⚡ Blinkit Products & Prices Scraper

Extract live Blinkit products, prices, discounts, stock levels, delivery ETAs and ratings — across any Indian location.

🔎 Search products · 💰 Track prices · 📦 Check stock · 📍 Compare locations · ⚡ Fast extraction

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🛒 Products	Search terms, whole categories, or specific product URLs
💰 Pricing	Price, MRP, discount amount & percent, price per 100 g/ml
📦 Availability	Stock status plus live inventory counts per store
🚚 Delivery	Location-specific delivery ETA in minutes
📍 Locations	City name, 6-digit PIN code, or exact coordinates
📊 Comparison	The same product priced across as many locations as you like

📍 Blinkit prices are set per dark store — not nationally

In a verified three-city run, 26 of the 69 products found in more than one city were priced differently, and stock diverged completely:

Product	Delhi	Mumbai	Bengaluru
English Oven Zero Maida Multigrain Bread	₹70	₹65	₹70
Amul Moti Toned Milk	₹33	—	₹30
Amul Taaza Toned Milk	Out of stock	12 in stock	—

A national average would hide every one of these. This Actor returns one row per product per location, so the gaps stay visible.

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🚀 Get started in seconds

Paste this, click Start, and you'll have products in about 8 seconds:

{
  "searchQueries": ["chocolate"],
  "locations": ["Delhi"]
}

That's the whole setup — no account, no login, no cookies, nothing to configure. To compare cities, just add more locations:

{
  "searchQueries": ["amul milk"],
  "locations": ["Delhi", "Mumbai", "560001"],
  "maxResults": 100
}

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What you can use it for

• Price monitoring — track competitor pricing on FMCG products over time
• Multi-city price comparison — quantify how the same SKU is priced across metros
• Stockout tracking — live per-store inventory counts, not just an in/out flag
• Discount monitoring — find where the MRP-to-price gap is widening
• Brand monitoring — follow your own products' listings, ratings and shelf presence
• Catalogue extraction — pull an entire Blinkit category for market research

What makes this different

	This Actor	Typical Blinkit scrapers
Discounts	Numeric discountAmount and discountPercent	A text badge like "10% OFF" you have to parse
Pack sizes	Parsed to unitQuantity + unitMeasure, plus price per 100 g/ml	Raw string only
Paid placements	Flagged with isSponsored	Mixed silently into results
Inputs	Search and categories and product URLs	Usually search only
Locations	City name, PIN code, or coordinates	Often raw latitude/longitude only
Missing data	Reported as null	Sometimes zero-filled or invented

Why isSponsored matters

Blinkit injects paid placements into results, heavily concentrated at the top. Measured across 1,000 products collected by this Actor:

Result positions	Share that are ads
1–12 (first screen)	58%
13–24	47%
25–50	32%
51–100	5%
100+	0%

If you sample the first page to measure share of shelf or organic ranking and can't tell ads apart, more than half your sample is advertising rather than ranking.

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How it works

1. You give it search terms, categories or product URLs, plus one or more locations.
2. Each location is resolved to coordinates and checked against Blinkit's serviceability API. Unserviceable locations are reported and skipped — the run carries on.
3. For each location, the Actor collects products exactly as a customer in that area would see them, following Blinkit's own pagination.
4. Rows are normalised, de-duplicated per location, and streamed to your dataset.

There is no browser involved, which is why runs are measured in seconds and fit comfortably in 256 MB.

Input

Everything is optional — the defaults run as-is. Provide at least one of search terms, categories or product URLs.

Field	Type	Default	What it does
searchQueries	array	["chocolate"]	Search terms, e.g. Amul milk, Red Bull
locations	array	["Delhi"]	City, PIN code, or "28.6139,77.2090"
maxResults	integer	50	Max products per location
categories	array	[]	Category name (ice cream) or a Blinkit category URL
productUrls	array	[]	Specific Blinkit product links
brandFilter	array	[]	Keep only these brands
includeOutOfStock	boolean	true	Keep products the store has run out of
includeSponsored	boolean	true	Keep paid placements (always flagged)
maxRequestRetries	integer	3	Retries before giving up on a request
proxyConfiguration	object	Apify residential	Pre-configured; see Proxies

Output

One row per product, per location.

Field	Type	Description
productId	string	Blinkit's stable SKU id
name · brand	string	Product name and brand
subcategory	string	Blinkit's product type, e.g. Potato Chips
price · mrp	number	Selling price and maximum retail price, in INR
discountAmount · discountPercent	number	Calculated from MRP and price
packSize	string	As shown by Blinkit, e.g. 500 ml, 4 x 250 ml
unitQuantity · unitMeasure	number · string	Pack size normalised to grams or millilitres
pricePerUnit · pricePerUnitBasis	number · string	Price per 100 g / 100 ml, for fair comparison
availability · stockStatus	boolean · string	Whether it can be bought right now
inventoryCount	integer	Units on hand at that dark store
deliveryEtaMinutes	integer	Delivery estimate for that store
rating	number	Average customer rating, 0–5
isSponsored	boolean	true for Blinkit paid placements
productUrl · imageUrl · imageUrls	string · array	Links and images (up to 5)
variantGroupId	string	Links variants of the same product
merchantId · merchantType	string	Which dark store served this price
location · cityName · pincode	string	The location this row was priced for
latitude · longitude	number	Coordinates used
source · sourceTerm	string	Whether the row came from a search, category or product URL — and which one
currency	string	INR
scrapedAt	string	ISO 8601 UTC timestamp

Example output

{
  "productId": "212722",
  "name": "Nestle KitKat 4 Fingers Choco Coated Wafer Bar",
  "brand": "Nestle KitKat",
  "subcategory": "Chocolates",
  "price": 30.0,
  "mrp": 30.0,
  "discountAmount": 0.0,
  "discountPercent": 0.0,
  "currency": "INR",
  "packSize": "38.5 g",
  "unitQuantity": 38.5,
  "unitMeasure": "g",
  "pricePerUnit": 77.9221,
  "pricePerUnitBasis": "per 100 g",
  "availability": true,
  "stockStatus": "in_stock",
  "inventoryCount": 50,
  "deliveryEtaMinutes": 13,
  "rating": 4.72,
  "isSponsored": false,
  "productUrl": "https://blinkit.com/prn/nestle-kitkat-4-fingers-choco-coated-wafer-bar/prid/212722",
  "imageUrl": "https://cdn.grofers.com/da/cms-assets/cms/product/....png",
  "variantGroupId": "1097667",
  "merchantId": "36778",
  "merchantType": "express",
  "location": "Delhi",
  "cityName": "Delhi",
  "pincode": null,
  "latitude": 28.6139,
  "longitude": 77.209,
  "source": "search",
  "sourceTerm": "chocolate",
  "scrapedAt": "2026-08-27T14:31:05+00:00"
}

The dataset ships with four ready-made views: Products & prices, Compare across locations, Discounts & unit economics, and Search placement (which flags paid placements alongside organic results).

To exclude paid placements from the data altogether, set includeSponsored to false in the input. Dataset views select columns rather than filtering rows, so the filtering happens at collection time.

More examples

Track one product across cities — the fastest way to see location pricing:

{
  "productUrls": ["https://blinkit.com/prn/amul-gold-milk/prid/14639"],
  "locations": ["Delhi", "Mumbai", "560001"],
  "maxResults": 10
}

Monitor your brand inside a category, excluding ads:

{
  "categories": ["chips"],
  "brandFilter": ["Lay's", "Bingo"],
  "locations": ["Gurugram"],
  "maxResults": 300,
  "includeSponsored": false
}

Pull a whole category catalogue for one city:

{
  "categories": ["https://blinkit.com/cn/munchies/cid/1237/940"],
  "locations": ["Mumbai"],
  "maxResults": 2000
}

Multi-location scraping

Blinkit assigns every customer a dark store from their coordinates, and that store sets the price, the stock and the delivery time. Specify a location three ways:

Input	Example	Resolves to
City name	Mumbai	City centre
PIN code	110001	The PIN's city
Coordinates	19.1176,72.9060	That exact point

City names and PIN codes resolve to a city-level point, which is enough to reach the right city's store. For a specific neighbourhood's store, pass coordinates.

Because pricing is per store, rows are de-duplicated per location: one SKU scraped for three cities gives three rows. That is what makes the comparison possible.

Proxies

Blinkit refuses connections from data-centre IP ranges, so runs use Apify residential proxies. This is already configured in the default input and you should not need to touch it.

Residential traffic is billed by Apify separately from this Actor's price. Responses are compressed, so 1,000 products moves only about 1 MB — well under a cent.

Performance

Measured on the Apify platform at 256 MB:

Run	Products	Time
Default, 1 location	50	7–19 s
3 locations × 100	300	30 s
1 location × 1,000	1,000	2 min 6 s

Rows stream to the dataset in batches, so memory stays flat no matter how large maxResults is.

Pricing

Event	Price
Actor start	$0.00005
Per product scraped	$0.0015

1,000 products costs about $1.50, plus a fraction of a cent in residential proxy traffic. You are charged per product actually written to your dataset — a run that finds nothing costs only the start fee.

Limitations

• No review counts. Blinkit's web API publishes an average rating but no number of reviews, so that field is not offered rather than shipped permanently empty.
• No top-level category field. Blinkit leaves its category hierarchy blank in the responses used here, so it is omitted. subcategory (its product type, e.g. Potato Chips) is populated on essentially every row, and sourceTerm records which category a row came from.
• One store per location. Prices reflect the dark store Blinkit assigns to those coordinates, not a city-wide average.
• Out-of-stock products may have no price. Blinkit reports 0 for products a store isn't selling; that is returned as null, not as free.
• City and PIN inputs are city-level. Use coordinates for neighbourhood precision.
• Ambiguous category names are rejected, not guessed. If a name could mean several categories, the run lists the candidates instead of silently scraping the wrong one. Paste a category URL when in doubt.
• Blinkit operates only in India, and only in the cities it serves.

FAQ

Do I need a Blinkit account? No. Only publicly accessible catalogue data is collected — no login, no cart, no personal data.

Why did I get fewer products than maxResults? Blinkit ran out of matching results for that term at that store. maxResults is a ceiling, not a target.

Can I compare one SKU across cities? Yes — put its URL in productUrls and list several locations.

Why are some rows marked isSponsored? Blinkit injects paid placements into results. They're kept and flagged by default; set includeSponsored: false to drop them.

How do I find a category URL? Open the category on blinkit.com and copy the address — it looks like https://blinkit.com/cn/munchies/cid/1237/940.

How often should I run it? Quick-commerce pricing moves daily. Most price-monitoring users schedule a daily run; stockout tracking benefits from a few runs a day.

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Collects publicly accessible data only. Blinkit is a trademark of its respective owner; this Actor is not affiliated with or endorsed by Blinkit. You are responsible for ensuring your use of the data complies with applicable laws and Blinkit's terms.