Zomato Restaurant Reviews Scraper

Scrape Zomato restaurant reviews at scale - star ratings (/5), full review text, reviewer details and owner responses - plus a per-restaurant lead record (phone number, full address, GPS coordinates, cuisines, cost for two, aggregate rating). Pick a mode: Reviews (paste restaurant page URLs or bare IDs to get every review + a lead record for each) or Discovery (paste a city/locality listing URL to pull a lead record for every restaurant in that area). Every review also ships as an LLM-ready markdown block. No login, no Zomato API key.

Runs on Apify: scheduling, REST API, proxy rotation, monitoring, and one-click export to JSON, CSV, Excel or HTML.

What does Zomato Restaurant Reviews Scraper do?

Choose a mode and give it the matching input:

• Reviews mode - paste any Zomato restaurant URL or a bare restaurant ID. Returns every review plus a lead record for each restaurant.
• Discovery mode - pick a city (and optional cuisine) from the dropdowns, or paste a city/locality listing URL. Returns a lead record for every restaurant in that area (name, phone, address, geo, cuisines, cost, rating). Discovery is leads-only and does not scrape reviews - feed the restaurants it finds into Reviews mode when you want their reviews.

Output datasets:

• Reviews (Reviews mode) - one row per review: rating (/5), full text, reviewer name & profile, the restaurant's owner response, a short permalink, and an approximate date.
• Restaurant leads (both modes) - one record per restaurant: name, phone number(s), full address, latitude/longitude, cuisines, cost for two, aggregate rating, total review count and timings.

It works across India, UAE and every other market Zomato covers, and can discover every restaurant in a locality (up to 200 per listing URL) as a ready-to-import lead list.

Why scrape Zomato reviews?

• Reputation & sentiment analysis - track ratings, complaints and owner responses across your outlets or your competitors.
• Restaurant lead lists & market mapping - phone, address and GPS for every restaurant in a city or cuisine, ready for CRM import.
• AI / RAG pipelines - every review ships as a self-contained markdown block for embeddings and LLM ingestion.
• Competitive & location intelligence - cost-for-two, cuisines and rating distribution per locality.

How to scrape Zomato restaurant reviews

1. Pick a Mode. For Reviews, paste restaurant URLs (https://www.zomato.com/ncr/warehouse-cafe-connaught-place-new-delhi) or bare IDs like 301605 into Restaurant URLs or IDs. For Discovery, pick a City (and optionally a Cuisine) from the dropdowns, or paste your own locality listing URL (https://www.zomato.com/ncr/connaught-place-restaurants) into City / locality listing URLs (advanced), and set Max restaurants per listing.
2. In Reviews mode, set Max reviews per restaurant and any optional rating or date filter (or turn Scrape reviews off for a leads-only pass over your pasted URLs). In Discovery mode these are ignored - it always returns one lead per restaurant, no reviews.
3. Click Start, then download the results as JSON, CSV or Excel - or pull them from the Apify API.

Input

Field	Description
mode	reviews (default) or discovery. Picks which inputs below are used.
startUrls	Reviews mode. Restaurant page URLs or bare restaurant IDs.
city	Discovery mode. Pick a city; the actor builds and paginates its Zomato restaurants listing.
cuisine	Discovery mode. Optional: narrow the city search to one cuisine.
listingUrls	Discovery mode (advanced). Your own city/locality/collection listing URLs (used with or instead of city).
maxRestaurants	Discovery mode: how many restaurants to expand and scrape per listing (the actor paginates the listing to reach this many, up to 200).
maxReviews	Max reviews per restaurant (newest-first). Defaults to 200.
includeReviews	Reviews mode: turn off for a leads-only run (no reviews, no review charges). Discovery is always leads-only.
sortBy	Output order: newest / oldest / highest / lowest rating.
fromDate	Keep only reviews on or after this day (approximate; stops early once older reviews are reached).
minRating / maxRating	Keep reviews within a 1-5 rating range.
proxyConfiguration	Proxy settings. Defaults to Apify Residential (India) because Zomato blocks datacenter IPs; switch to datacenter to cut cost if you prefer.

Output

The default dataset holds the run's main results: in Reviews mode, one row per review (also mirrored to the reviews dataset); in Discovery mode, one restaurant lead per restaurant (also mirrored to the restaurants dataset). In Reviews mode the per-restaurant lead record is in the restaurants dataset. Download in JSON, HTML, CSV or Excel, or via the API.

{
  "restaurantId": 301605,
  "restaurantName": "Warehouse Cafe",
  "reviewId": "504560717",
  "rating": 4,
  "ratingType": "DINING",
  "reviewText": "Great ambience and food, loved the pizza and the cocktails ...",
  "timestamp": "17 hours ago",
  "reviewDate": "2026-08-30",
  "reviewerName": "Nitesh Mehra",
  "reviewerProfileUrl": "https://www.zomato.com/users/nitesh-mehra-88230886",
  "ownerResponse": { "text": "Thank you for visiting!", "author": "Warehouse Cafe" },
  "reviewUrl": "https://www.zoma.to/Avnobmn"
}

Restaurant lead record:

{
  "restaurantId": 301605,
  "restaurantName": "Warehouse Cafe",
  "restaurantUrl": "https://www.zomato.com/ncr/warehouse-cafe-connaught-place-new-delhi",
  "phones": ["+919953033368", "+919999537128"],
  "address": "D 19/20, D Block, Inner Circle, Connaught Place, New Delhi",
  "locality": "Connaught Place, New Delhi",
  "city": "New Delhi",
  "zipcode": "110001",
  "latitude": 28.6337308501,
  "longitude": 77.2210077569,
  "cuisines": ["North Indian", "Italian", "Asian"],
  "costForTwo": "₹3,000 for two people (approx.) with alcohol",
  "rating": 4.2,
  "reviewCount": 15400
}

Data fields

Field	Description
rating / ratingType	Review rating (1-5) and the experience it is for (DINING / DELIVERY).
reviewText	Full review body.
timestamp / reviewDate	Relative timestamp as shown + an approximate ISO date.
reviewerName / reviewerProfileUrl	Reviewer identity.
ownerResponse	Restaurant/management reply {text, author}.
commentCount	Number of comments on the review.
phones / address / latitude / longitude / zipcode	Restaurant contact + location (leads).
cuisines / costForTwo / rating / reviewCount / timing	Restaurant profile (leads).
markdownContent	LLM-ready per-review markdown block.

How much does it cost to scrape Zomato?

This actor uses pay-per-event pricing: a small start fee per run, plus a charge per review delivered and per restaurant lead record. On the Free plan it is $0.005 start + $0.005 per review + $0.005 per lead; per-event rates drop on higher Apify plans (as low as $0.002 each). You are never charged for a review that is filtered out or a lead that could not be fetched. Turn Scrape reviews off for a cheaper, leads-only run. See the Pricing tab for current rates. On the Apify Free plan you get monthly usage credits to try it at no cost.

Tips

• Discovery mode: set Mode to Discovery, pick a City (and optional Cuisine), or paste a locality URL (e.g. .../ncr/connaught-place-restaurants), and set Max restaurants to pull an entire area's restaurant leads (name/phone/address/geo/cuisine/cost/rating), up to 200 per listing. Discovery does not scrape reviews - feed the restaurants it finds into Reviews mode for that.
• Cheap leads run: set Scrape reviews off to collect only phone/address/geo/cuisine/cost per restaurant.
• Recent reviews only: use Reviews from to stop early once older reviews are reached (faster + cheaper).
• Schedule the actor to track new reviews over time.

FAQ

• Do I need a Zomato account or API key? No.
• Can it scrape a whole city? Yes - in Discovery mode pick a City (and optional Cuisine), or paste a listing URL. It returns a lead for every restaurant (up to 200 per listing; use several cuisines or localities to cover more). For their reviews, run those restaurants through Reviews mode.
• Is there a restaurant email? No - Zomato does not publish restaurant emails; phone, address and GPS are the available contact fields.
• Are review dates exact? Zomato shows relative timestamps ("6 months ago"), so reviewDate is an approximation computed at scrape time; the exact string is kept in timestamp.
• Can I call it from an AI agent / MCP? Yes - it is a standard Apify actor with a typed input schema, so agents and the Apify MCP server can run it directly.
• Is scraping Zomato legal? This tool collects only publicly available data. You are responsible for how you use it and for complying with Zomato's terms and applicable law.

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Support

Questions, a missing field, or a bug? Open the Issues tab on this actor's page - we read every one. If this actor helps your work, a ⭐ review on the Apify Store means a lot 🙏

Changelog

• 2026-08-30 - Initial release: reviews + per-restaurant leads + city/locality discovery, multi-event pricing, LLM-ready markdown, JSON/CSV/Excel export.