Blinkit Scraper

Pull live product, price, and availability data from Blinkit — India's 10-minute instant-grocery service — including selling price, MRP, discount, pack size, in-stock status, delivery ETA, ratings, and product images, all priced for the exact delivery location you choose. Built for q-commerce competitive-intelligence teams, FMCG brands monitoring shelf price and stock, and grocery-price analysts who need accurate store-level Blinkit data across Indian cities without building and maintaining their own collector.

Why This Scraper?

• Location-accurate pricing for any delivery point — Blinkit prices, stock, and delivery times change store-by-store; this actor returns the real local price for the city or coordinates you pick, verified across Delhi, Mumbai, and Bangalore (the same milk priced differently in each).
• City picker with 10 named Indian metros — Delhi, Mumbai, Bangalore, Hyderabad, Chennai, Kolkata, Pune, Ahmedabad, Gurgaon, and Noida — no coordinate hunting required.
• Pinpoint custom coordinates — switch the city picker to Custom and enter an exact latitude/longitude to scrape a specific neighborhood's serving store.
• Batch keyword search — queue many search terms in one run (e.g. "milk", "amul butter", "maggi noodles"); each term runs as its own search with its own result cap.
• Selling price, MRP, and discount on every row — current price (₹), original MRP (₹), and a derived discount % (null when there's genuinely no discount, never a fake 0%).
• Pack-size and availability fields — exact unit ("500 ml", "1 kg", "6 pcs"), a true/false in-stock flag for the chosen store, and the live delivery ETA window.
• Ratings, image, product ID, and canonical URL — average rating, rating count (parsed cleanly from Indian-style "13 lac"/"1.2k" formats), product image, Blinkit product ID, and a ready-to-open product link per row.
• Paste Blinkit search or category URLs — drop in any blinkit.com/s/?q=... search link or /cn/.../cid/... category page; in-URL filters are applied automatically.
• Automatic deduplication — results are deduped by product ID across pages, so overlapping loads never produce duplicate rows.

Use Cases

Q-commerce Competitive Intelligence

• Track Blinkit's catalog and prices against Zepto, Instamart, and BigBasket
• Monitor instant-delivery ETAs by city to benchmark fulfillment speed
• Map which SKUs a competitor stocks in each metro
• Spot assortment gaps between dark stores in different cities

FMCG Brand Price Monitoring

• Watch your own products' selling price and MRP on Blinkit shelves
• Detect unauthorized discounting or price erosion across regions
• Verify in-stock status of your SKUs at store level
• Compare your pack sizes and pricing against rival brands

Market & Pricing Research

• Build product price datasets across Delhi, Mumbai, Bangalore, and 7 more metros
• Study regional brand presence (e.g. Nandini in Karnataka, Gokul in Maharashtra)
• Track discount depth and MRP-to-price gaps by category
• Feed dynamic-pricing models with real store-level grocery data

Availability & Assortment Tracking

• Monitor stock-outs of high-velocity SKUs by delivery area
• Track when new products appear in a category
• Measure delivery-time promises across neighborhoods
• Audit catalog breadth for a brand or category over time

Getting Started

Simple Keyword Search

Search a single term in the default city (Delhi):

{
    "searchTerms": ["milk"],
    "maxResults": 50
}

Compare One Product Across Cities

Run the same term in different metros to compare regional pricing — launch a run per city:

{
    "searchTerms": ["amul butter", "maggi noodles"],
    "city": "mumbai",
    "maxResults": 100
}

Category URL with Custom Coordinates

Paste a Blinkit category URL and target an exact neighborhood by coordinates:

{
    "startUrls": ["https://blinkit.com/cn/dairy-bread-eggs/cid/14/922"],
    "city": "custom",
    "latitude": "12.9716",
    "longitude": "77.5946",
    "maxResults": 200
}

Input Reference

What to Scrape

Parameter	Type	Default	Description
searchTerms	string[]	["milk"]	Products to search for, one per line (e.g. "milk", "amul butter", "maggi noodles"). Each term runs as its own search.
startUrls	string[]	[]	Blinkit search or category URLs (e.g. https://blinkit.com/s/?q=milk or a category page link). Filters in the URL are applied automatically. Leave empty if you only use Search Terms.

Delivery Location

Parameter	Type	Default	Description
city	select	Delhi	The city to scrape from. Choose Delhi, Mumbai, Bangalore, Hyderabad, Chennai, Kolkata, Pune, Ahmedabad, Gurgaon, Noida, or "Custom (use coordinates below)". Prices and stock depend on the delivery area.
latitude	string	""	Exact delivery latitude (e.g. 28.6139). Only used when City is set to Custom.
longitude	string	""	Exact delivery longitude (e.g. 77.2090). Only used when City is set to Custom.

Options

Parameter	Type	Default	Description
maxResults	integer	100	Maximum number of products to collect for each search term or URL. Set to 0 for no limit. Start with 20-50 to test, then increase.

Output

Each product is one flat row in the dataset. Here's a representative result:

{
    "name": "Amul Taaza Toned Fresh Milk",
    "brand": "Amul",
    "price": 31,
    "mrp": 33,
    "discountPercent": 6,
    "unit": "500 ml",
    "inStock": true,
    "deliveryTime": "12 mins",
    "imageUrl": "https://cdn.grofers.com/app/images/products/sliding_image/amul-taaza.jpg",
    "productId": "14258",
    "category": "dairy bread eggs",
    "rating": 4.6,
    "ratingCount": 3685,
    "searchTerm": "milk",
    "sourceUrl": null,
    "url": "https://blinkit.com/prn/amul-taaza-toned-fresh-milk/prid/14258",
    "location": {
        "city": "Delhi",
        "latitude": 28.6139,
        "longitude": 77.209
    },
    "scrapedAt": "2026-05-29T14:30:00Z"
}

Product Fields

Field	Type	Description
name	string	Product display name
brand	string | null	Brand name
price	number | null	Current selling price in INR (₹)
mrp	number | null	Maximum Retail Price (original price) in INR (₹)
discountPercent	number | null	Discount percentage off MRP; null when there is no genuine discount
unit	string | null	Pack size / quantity (e.g. "500 ml", "1 kg", "6 pcs")
inStock	boolean	Whether the product is available at the chosen delivery location
deliveryTime	string | null	Estimated delivery window (e.g. "12 mins")
imageUrl	string | null	Product image URL
productId	string | null	Blinkit product / variant ID
category	string | null	Category grouping (set for category URLs; null for keyword searches)
rating	number | null	Average customer rating
ratingCount	integer | null	Number of ratings
searchTerm	string | null	The search term that produced this row (null for URL inputs)
sourceUrl	string | null	The input URL that produced this row (null for keyword inputs)
url	string | null	Canonical Blinkit product URL
location	object	The delivery location used for this row: city, latitude, longitude
scrapedAt	string	ISO 8601 timestamp of collection

Tips for Best Results

• Set the city closest to your target market — Blinkit prices, stock, and delivery times are store-specific, so the delivery location you pick determines the data you get.
• Run the same term across multiple cities to compare regional pricing — launch one run per city (e.g. Delhi vs. Mumbai vs. Bangalore) and join the results on product name to see local price gaps and regional-only brands.
• Use Custom coordinates for a precise neighborhood — set City to Custom and paste an exact latitude/longitude (right-click a spot in Google Maps to copy them) when a city-center point isn't where you want to measure.
• Start small, then scale — set maxResults to 20-50 on your first run to confirm the data matches your needs, then raise it or set 0 for no limit.
• Batch your keywords — list many search terms at once; maxResults applies per term, so a 3-term run at 50 each returns up to 150 rows.
• Read discountPercent correctly — it's null (not 0) when the selling price equals MRP, so filtering on a non-null value gives you only genuinely discounted products.
• Mix keywords and URLs — combine Search Terms and Blinkit category/search URLs in a single run; the searchTerm and sourceUrl fields tell you which input produced each row.

Pricing

$1.90 per 1,000 results — slightly under the market rate for Blinkit data, with no compute charges to track.

Results	Estimated Cost
100	$0.19
1,000	$1.90
10,000	$19.00
100,000	$190.00

A "result" is any product row in the output dataset. No compute charges — you only pay per result returned.

Integrations

Export data in JSON, CSV, Excel, XML, or RSS. Connect to 1,500+ apps via:

• Zapier / Make / n8n — Workflow automation
• Google Sheets — Direct spreadsheet export
• Slack / Email — Notifications on new results
• Webhooks — Trigger custom APIs on run completion
• Apify API — Full programmatic access

Legal & Ethical Use

This actor is designed for legitimate price research, competitive analysis, and market intelligence on publicly available product listings. Users are responsible for complying with applicable laws and Blinkit's Terms of Service. Do not use extracted data for spam, harassment, or any illegal purpose. Extract only publicly visible catalog data and respect personal-data regulations.