Yelp Business Review Scraper

Yelp Review Scraper -- Extract All Business Reviews Without API Limits

Scrape all Yelp business reviews at scale -- a powerful alternative to the Yelp Fusion API that bypasses the 3-review limit. The Yelp Fusion API only returns 3 reviews per business, making it useless for any serious analysis. Yelp Business Review Scraper is an Apify actor that extracts all reviews from any Yelp business listing, bypassing the official Yelp Fusion API's 3-review limit. Extract review text, star ratings, dates, reviewer info, photos, business owner replies, and more from any Yelp business page. Use the data for sentiment analysis, competitor research, reputation monitoring, or market intelligence.

• Why use this Yelp review scraper?
• What data can you extract from Yelp reviews?
• How to scrape Yelp reviews
• Input parameters
• Output example
• How much does it cost to scrape Yelp reviews?
• Use cases for Yelp review data
• Integrations and API access
• Frequently asked questions
• Related actors

Why use this Yelp review scraper?

• 📊 Extract all reviews, not just 3 -- the Yelp Fusion API returns a maximum of 3 reviews per business. This Yelp scraper extracts every review available on the business page, giving you the complete picture.
• ⚡ No API key required -- skip the Yelp Fusion API application process and rate limits. Start scraping Yelp reviews in minutes without any API credentials.
• 🌍 Filter reviews by language -- retrieve reviews in any of 24 supported languages, including English, Spanish, French, German, Japanese, Chinese, Korean, and more.
• 🔄 Sort reviews any way you need -- sort by newest, oldest, highest rated, lowest rated, Yelp default, or elite reviews only. Get exactly the data slice you need for your analysis.
• 📥 Export in any format -- download your scraped Yelp reviews as JSON, CSV, Excel, XML, or HTML. Integrate directly into your data pipeline or spreadsheet workflow.
• 🔁 Automatic pagination -- the scraper fetches all available review pages automatically. No need to handle pagination logic yourself.
• 🏢 Bulk scraping -- scrape reviews from multiple Yelp businesses in a single run. Just provide a list of URLs, business IDs, or aliases.
• 💬 Business owner replies included -- extract business owner responses to reviews, including the reply text, date, and owner information.
• 👤 Optional reviewer data -- enable sensitive data mode to get reviewer names, locations, profile URLs, review counts, friend counts, and elite status.
• 🖼️ Review photos -- extract all images attached to each review, including captions when available.
• 📈 Feedback metrics -- get the useful, funny, and cool vote counts for every review, so you can identify the most impactful reviews.
• 🔗 Flexible input -- provide Yelp business URLs, business aliases (URL slugs), or Yelp business IDs. Mix and match input types in a single run.
• 🛡️ Reliable and maintained -- regularly updated to keep pace with Yelp's website changes. Built on the Apify platform with automatic retries and error handling.

What data can you extract from Yelp reviews?

Yelp Business Review Scraper extracts a comprehensive set of data fields from every review. Here is the complete list of fields you get for each scraped Yelp review:

Core review data:

• Star rating (1-5) -- the reviewer's numerical rating of the business
• Full review text -- the complete text of the review, not truncated
• Review date -- when the review was posted
• Review language -- ISO 639-1 language code (e.g., "en", "es", "fr")
• Review ID -- unique Yelp identifier for the review
• Review URL -- direct link to the review on Yelp

Business identification:

• Business ID -- Yelp's internal business identifier
• Business alias -- URL-friendly slug (e.g., "the-old-fashioned-madison")
• Business URL -- full link to the Yelp business page

Review media:

• Images -- all photos attached to the review, including URLs and captions
• Image count -- number of photos attached (in CSV output)

Community feedback:

• Useful votes -- how many users marked the review as useful
• Funny votes -- how many users marked the review as funny
• Cool votes -- how many users marked the review as cool

Business owner reply (when present):

• Reply text -- the owner's response to the review
• Reply date -- when the owner responded
• Reply ID -- unique identifier for the reply

Reviewer information (when includeSensitiveData is enabled):

• Reviewer name -- the reviewer's display name on Yelp
• Reviewer location -- where the reviewer is based
• Reviewer profile URL -- link to their Yelp profile
• Review count -- total number of reviews the user has written
• Friend count -- number of Yelp friends
• Photo count -- number of photos the user has posted
• Elite year -- the year the reviewer achieved Yelp Elite status (if applicable)
• Reply user name -- name of the business owner who replied
• Reply user role -- role of the replying user (e.g., "Business Owner")

This level of detail makes the scraper ideal for in-depth sentiment analysis, competitive benchmarking, and review trend analysis. The Yelp Fusion API, by comparison, returns only 3 reviews per business with a limited subset of fields.

How to scrape Yelp reviews

Getting started with Yelp review scraping takes less than five minutes. Follow these steps to extract your first batch of Yelp reviews:

Step 1: Create a free Apify account

Sign up at apify.com if you don't already have an account. Every new account comes with $5 in free credits -- enough to scrape 5,000 Yelp reviews at no cost.

Step 2: Open Yelp Business Review Scraper

Navigate to the Yelp Business Review Scraper actor page on the Apify Store. Click the Try for free button to open the actor in your Apify Console.

Step 3: Add Yelp business URLs, aliases, or IDs

In the input form, add the Yelp businesses you want to scrape reviews from. You have three options:

• Business URLs -- paste full Yelp URLs like https://www.yelp.com/biz/the-old-fashioned-madison
• Business aliases or IDs -- enter URL slugs like the-old-fashioned-madison or Yelp business IDs

You can add as many businesses as you need. The scraper processes them all in a single run.

Step 4: Configure optional settings

Optionally, adjust these settings to fine-tune your scrape:

• Set the review language to filter reviews in a specific language
• Choose a sort order (newest, oldest, highest rated, etc.)
• Set a maximum number of reviews per business
• Enable sensitive data to include reviewer personal information

Step 5: Click Start and download your data

Click the Start button to begin scraping. Once the run completes, download your Yelp review data in any format you prefer: JSON, CSV, Excel, XML, or HTML. You can also access the data programmatically via the Apify API.

Input parameters

Parameter	Type	Required	Default	Description
businessUrls	array	No*	--	Yelp URLs of businesses to scrape reviews from. Example: https://www.yelp.com/biz/the-old-fashioned-madison
businessAliasesOrIds	array	No*	--	Business aliases (URL slugs) or Yelp business IDs. Example: the-old-fashioned-madison
language	string	No	en	Filter reviews by language using ISO 639-1 codes. 24 languages supported: English, Spanish, French, German, Italian, Dutch, Portuguese, Russian, Japanese, Chinese (Simplified), Chinese (Traditional), Korean, Turkish, Arabic, Danish, Finnish, Norwegian, Swedish, Hebrew, Thai, Polish, Czech, Hungarian, Greek.
sortBy	string	No	newest	Sort order for reviews. Options: newest, oldest, yelp (Yelp default), highestRated, lowestRated, elites (elite reviews only).
maxReviews	integer	No	100	Maximum number of reviews to fetch per business.
includeSensitiveData	boolean	Yes	false	Include reviewer personal information (name, location, profile URL, friend count, photo count, review count, elite year) in the output.

*At least one of businessUrls or businessAliasesOrIds must be provided.

Output example

Yelp Business Review Scraper outputs data in two formats: a structured JSON dataset and a flattened CSV file. You can export the results in JSON, CSV, Excel, XML, or HTML directly from the Apify Console, or access them programmatically via the Apify API.

CSV file

Scraped reviews are stored in a CSV file named reviews.csv. The file contains the following columns:

• business_id: Yelp business ID
• business_alias: Yelp business alias (URL slug)
• business_url: Link to the Yelp business page
• review_id: Unique review identifier
• review_url: Link to the review on Yelp
• rating: Star rating (1-5)
• text: Full review text
• language: Review language (ISO 639-1 code)
• date: Review date
• image_count: Number of images attached to the review
• feedback_useful: Number of "useful" votes
• feedback_funny: Number of "funny" votes
• feedback_cool: Number of "cool" votes
• reply_id: Business owner reply ID (if any)
• reply_text: Business owner reply text (if any)
• reply_date: Business owner reply date (if any)

When includeSensitiveData is enabled, the following columns are also included:

• reply_user_name: Name of the business owner who replied
• reply_user_role: Role of the replying user (e.g. "Business Owner")
• user_id: Reviewer's Yelp user ID
• user_url: Link to the reviewer's Yelp profile
• user_name: Reviewer's display name
• user_location: Reviewer's location
• user_friend_count: Number of friends the reviewer has
• user_photo_count: Number of photos the reviewer has posted
• user_review_count: Number of reviews the reviewer has written
• user_elite_year: Year the reviewer achieved Yelp Elite status (if applicable)

Example CSV output

business_id,business_alias,business_url,review_id,review_url,rating,text,language,date,image_count,feedback_useful,feedback_funny,feedback_cool,reply_id,reply_text,reply_date
RJNAeNA-209sctUO0dmwuA,the-old-fashioned-madison,https://www.yelp.com/biz/the-old-fashioned-madison,abc123,https://www.yelp.com/biz/the-old-fashioned-madison?hrid=abc123,5,"Absolutely loved this place! The cheese curds were perfectly crispy and the Old Fashioned cocktail was top-notch. Great atmosphere right on the Capitol Square.",en,2024-08-12,2,4,1,2,,,
RJNAeNA-209sctUO0dmwuA,the-old-fashioned-madison,https://www.yelp.com/biz/the-old-fashioned-madison,def456,https://www.yelp.com/biz/the-old-fashioned-madison?hrid=def456,4,"Solid Wisconsin comfort food. The Friday fish fry is a must-try. Only downside is the long wait times on weekends - get there early!",en,2024-07-28,0,2,0,1,reply789,"Thanks for the kind words! We're glad you enjoyed the fish fry. Pro tip: reservations help with the weekend rush!",2024-07-30

Apify Dataset

The results are stored in a dataset which you can find in the Storage tab. Each item in the dataset represents a single review.

Example JSON output

{
  "business_id": "RJNAeNA-209sctUO0dmwuA",
  "business_alias": "the-old-fashioned-madison",
  "business_url": "https://www.yelp.com/biz/the-old-fashioned-madison",
  "review_id": "abc123",
  "review_url": "https://www.yelp.com/biz/the-old-fashioned-madison?hrid=abc123",
  "rating": 5,
  "text": "Absolutely loved this place! The cheese curds were perfectly crispy and the Old Fashioned cocktail was top-notch. Great atmosphere right on the Capitol Square.",
  "language": "en",
  "date": "2024-08-12",
  "images": [
    {
      "url": "https://s3-media0.fl.yelpcdn.com/bphoto/example1/o.jpg",
      "caption": "Wisconsin cheese curds"
    },
    {
      "url": "https://s3-media0.fl.yelpcdn.com/bphoto/example2/o.jpg",
      "caption": null
    }
  ],
  "feedback": {
    "useful": 4,
    "funny": 1,
    "cool": 2
  },
  "businessOwnerReply": null,
  "user": null
}

Example JSON output with sensitive data enabled

When includeSensitiveData is set to true, the user field is populated with reviewer information:

{
  "business_id": "RJNAeNA-209sctUO0dmwuA",
  "business_alias": "the-old-fashioned-madison",
  "business_url": "https://www.yelp.com/biz/the-old-fashioned-madison",
  "review_id": "def456",
  "review_url": "https://www.yelp.com/biz/the-old-fashioned-madison?hrid=def456",
  "rating": 4,
  "text": "Solid Wisconsin comfort food. The Friday fish fry is a must-try. Only downside is the long wait times on weekends - get there early!",
  "language": "en",
  "date": "2024-07-28",
  "images": [],
  "feedback": {
    "useful": 2,
    "funny": 0,
    "cool": 1
  },
  "businessOwnerReply": {
    "id": "reply789",
    "text": "Thanks for the kind words! We're glad you enjoyed the fish fry. Pro tip: reservations help with the weekend rush!",
    "date": "2024-07-30",
    "user": {
      "id": "owner123",
      "name": "The Old Fashioned",
      "role": "Business Owner",
      "image": "https://s3-media0.fl.yelpcdn.com/bphoto/owner/ms.jpg"
    }
  },
  "user": {
    "id": "user456",
    "url": "https://www.yelp.com/user_details?userid=user456",
    "name": "Sarah M.",
    "location": "Madison, WI",
    "image": "https://s3-media0.fl.yelpcdn.com/photo/user456/ms.jpg",
    "friendCount": 42,
    "photoCount": 15,
    "reviewCount": 87,
    "eliteYear": 2023
  }
}

How much does it cost to scrape Yelp reviews?

Yelp Business Review Scraper uses simple, transparent per-result pricing -- you only pay for the reviews you get.

$1.00 per 1,000 reviews -- each review extracted counts as one result. If you scrape 500 reviews from a business, you pay for 500 results. No hidden compute fees, no per-run charges.

Free trial: Every new Apify account comes with $5 in free platform credits -- no credit card required. That's enough to scrape 5,000 reviews at no cost, so you can fully evaluate the scraper and data quality before committing.

Enterprise plans: If you need to scrape Yelp reviews at very high volume -- tens of thousands of reviews across thousands of businesses on a regular basis -- reach out to sales@beatanalytics.org for custom Enterprise pricing with dedicated support.

Use cases for Yelp review data

Yelp review data is a rich source of unstructured text and structured metadata that powers a wide range of business and research applications. Here are the most common use cases for scraped Yelp reviews:

Sentiment analysis and NLP

Feed Yelp review text into natural language processing pipelines to measure customer sentiment at scale. Track how sentiment changes over time, identify common complaints, and compare sentiment across competitors. Yelp reviews are one of the most-used datasets in academic NLP research because of their structured star ratings paired with free-text reviews.

Reputation monitoring

Monitor your own business reviews on Yelp to catch negative feedback early and respond promptly. Set up scheduled scraping runs to get new reviews automatically and alert your team when low-rated reviews appear. Proactive reputation management can prevent small issues from becoming major PR problems.

Competitive benchmarking

Compare your review ratings, review volume, and common themes against direct competitors. Identify what customers praise about competitors that your business could improve on, and find areas where your business already excels. Bulk Yelp review download across a competitive set gives you the data foundation for strategic planning.

Product and service feedback mining

Extract specific feedback about products, menu items, or service aspects from review text. Use keyword analysis or topic modeling to identify which offerings customers love and which ones need improvement. This is especially valuable for restaurants, hotels, and service businesses where reviews are detailed and specific.

Review response strategy

Analyze how businesses in your industry respond to reviews -- which types of reviews get responses, how quickly owners reply, and what response styles correlate with improved follow-up ratings. Use this data to develop your own review response playbook.

Market research and location intelligence

Aggregate review data across businesses in a geographic area to understand market dynamics. Identify underserved neighborhoods, track emerging food trends, or measure the impact of seasonal events on business sentiment. Combine with the Yelp Business Details Scraper for a complete picture of market conditions.

Academic research

Yelp review data is widely used in academic research across fields including computer science, marketing, economics, and hospitality management. Common research applications include sentiment analysis model training, review authenticity detection, word-of-mouth dynamics, and platform economy studies.

Lead generation and sales intelligence

Identify businesses with low review scores or recurring complaints as potential leads for products or services that address those pain points. For example, a restaurant technology company could target businesses whose reviews frequently mention slow service or order errors.

Integrations and API access

You can integrate Yelp Business Review Scraper into your existing workflows using the Apify API, official SDKs, or no-code automation platforms.

Python

Use the Apify Python SDK to run the scraper and retrieve results programmatically:

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run_input = {
    "businessUrls": [
        {"url": "https://www.yelp.com/biz/the-old-fashioned-madison"}
    ],
    "language": "en",
    "sortBy": "newest",
    "maxReviews": 100,
    "includeSensitiveData": False,
}

run = client.actor("beatanalytics/yelp-business-review-scraper").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript / TypeScript

Use the Apify JavaScript SDK to integrate Yelp review scraping into your Node.js applications:

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_API_TOKEN" });

const input = {
    businessUrls: [
        { url: "https://www.yelp.com/biz/the-old-fashioned-madison" }
    ],
    language: "en",
    sortBy: "newest",
    maxReviews: 100,
    includeSensitiveData: false,
};

const run = await client
    .actor("beatanalytics/yelp-business-review-scraper")
    .call(input);

const { items } = await client
    .dataset(run.defaultDatasetId)
    .listItems();

console.log(items);

No-code integrations

Yelp Business Review Scraper integrates with popular automation platforms so you can build workflows without writing any code:

• Make (formerly Integrobot) -- connect Yelp review scraping to hundreds of other apps. Trigger scrapes on a schedule and send results to Google Sheets, Slack, email, or your CRM.
• Zapier -- create Zaps that automatically run the scraper and process the results. For example, send a Slack notification whenever new 1-star reviews are detected.
• Webhooks -- configure a webhook URL to receive results automatically when a scraping run completes. Ideal for building custom data pipelines.
• Apify API -- access all actor functionality via REST API endpoints. Schedule runs, retrieve datasets, and manage storage programmatically.

Frequently asked questions

Is it legal to scrape Yelp?

Web scraping of publicly available data is generally legal in the United States, as affirmed by the 2022 US Ninth Circuit ruling in hiQ Labs v. LinkedIn, which established that scraping publicly accessible data does not violate the Computer Fraud and Abuse Act. Yelp reviews are publicly visible on the Yelp website without requiring a login or account.

That said, you should always review Yelp's Terms of Service and consult with legal counsel if you have concerns about your specific use case. The legality of web scraping can vary by jurisdiction and intended use. Apify provides the scraping infrastructure, but users are responsible for ensuring their use of scraped data complies with applicable laws and terms of service.

How to get Yelp reviews without the API?

Yelp Business Review Scraper is the easiest way to get Yelp reviews without the API. The official Yelp Fusion API has a hard limit of 3 reviews per business, which makes it impractical for any analysis requiring a complete dataset. This scraper bypasses that limitation entirely by extracting reviews directly from Yelp business pages.

To get started: create a free Apify account, open the Yelp Business Review Scraper, paste in your Yelp business URLs, and click Start. You will have all the reviews downloaded in JSON or CSV within minutes. See How to scrape Yelp reviews for a step-by-step guide.

How many reviews can I scrape?

There is no hard limit on the total number of reviews you can scrape. The scraper extracts all reviews available on each Yelp business page. You can control the number of reviews per business using the maxReviews parameter -- set it to any number, or leave it at the default of 100.

For businesses with thousands of reviews, the scraper handles pagination automatically and fetches every page of reviews. If you need to scrape reviews from hundreds or thousands of businesses in a single run, the scraper processes them concurrently for efficient bulk extraction.

How much does it cost to scrape Yelp?

Yelp Business Review Scraper costs $1.00 per 1,000 reviews scraped. Every new Apify account includes $5 in free credits -- enough to scrape 5,000 reviews at no cost. Contact sales@beatanalytics.org for Enterprise pricing on large-scale scraping operations. See How much does it cost to scrape Yelp reviews? for more details.

What is the difference between Yelp Details and Yelp Reviews scrapers?

The two scrapers extract different types of data from Yelp:

• Yelp Business Review Scraper (this actor) extracts individual reviews -- the review text, star ratings, dates, reviewer information, photos, and business owner replies.
• Yelp Business Details Scraper extracts business-level information -- the business name, address, phone number, hours, categories, average rating, photos, attributes, and more. It also supports finding businesses via search queries and locations.

The two scrapers are complementary. A common workflow is to use the Details scraper to discover businesses (e.g., search for "pizza" in "New York"), then feed those business URLs into the Reviews scraper to extract all their reviews. Together, they provide a complete Yelp data extraction solution.

Can I filter reviews by language?

Yes. The scraper supports filtering reviews by any of 24 languages: English, Spanish, French, German, Italian, Dutch, Portuguese, Russian, Japanese, Chinese (Simplified), Chinese (Traditional), Korean, Turkish, Arabic, Danish, Finnish, Norwegian, Swedish, Hebrew, Thai, Polish, Czech, Hungarian, and Greek.

Set the language parameter to the ISO 639-1 code for your desired language (e.g., en for English, es for Spanish, fr for French). Only reviews in the selected language will be returned.

How often is the data updated?

The scraper extracts live data from Yelp every time you run it. There is no caching or stale data -- each run fetches the current state of reviews on the business page. You can schedule the scraper to run at any interval (hourly, daily, weekly) using Apify's built-in scheduling feature, ensuring your dataset always reflects the latest reviews.

What export formats are supported?

The scraper outputs data in two built-in formats: a JSON dataset (structured, nested data) and a CSV file (flattened for spreadsheets). From the Apify Console, you can additionally export the results as Excel (XLSX), XML, or HTML with a single click. The data is also accessible via the Apify API for programmatic access in any format.

Can I get reviewer information?

Yes. By default, reviewer personal information is excluded from the output for privacy. Enable the includeSensitiveData parameter (see Input parameters) to include reviewer details: display name, location, Yelp profile URL, friend count, photo count, total review count, and Yelp Elite status year.

When sensitive data is enabled, business owner reply information is also enriched with the owner's name and role.

Can I scrape reviews from multiple businesses at once?

Yes. You can add as many Yelp business URLs, aliases, or IDs as you need in a single run. The scraper processes all businesses concurrently, making bulk Yelp review download fast and efficient. There is no limit on the number of businesses per run.

Related actors

Yelp Business Details Scraper

The Yelp Business Details Scraper extracts comprehensive business information from Yelp, including business name, address, phone, hours, categories, ratings, photos, attributes, and more. It also supports discovering businesses via search queries and locations.

Common workflow: Use the Yelp Business Details Scraper to find businesses by search query (e.g., "Italian restaurants" in "San Francisco") or to enrich a list of business URLs with detailed business data. Then use the Yelp Business Review Scraper to extract all reviews for the businesses you have identified. This combination gives you a complete Yelp data extraction pipeline -- business metadata plus full review content.

For example, a market research team studying the restaurant landscape in a new city could:

1. Run the Details scraper with search queries like "restaurants", "cafes", "bars" across multiple neighborhoods
2. Filter the results by rating, review count, or category to identify the most relevant businesses
3. Feed those business URLs into the Reviews scraper to extract all customer reviews
4. Analyze review text for sentiment, common themes, and competitive strengths

This two-step approach gives you both the quantitative business data and the qualitative customer feedback needed for thorough market analysis.