Blinkit Scraper — Products, Prices, Stock & Delivery ETA

Turn any Blinkit search into a clean, structured dataset. Scrape live product data by keyword, by pasting Blinkit website URLs (product, category, or search deeplinks), or both — across one or more delivery locations.

Get name, brand, variant, MRP + selling price, discount, stock, inventory, merchant/store, images, and optional real-time delivery ETA — one row per product, per location. Prices and stock are hyperlocal on Blinkit (set per dark-store), so every input runs at every location you give. Pure HTTP, no browser.

Why Use This Scraper?

• ✅ Search by keyword and/or paste Blinkit URLs — products, categories, and search deeplinks are auto-classified from one input
• ✅ Multi-location by design — each query and URL runs at every delivery location, so you get true hyperlocal prices and stock
• ✅ Built for price comparison — compare the same product across cities and neighborhoods in a single run
• ✅ Full pricing on every row — selling price, MRP, and a computed discount percent
• ✅ Live availability — in-stock flag plus raw inventory count, straight from the serving dark-store
• ✅ Optional real-time delivery ETA in minutes, attached to every product
• ✅ Works from anywhere — stores are resolved from coordinates, not your IP, so location is decoupled from where the run executes
• ✅ JSON, CSV, or Excel output, ready for spreadsheets, BI tools, and pipelines

Overview

The Blinkit Scraper is built for pricing analysts, category managers, brands, and researchers who need quick-commerce data in a spreadsheet instead of tapping through a phone app, one pincode at a time.

The output is product-shaped rows — one row per product, per delivery location. Whether a row comes from a keyword search, a category deeplink, or a single product URL, it carries the same flat schema (price, MRP, stock, merchant, location), so everything lands in one clean table.

Blinkit is hyperlocal: each delivery area is served by a nearby dark-store with its own catalog, prices, and stock. That's why you supply locations — the actor geocodes each one, resolves the serving store, and reports exactly what a shopper at that address would see. It talks to Blinkit's own mobile-app API over HTTP, so it stays fast and lightweight (no browser, no rendering).

Supported Inputs

You can drive the scraper three ways — keywords, URLs, or both — and every input is run at every location.

Search queries

Plain product keywords. Each is searched on Blinkit at every delivery location.

{
  "searchQueries": ["milk", "paneer", "atta", "cold drink"]
}

Start URLs (Blinkit deeplinks)

Paste Blinkit website URLs and the actor auto-classifies each one by its shape — no tagging required.

URL type	Pattern	Example
Product	blinkit.com/prn/{slug}/prid/{id}	https://blinkit.com/prn/amul-gold-milk/prid/14639
Category	blinkit.com/cn/{slug}/cid/{l0}/{l1}	https://blinkit.com/cn/dairy-bread-eggs/cid/14/922
Search	blinkit.com/s/?q={query}	https://blinkit.com/s/?q=paneer

{
  "startUrls": [
    "https://blinkit.com/prn/amul-gold-milk/prid/14639",
    "https://blinkit.com/cn/dairy-bread-eggs/cid/14/922",
    "https://blinkit.com/s/?q=paneer"
  ]
}

startUrls accepts both plain strings ("https://…") and request objects ({ "url": "https://…" }) — mix freely. Provide searchQueries and/or startUrls.

Delivery locations

Area or locality names. Each is geocoded to coordinates, and the serving dark-store is resolved so prices and stock reflect that exact location.

{
  "locations": [
    "Koramangala, Bangalore",
    "Connaught Place, New Delhi",
    "Bandra West, Mumbai"
  ]
}

Use Cases

Audience	Use case
Pricing & category teams	Compare selling price, MRP, and discount for the same SKU across cities and neighborhoods
Brands & FMCG	Track product visibility, stock, and price by location; spot where you're out of stock or undercut
Quick-commerce & retail analysts	Monitor the live catalog of a dark-store network without an app or manual checks
Operations & logistics	Pair price with real-time delivery ETA to study serviceability and delivery performance by area
BI & data teams	Feed a clean, flat product feed into dashboards, warehouses, and reports
Researchers & ML pipelines	Bulk-export hyperlocal pricing and availability as training or automation input

How It Works

1. Input — give keywords, Blinkit URLs (or both), and one or more delivery locations
2. Geocode & resolve store — each location is geocoded to coordinates and the serving dark-store is resolved, so prices and stock are hyperlocal
3. Fetch — Blinkit's mobile-app API is queried over HTTP with a real Chrome TLS fingerprint (passes Cloudflare without a browser); search results paginate until productsLimit
4. Normalize — each product is flattened to a clean row with price, MRP, computed discount, stock, inventory, merchant, and images; optional delivery ETA is attached
5. Output — one product row per (query/URL × location), exportable as JSON, CSV, or Excel

Input Configuration

Field	Type	Required	Notes
searchQueries	array<string>	yes*	Product keywords. Each is searched at every location. *Provide this and/or startUrls.
startUrls	array<string | { url }>	yes*	Blinkit deeplinks — product, category, or search. Auto-classified. *Provide this and/or searchQueries.
locations	array<string>	yes	Delivery area/locality names. Each is geocoded and its dark-store resolved, so prices/stock are per-location.
productsLimit	integer	no	Max products per (query/URL × location). Default 45. Results are paginated until this many are collected or they run out.
includeEtaDetails	boolean	no	Default false. Fetch each location's real-time delivery ETA (minutes) and attach it to every product. Adds one request per location.
maxItems	integer	no	Hard cap on total dataset rows across all queries and locations. Default 1000.
maxConcurrency	integer	no	Max Blinkit API requests in flight at once. Default 6.
minConcurrency	integer	no	Minimum parallelism. Default 1.
maxRequestRetries	integer	no	Per-request retry budget (fresh proxy session each retry). Default 5.
proxy	object	no	Defaults to Apify Proxy. Indian residential proxies give the best reliability and correct geo.

Common scenarios

1. Compare one keyword across cities

{
  "searchQueries": ["milk"],
  "locations": ["Koramangala, Bangalore", "Connaught Place, New Delhi", "Bandra West, Mumbai"]
}

2. Several products and categories in one location, with delivery ETA

{
  "searchQueries": ["paneer", "atta"],
  "startUrls": ["https://blinkit.com/cn/dairy-bread-eggs/cid/14/922"],
  "locations": ["Koramangala, Bangalore"],
  "includeEtaDetails": true
}

3. Track specific products by URL across neighborhoods

{
  "startUrls": [
    "https://blinkit.com/prn/amul-gold-milk/prid/14639",
    "https://blinkit.com/prn/pride-of-cows-farm-cow-milk/prid/485463"
  ],
  "locations": ["Koramangala, Bangalore", "Connaught Place, New Delhi"],
  "productsLimit": 10
}

Output Overview

Each dataset item is one product row — a single product as seen at a single delivery location. The same flat schema is used no matter how the row was discovered (keyword search, category deeplink, or product URL); sourceType tells you which.

Because every input runs at every location, a single keyword across three cities yields three sets of rows — the natural shape for price comparison and availability tracking.

Notes on when fields are populated:

• location, city, locality, lat, lon, serviceable describe the resolved delivery location. If serviceable is false, Blinkit doesn't deliver there and product rows for that location may be empty.
• etaMinutes is populated only when includeEtaDetails is on; otherwise it's null.
• brand is often null — Blinkit frequently doesn't populate it in its API (see FAQ).
• discountPercent is computed from mrp and price; it's 0 when there's no discount.

Output is a flat table by default; the Apify Console "Export" tab gives JSON, CSV, or Excel.

Output Samples

Product row — keyword search, single location

{
  "query": "milk",
  "sourceType": "search",
  "sourceUrl": null,
  "location": "Koramangala, Bangalore",
  "city": "Bengaluru",
  "locality": "Koramangala",
  "lat": 12.9352,
  "lon": 77.624532,
  "serviceable": true,
  "productId": 485463,
  "merchantId": 37746,
  "name": "Pride of Cows Farm Cow Milk",
  "brand": null,
  "unit": "500 ml",
  "price": 85,
  "mrp": 85,
  "discountPercent": 0,
  "inStock": true,
  "inventory": 12,
  "imageUrl": "https://cdn.grofers.com/da/cms-assets/cms/product/42badb39-3720-4e49-8e19-980a10367928.png",
  "productUrl": "https://blinkit.com/prn/pride-of-cows-farm-cow-milk/prid/485463",
  "merchantType": "super_longtail",
  "etaMinutes": 10,
  "scrapedAt": "2026-06-24T09:20:22.378Z"
}

Key Output Fields

Source & location

• query — the keyword (or URL-derived query) this row came from
• sourceType — search, category, or product
• sourceUrl — the Blinkit deeplink, when the row came from a startUrls entry (else null)
• location — the delivery location you supplied
• city, locality — resolved from geocoding
• lat, lon — coordinates of the resolved location
• serviceable — whether Blinkit delivers to this location

Product identity

• productId — Blinkit's numeric product id
• merchantId — the serving dark-store / merchant id
• name — product display name
• brand — brand (often null; Blinkit limitation)
• unit — pack size / variant (e.g. "500 ml")
• imageUrl — product image
• productUrl — canonical Blinkit product link

Price, stock & delivery

• price — current selling price
• mrp — maximum retail price
• discountPercent — computed discount (0 when none)
• inStock — availability flag at this dark-store
• inventory — raw available quantity (when exposed)
• merchantType — store/merchant type (e.g. super_longtail)
• etaMinutes — real-time delivery ETA (with includeEtaDetails)
• scrapedAt — ISO timestamp of capture

FAQ

Do I need to log in?

No. The scraper reads publicly available Blinkit catalog data — no account, no login, no cookies required.

Is there an official Blinkit API?

No. There's no public Blinkit API. The actor talks to Blinkit's own mobile-app endpoints over HTTP — the same data the app uses to show you products, prices, and stock.

Why are prices and stock different per location?

Blinkit is hyperlocal. Each delivery area is served by a nearby dark-store with its own catalog, prices, and inventory, so the same product can have a different price — or be out of stock — a few kilometers away. That's exactly why you supply locations: each one is geocoded, the serving store is resolved, and the row reflects what a shopper at that address would see.

Can I paste Blinkit URLs instead of keywords?

Yes. Put them in startUrls. Product (/prn/{slug}/prid/{id}), category (/cn/{slug}/cid/{l0}/{l1}), and search (/s/?q={query}) deeplinks are all auto-classified. You can mix URLs and searchQueries freely — both run at every location.

Why is brand sometimes empty?

Blinkit often doesn't populate the brand field in its API response, even when the brand is obvious from the product name. When that happens, brand comes back null. The brand is usually recoverable from name if you need it downstream.

Is the delivery ETA real-time?

Yes — when includeEtaDetails is enabled, the actor fetches each location's live ETA (in minutes) at scrape time and attaches it to every product row. Leave it off and etaMinutes is null.

Does this work outside India?

Yes. Blinkit serves India, but the actor resolves dark-stores from coordinates, not from your IP or where the run executes — so you can scrape any Indian delivery location from anywhere. For best reliability and correct geo, use Indian residential proxies in the proxy setting.

How many products do I get per search?

Up to productsLimit per (query/URL × location) — default 45 — paginated until that many are collected or Blinkit runs out of results. maxItems caps the total across the whole run.

Can I export to CSV or Excel?

Yes. Output is a flat table — export it as JSON, CSV, or Excel from the Apify Console, or pull it via the API for your own pipeline.

Support

Found a bug, hit a location that won't resolve, or want another Blinkit URL kind supported? Open an issue on the actor's Issues tab, or reach out via the memo23 profile on Apify.

Additional Services

Need a custom export shape, scheduled price monitoring, or another quick-commerce source added? I build tailored scrapers and data pipelines — get in touch via the memo23 profile.

Explore More Scrapers

If you track quick-commerce, retail prices, and product availability, these pair well:

• Zepto Scraper — compare prices and stock against Blinkit on India's other 10-minute delivery app
• Amazon Product Scraper — benchmark quick-commerce pricing against marketplace listings
• Google Maps Scraper — map dark-store and retail locations by area
• Trustpilot Scraper — customer sentiment for the brands you track

Full portfolio: apify.com/memo23.

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⚠️ Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Blinkit, Blink Commerce Private Limited, Zomato Limited (Eternal Limited), or any of their parent companies or subsidiaries. All trademarks mentioned are the property of their respective owners.

The scraper accesses only publicly available Blinkit product and catalog data — no authenticated endpoints, private accounts, or content behind a login. Users are responsible for ensuring their use complies with Blinkit's Terms of Service, applicable data-protection law (GDPR, CCPA, India's DPDP Act, etc.), and any contractual obligations of their own organization. Prices, stock, and availability are point-in-time snapshots that change continuously and per location — verify against the live app before relying on them for commercial decisions.

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