Blinkit Product & Price Scraper — MRP, Discount & Stock

Blinkit Scraper — Product, Price, MRP, Discount & Stock Data

Scrape Blinkit — India's #1 quick-commerce grocery app (owned by Zomato/Eternal) — as clean, structured data. This Blinkit scraper searches any keyword for the delivery city you choose and returns every product with name, brand, pack size, selling price, MRP, discount %, stock status, inventory, rating, store/merchant and image — no login, no coding, no browser automation to babysit. Because Blinkit prices and availability are store-specific, you pick the city (or exact coordinates) and get live, per-store Blinkit data.

Export to JSON, CSV, Excel, or API.

Built for price-monitoring and e-commerce teams, FMCG and D2C brands, quick-commerce analysts, market researchers, and data engineers who need live Blinkit product and pricing data by location.

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🔎 Why scrape Blinkit?

Blinkit (formerly Grofers) is one of India's largest quick-commerce platforms, delivering groceries and daily essentials in minutes across major metros. Its catalog, pricing, discounts and stock change constantly and vary store-by-store — which makes it one of the richest live datasets for understanding Indian grocery and FMCG retail. But that same volatility makes manual tracking impossible: prices move during the day, products sell out, and what you see depends entirely on the delivery location.

A Blinkit scraper turns that moving target into a clean, repeatable dataset. Instead of copy-pasting from the app, you get every product in a search as a typed record — prices as numbers, MRP and discount percentage computed, stock and inventory flagged — ready for spreadsheets, databases and BI tools. Schedule it and you have a price-history and availability feed for the categories, brands and cities you care about.

Because scrape Blinkit jobs are per-store, you can run the same keywords across Mumbai, Delhi, Bangalore and more in a single run and compare pricing and assortment across locations — something no single app session can show you.

Common reasons people scrape Blinkit:

• Price monitoring — track selling price, MRP and discounts over time for your SKUs and competitors'.
• Competitor & market research — compare quick-commerce pricing and assortment across cities and apps.
• Brand & category analysis — see how a brand's range is priced, discounted and stocked on Blinkit.
• Availability & out-of-stock tracking — monitor whether key products are in stock per store.
• FMCG & D2C intelligence — benchmark your listings, pack sizes and price points on the shelf.
• MAP / pricing-compliance checks — spot where products are sold below expected price.
• Dashboards & data products — build clean datasets of the Indian quick-commerce catalog.

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✨ What this Blinkit scraper does

• ✅ Keyword search, any city — enter product terms (e.g. milk, chips, atta) and pick one or more delivery cities; the Blinkit scraper queries each store.
• ✅ Per-store pricing — Blinkit prices, discounts and stock are location-specific. Choose a city from the list or pass exact latitude/longitude to target any store.
• ✅ Multi-city in one run — scrape several cities at once to compare prices and availability side by side.
• ✅ Automatic pagination — follows Blinkit's cursor (postback_params) through result pages and returns large, de-duplicated result sets, bounded by your maxItems and maxPagesPerSearch limits.
• ✅ Rich product fields — captures productId, name, brand, packSize, price, mrp, discountPercent, currency, rating, inStock, inventory, merchantType, merchantId, eta, image and productUrl, plus the searchQuery, city and scrapedAt timestamp for each record.
• ✅ Clean, typed output — prices and MRP parsed from ₹ strings into numbers (INR); discount % computed; stock as a boolean.
• ✅ No browser, fast & cheap — pure JSON API access with a browser-grade TLS fingerprint (Impit) that clears Cloudflare, so runs are quick and low-cost (a 12-product sample finishes in ~4 seconds).
• ✅ Reliable transport — datacenter-first with automatic fallback to Indian residential proxies and up to 6 retries with session rotation.
• ✅ Export anywhere — JSON, CSV, Excel, HTML, or straight from the Apify API and integrations.

Only the fields and modes above are claimed — they all come from the live Blinkit layout API.

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🎯 Use cases

• Pricing & revenue teams — monitor Blinkit selling price vs. MRP and track discount depth across cities.
• FMCG & CPG brands — see how your products (and competitors') are priced, bundled and stocked on quick-commerce shelves.
• D2C founders — benchmark your Blinkit listing against category leaders by pack size and price point.
• Market researchers & analysts — build live datasets of the Indian quick-commerce grocery catalog.
• Category managers — track assortment, new launches and out-of-stock rates per store.
• Quant & data teams — feed structured Blinkit data into dashboards, price-history models and alerts.
• Agencies & consultancies — deliver pricing and availability intelligence to retail clients.
• Deal & coupon sites — surface the biggest live discounts by filtering on discountPercent.

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📥 Input

Configure the run from the Apify Console UI or via the API. The main inputs:

Field	Type	Description
searchQueries	array of strings	Product terms to search on Blinkit (e.g. milk, chips, chocolate, atta).
cities	array of strings	Delivery cities whose store to scrape. Options: Mumbai, Delhi, Bangalore, Hyderabad, Chennai, Pune, Kolkata, Gurgaon. Prices/stock are per-store.
latitude	string	Optional exact delivery latitude. When set with longitude, overrides cities.
longitude	string	Optional exact delivery longitude. Pairs with latitude to target any store.
maxItems	integer	Stop after collecting this many products (across all keywords and cities).
maxPagesPerSearch	integer	Maximum result pages to fetch per keyword (default 5).
proxyConfiguration	object	Proxy settings. Indian residential proxy is recommended (default); the actor uses datacenter first and falls back to Indian residential automatically.

Example — several products in Mumbai

{
  "searchQueries": ["milk", "chips", "chocolate"],
  "cities": ["mumbai"],
  "maxItems": 300,
  "maxPagesPerSearch": 5,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "IN"
  }
}

Example — compare two cities

{
  "searchQueries": ["atta", "oil"],
  "cities": ["mumbai", "delhi"],
  "maxItems": 500
}

Example — target exact coordinates

{
  "searchQueries": ["chocolate"],
  "latitude": "12.9716",
  "longitude": "77.5946",
  "maxItems": 200
}

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📤 Output

Each Blinkit product is one dataset item. A real sample from a live run:

{
  "productId": "637875",
  "name": "Country Delight Cow Milk",
  "brand": "Country Delight",
  "packSize": "450 ml",
  "price": 47,
  "mrp": 48,
  "discountPercent": 2,
  "currency": "INR",
  "rating": 4.5,
  "inStock": true,
  "inventory": 9,
  "merchantType": "express",
  "merchantId": "41649",
  "eta": "earliest",
  "image": "https://cdn.grofers.com/da/cms-assets/cms/product/b91b3590-34ae-4f9b-a53a-6951452fb937.png",
  "productUrl": "https://blinkit.com/prn/x/prid/637875",
  "searchQuery": "milk",
  "city": "mumbai",
  "scrapedAt": "2026-10-25T12:49:40.209Z"
}

Field reference

Field	Description
productId	Blinkit product ID.
name	Product display name.
brand	Brand name.
packSize	Variant / pack size (e.g. 450 ml, 500 g).
price	Current selling price in INR (numeric).
mrp	Maximum retail price in INR (falls back to price when Blinkit returns no separate MRP).
discountPercent	Discount off MRP, computed; 0 when there is no discount.
currency	Always INR.
rating	Product rating (number), present when Blinkit shows one.
inStock	true/false stock status for the selected store.
inventory	Available quantity for the store, present when Blinkit returns it.
merchantType	Fulfilling store type (e.g. express).
merchantId	Fulfilling store / merchant ID.
eta	Delivery ETA identifier (e.g. earliest).
image	Product image URL.
productUrl	Canonical Blinkit product page URL.
searchQuery	The keyword that returned this product.
city	The delivery city (or lat,lon) used — prices are per store.
scrapedAt	ISO timestamp when the record was collected.

Core fields (productId, name, brand, packSize, price, mrp, discountPercent, inStock, rating, image, productUrl, city) populate on essentially every product. A few fields are present when available — inventory and rating depend on what Blinkit returns for that item and store.

Prices are per store. Blinkit prices, discounts and stock depend on the delivery location, so the same product can differ between cities. Always set the cities (or coordinates) you want to monitor.

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🔁 Pagination & scale

The Blinkit scraper paginates automatically. For each keyword it calls the Blinkit layout search API, reads the product cards, then follows the server's cursor (postback_params) to request the next page — repeating until there are no more results, the cursor runs out, or your limits are reached. Pagination is bounded by two inputs:

• maxPagesPerSearch — how many result pages to fetch per keyword (default 5).
• maxItems — a hard cap on total products across all keywords and cities.

Records are de-duplicated per store using a city:productId key, so running multiple keywords (or the same keyword across cities) never produces duplicate rows for the same store. Scale up by adding more keywords, more cities and raising maxItems; the actor runs HTTP-only (no browser) with retry and proxy-session rotation, so large pulls stay fast and inexpensive.

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⚙️ How to use

1. Open the actor on the Apify Console and click Try for free.
2. Enter one or more search keywords and pick your delivery cities (or set exact latitude/longitude).
3. Set Maximum products (maxItems) and, if needed, Max pages per keyword.
4. Keep the recommended Indian residential proxy and click Start.
5. When the run finishes, export the dataset as JSON, CSV, Excel or HTML — or pull it via the Apify API.
6. Automate it: run on a schedule to build price history, or push results to Make, Zapier, Google Sheets, a webhook, S3 and more.

You can also start runs and fetch the dataset programmatically through the Apify API for full integration into your own pipeline.

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💡 Tips

• Pick the right cities — prices and stock are store-specific, so set the exact cities (or coordinates) you want to monitor.
• Use several keywords to cover a whole category or a brand's full range in one run.
• Compare cities — add multiple cities to see price and stock differences across stores.
• Pull broadly, filter later — collect a wide set, then filter the dataset on discountPercent, inStock, brand or city.
• For niche locations, use latitude/longitude to hit a specific store the city presets don't cover.
• Schedule daily runs to build a Blinkit price-history and out-of-stock dataset over time.

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❓ FAQ

Is scraping Blinkit legal? This actor collects publicly available product and pricing information for legitimate business uses such as price monitoring, market research and analysis. You are responsible for how you use the data and for complying with applicable laws, regulations and the website's terms. Don't use the output to infringe intellectual-property rights or for any unlawful purpose.

Do I need a Blinkit account, API key or login? No. There is no login and no coding. You just enter keywords and pick cities — the Blinkit scraper handles everything else.

Is there an official Blinkit API? Blinkit does not offer a public product/pricing API. This actor acts as a practical Blinkit API: it reads Blinkit's own JSON layout endpoints and returns clean, structured records you can call programmatically via the Apify API.

Why do I have to choose a city? Blinkit prices, discounts and stock are set per delivery store, so results are tied to a city or location. Pick the city (or coordinates) you care about, or run several at once to compare.

How many results can I get and how fast is it? It depends on the keyword and city, but the actor paginates through all available result pages up to your maxItems / maxPagesPerSearch limits. It's HTTP-only (no browser), so it's fast and cheap — a 12-product sample finishes in about 4 seconds.

Do I need proxies? Yes — Blinkit is geo-restricted and behind Cloudflare, so an Indian residential proxy is recommended (and set by default). The actor tries datacenter first and falls back to Indian residential automatically, with retries and session rotation.

Are MRP and discounts included? Yes. Every product includes the current selling price, the mrp, and a computed discountPercent so you can spot deals and track discount depth.

Is stock information available? Yes. inStock reflects availability at the selected store, and inventory gives the quantity when Blinkit returns it.

In what formats can I export the data? Structured JSON by default, plus CSV, Excel and HTML, or straight from the Apify API and its integrations.

How fresh is the data? It's scraped live at run time (each record carries a scrapedAt timestamp). Schedule the actor to keep a continuously refreshed price and availability feed.

Can I filter by brand, discount or stock? The actor searches by keyword and city; for brand, discount or stock filtering, pull the data and filter the dataset on brand, discountPercent or inStock — these fields are included on every record.

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🔗 Related scrapers

• Woolworths Scraper — AU Prices, Specials & Unit Price
• Coles Scraper — Prices, Specials, Stock & Catalog

Need another grocery or quick-commerce source? These price and catalog scrapers follow the same clean, structured output model.

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Ready to scrape Blinkit? Enter your keywords, pick your cities and click Start — get live Blinkit product and price data as JSON, CSV or Excel in seconds.