number	yes	Coordinates	52.53034262
phone	string	yes	Phone number	030 2411221
isClosed	boolean	yes	Whether the business is marked closed	false
isOpenNow	boolean	yes	Whether open at scrape time	true
hours	array	yes	Weekly hours, one object per day	[{"day":"Mo","hours":["8:00 AM - 6:00 PM"]}]
attributes	object	yes	Business attributes (parking, seating, etc.)	{"OutdoorSeating":true}
reviews	array	yes	Review objects from the page	see below

Each element of reviews contains id, rating, text, language, author, authorLocation, authorReviewCount, and date.

Example dataset record

{
  "businessId": "vs3J4zfbThn0_5w2Q5Mfuw",
  "name": "Schlögl's",
  "alias": "schlögls-berlin",
  "url": "https://www.yelp.de/biz/schlögls-berlin",
  "rating": 4.3,
  "reviewCount": 114,
  "priceRange": "€€",
  "categories": ["Deutsch", "Biergarten"],
  "categoryAliases": ["german", "beergarden"],
  "photo": "https://s3-media0.fl.yelpcdn.com/bphoto/6J497GlRPS0VMOg3GQTuog/l.jpg",
  "isAd": false,
  "ranking": 2,
  "searchTerm": "Lunch",
  "searchLocation": "Berlin, Deutschland",
  "sourceQuery": "Lunch in Berlin, Deutschland",
  "domain": "www.yelp.de",
  "detailsFetched": true,
  "address": "Karl-Liebknecht-Str. 9, Berlin, BE, 10178",
  "city": "Berlin",
  "country": "DE",
  "latitude": 52.5213,
  "longitude": 13.406281,
  "phone": "030 2411221",
  "isClosed": false,
  "isOpenNow": false,
  "hours": [
    {"day": "Mo", "hours": ["Geschlossen"], "isClosed": null}
  ],
  "reviews": [
    {
      "id": "E6wsKvO9VBU3e6lLjaQx1g",
      "rating": 5,
      "text": "Went here on the limb. While visiting Berlin...",
      "language": "en",
      "author": "Renata R.",
      "authorLocation": "New York, Vereinigte Staaten",
      "authorReviewCount": 607,
      "date": "2026-07-01T21:29:42+02:00"
    }
  ]
}

The record above was produced by a run with searchQueries: ["Lunch in Berlin"], countryCode: "DE", and scrapeDetails: true.

Query and input reference

Input	Type	Required	Default	Accepted values	Description
startUrls	array	no	—	Yelp search or business URLs	Preferred input; domain is taken from the URL host
searchTerm	string	no	—	keyword or category	What to find, e.g. Restaurants, Pizza
location	string	no	—	city or area	Where to search, e.g. Berlin, New York, NY
searchQueries	array	no	—	"term in location" or "term | location"	Alternative to searchTerm + location
countryCode	string	no	US	31 regional codes	Yelp site used when no start URL host is present
scrapeDetails	boolean	no	false	true / false	Fetches full business details; adds the listing-details charge event
maxItems	integer	no	0	0 = unlimited	Maximum businesses to scrape
proxyConfiguration	object	no	residential proxy	proxy settings	Residential proxies are recommended

Minimal request:

{
  "searchTerm": "Lunch",
  "location": "Berlin",
  "countryCode": "DE",
  "maxItems": 20,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

Advanced request (bulk queries with details):

{
  "searchQueries": ["Lunch in Berlin", "Pizza in München"],
  "countryCode": "DE",
  "scrapeDetails": true,
  "maxItems": 0,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

Retrieve the data through the API

1. Start the Actor with a JSON input (see above).
2. Wait for the run to finish, or call the synchronous endpoint for quick jobs.
3. Retrieve items from the run's default dataset.
4. Paginate or export the dataset in the format you need.

Python example:

import json
import urllib.request

API_TOKEN = "<your Apify API token>"
ACTOR_ID = "datascrapers/yelp-scraper"

payload = {
    "searchTerm": "Lunch",
    "location": "Berlin",
    "countryCode": "DE",
    "maxItems": 20,
    "proxyConfiguration": {"useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"]},
}

req = urllib.request.Request(
    f"https://api.apify.com/v2/acts/{ACTOR_ID}/runs?token={API_TOKEN}",
    data=json.dumps(payload).encode(),
    headers={"Content-Type": "application/json"},
)
with urllib.request.urlopen(req) as resp:
    run = json.loads(resp.read())["data"]

dataset_id = run["defaultDatasetId"]
with urllib.request.urlopen(
    f"https://api.apify.com/v2/datasets/{dataset_id}/items?token={API_TOKEN}"
) as resp:
    items = json.loads(resp.read())

For other languages, use the generated API tab on the Actor's page.

Data quality and record handling

• Conditional fields — detail fields (phone, hours, attributes, reviews) are only present when scrapeDetails is enabled and Yelp exposes them for that business.
• Nullable values — rating, reviewCount, and address components may be absent for sparse listings; treat them as nullable.
• Deduplication — businessId is the stable, recommended unique key. url also uniquely identifies a business.
• Retries and errors — requests are retried with backoff; a business that fails to load is skipped rather than partially written.
• Raw values — priceRange, categories, and hours are reported as Yelp displays them; no normalization beyond extracting the fields above.

The Actor does not guarantee a full-site snapshot; results reflect what a given query returns at run time.

Export and pipeline examples

Destination	Recommended method	Typical use
PostgreSQL/Supabase	Dataset API or webhook consumer	Store business records keyed by businessId
Google Sheets	Apify integration	Review and share a small result set
S3/cloud storage	Scheduled export or integration	Archive daily/weekly snapshots
BI tools	CSV/JSON export	Analyze ratings and price ranges by city

Pricing and cost examples

The Actor uses pay-per-event billing. Two charge events apply:

• dataset-item — $1.50 per 1,000 business listings returned.
• listing-details — $3.00 per 1,000 businesses when scrapeDetails is enabled (in addition to the listing event).

Apify plan discounts (Bronze/Silver/Gold) reduce these rates.

Records	Estimated base cost
1,000 listings	$1.50
10,000 listings	$15.00
10,000 listings + details	$45.00

Estimates assume the free-tier rate and no proxy markup; actual cost depends on your Apify plan and selected options.

Limitations and responsible data use

• The Actor collects publicly accessible listing data only; it does not bypass login or paywalls.
• Results depend on Yelp's current page structure; site changes can require Actor updates.
• Some fields are conditional or nullable (see Data dictionary).
• The Actor does not retain historical snapshots unless you store them yourself.
• You are responsible for complying with Yelp's terms of service and applicable privacy and contractual obligations.

Dataset questions

What does one dataset item represent?

One Yelp business listing, optionally enriched with full business details and a page of reviews.

Which field should I use as a unique identifier?

businessId. url is also unique and useful for joins with other datasets.

Are fields nullable or conditional?

Yes. Rating, review count, and address components may be null. Detail fields appear only when scrapeDetails is enabled and the page exposes them.

Can I retrieve the records as CSV or JSON?

Yes. The default dataset supports JSON, CSV, Excel, and XML exports, and the Dataset API returns JSON.

How do I paginate large datasets?

Set maxItems to cap the run, or paginate the default dataset via the Dataset API (offset/limit parameters).

What counts as a billable result?

Each business listing returned counts as one dataset-item. Enabling scrapeDetails adds one listing-details event per business.

Related datasets from Data Scrapers

• LinkedIn Company Scraper — company-level data (employee count, posts, founders) that can be joined with business listings by company name.
• Redfin Scraper — real-estate listings with pricing for location-based market research.
• Instagram Post Scraper — social posts that complement local-business brand analysis.
• Zoopla Scraper — property listings for adjacent UK location datasets.

Data Scrapers support

Need an additional field, record type, or export workflow? Contact Data Scrapers at stardustspotlight@gmail.com. Include a sample source URL, required fields, expected record volume, and preferred delivery format.