Flipkart Scraper — India Products, Prices, Discounts & Specs

Flipkart Scraper 🛒🇮🇳 — Products, Prices, Discounts, Ratings & Specs

This Flipkart scraper extracts product data from Flipkart, India's #1 online marketplace, into clean, structured records — no login, no coding. Search by keyword (or paste a Flipkart search URL) and scrape Flipkart products with title, brand, price, MRP, discount %, rating, number of ratings, review count, key specifications, warranty, availability, category and image in one run. Export to JSON, CSV, Excel, or API.

Built for price-monitoring teams, e-commerce analysts, pricing managers, competitor-intelligence researchers, marketplace sellers, affiliate publishers and data teams who need fresh Indian e-commerce data at scale.

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🔎 Why scrape Flipkart?

Flipkart is India's largest online marketplace, with hundreds of millions of listings across mobiles, electronics, fashion, appliances, home and more. Every product page carries a rich commercial picture: a selling price, the maximum retail price (MRP), a discount, a star rating, thousands of ratings and reviews, a block of key specifications and a warranty summary. That data is extremely valuable — but Flipkart has no open public product API, and the numbers change constantly as prices, offers and stock move throughout the day.

Collecting it by hand is painful: you would have to open thousands of product cards, copy prices and specs one by one, and redo the whole thing every time a sale starts. This Flipkart scraper does it for you — it reads the exact product data Flipkart server-renders into each search page and returns a clean, de-duplicated dataset you can download or feed straight into your own tools.

Common reasons people scrape Flipkart:

• 💰 Price & discount monitoring — track selling price, MRP and discount % across brands and categories over time.
• 📊 Competitor & assortment analysis — see which brands, models and price points dominate a category.
• 🧩 Catalog & price-comparison building — power comparison sites, apps and dashboards with fresh Indian e-commerce data.
• ⭐ Rating & review intelligence — rank products by rating and review volume to find bestsellers and gaps.
• 🔬 Product research — compare models at scale using the captured key specifications.
• 📈 Market research — study Indian e-commerce pricing, demand and discount behaviour.

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✨ What this Flipkart scraper does

Give it a search query (e.g. smartphone, laptop, headphones) or a Flipkart search URL, and the actor will:

• 🔎 Search Flipkart by keyword — run one or many queries in a single job.
• 📄 Paginate automatically through every result page (&page=1, &page=2, …) until it reaches your maxItems target.
• 💰 Capture the full pricing picture: selling price, mrp, discountPercent, discountAmount and currency (INR).
• ⭐ Include the rating, ratingCount (number of ratings) and reviewCount.
• 🧩 Return the key specifications (keySpecs) and a warranty summary for each product.
• 🏷️ Add brand, category, subCategory, availability and a product image.
• 🔗 Accept Flipkart search URLs so your filters and sorting are respected.
• 🧹 Deliver clean, de-duplicated records — each product appears once, keyed by its unique Flipkart product ID — with no HTML or clutter.
• ⬇️ Export to JSON, CSV, Excel, HTML, RSS/XML or via the Apify API.

Fast and reliable: a recent verification run collected 500 unique products in about 53 seconds on the default Apify datacenter proxy, with 100% coverage on the core fields (id, title, url, price, brand) and 0 duplicates. No login, no browser extensions, no manual copy-paste.

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🎯 Use cases

• Pricing managers — monitor Flipkart price and discount movements for your own and competitors' SKUs.
• E-commerce & marketplace sellers — benchmark your listings against the top results in each category.
• Price-comparison & deal sites — ingest Flipkart product data to keep listings and prices current.
• Market & category analysts — measure brand share, price bands and discount depth across a category.
• Affiliate publishers — build "best of" and deal pages ranked by discount %, rating or review volume.
• Product & sourcing teams — compare models using key specifications pulled at scale.
• Data & BI teams — feed a warehouse or dashboard with fresh Indian e-commerce data on a schedule.

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📥 Input

The actor accepts a simple, no-code input form. Provide search queries, Flipkart search URLs, or both.

Option A — by query (easiest)

{
    "searchQueries": ["smartphone", "laptop"],
    "maxItems": 500,
    "proxyConfiguration": { "useApifyProxy": true }
}

Option B — by URL (with filters / sorting)

{
    "startUrls": [
        { "url": "https://www.flipkart.com/search?q=headphones&sort=popularity" }
    ],
    "maxItems": 500,
    "proxyConfiguration": { "useApifyProxy": true }
}

Input parameters

Field	Type	Description
searchQueries	array	Keywords to search on Flipkart (e.g. laptop, smartphone, shoes, headphones). The scraper paginates each query automatically.
startUrls	array	Flipkart search URLs with filters/sorting already applied. Scraped in addition to searchQueries.
maxItems	integer	Maximum number of products to collect across all queries and URLs. Default 100.
proxyConfiguration	object	Proxy settings. Apify Proxy is enabled by default and recommended for reliable, uninterrupted results.

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📤 Output

Each product is returned as a clean, flat JSON object. Example from a live run:

{
    "id": "MOBHPP59BYSJ98M8",
    "title": "BOLTT EVO (Arctic White, 64 GB)",
    "subtitle": "4 GB RAM",
    "url": "https://www.flipkart.com/boltt-evo-arctic-white-64-gb/p/itmf046d663a1fd7?pid=MOBHPP59BYSJ98M8",
    "brand": "BOLTT",
    "price": 8999,
    "mrp": 17999,
    "discountPercent": 50,
    "discountAmount": 9000,
    "currency": "INR",
    "rating": 4.1,
    "ratingCount": 5527,
    "reviewCount": 1700,
    "keySpecs": [
        "4 GB RAM | 64 GB ROM | Expandable Upto 1 TB",
        "17.25 cm (6.79 inch) HD+ Display",
        "50MP + 2MP | 8MP Front Camera",
        "6000 mAh Lithium ion Battery",
        "T7250 Processor"
    ],
    "warranty": "1 Year Manufacturer Warranty for Device and 6 Months Manufacturer Warranty for In-box Accessories.",
    "availability": "IN_STOCK",
    "category": "Mobile",
    "subCategory": "Handset",
    "image": "https://rukmini1.flixcart.com/image/416/416/xif0q/mobile/7/t/d/-original-imahs3pd5ghzsw8e.jpeg?q=70"
}

Output fields

Field	Description
id	Unique Flipkart product ID (used as the de-duplication key).
title	Full product title.
subtitle	Short descriptor (e.g. colour / RAM / size). Present when available.
url	Direct link to the Flipkart product page.
brand	Brand name.
price	Selling price, numeric (INR).
mrp	Maximum retail price. Present for discounted items (see below).
discountPercent	Discount percentage off MRP. Present for discounted items.
discountAmount	Discount amount in INR. Present for discounted items.
currency	Currency code, e.g. INR.
rating	Average star rating (0–5).
ratingCount	Number of ratings.
reviewCount	Number of written reviews.
keySpecs	Array of the key specifications Flipkart lists for the product.
warranty	Warranty summary.
availability	Stock status, e.g. IN_STOCK, COMING_SOON.
category	Top-level category (e.g. Mobile).
subCategory	Sub-category (e.g. Handset).
image	Product image URL (served over https).

Field coverage (from a 500-product verification run): core fields id, title, url, price, brand, plus keySpecs, warranty, availability, category, subCategory and image were 100% populated; rating/ratingCount 99.8%, reviewCount 99.0%, subtitle 95.8%. The pricing-discount fields (mrp, discountPercent, discountAmount) populated for ~86% of products — they are present only when a product is discounted; items sold at MRP have no strike-through price, so these fields are legitimately absent, not missing. Empty values are omitted from each record rather than returned as null.

You can download the dataset as JSON, CSV, Excel, HTML, RSS or XML, or fetch it programmatically through the Apify API.

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🔁 Pagination & scale

The Flipkart scraper handles pagination for you. For every search query and every Flipkart search URL you provide, it walks the result pages one by one (&page=1, &page=2, …), reading every product card Flipkart server-renders into window.__INITIAL_STATE__. It keeps going until it has collected your maxItems target, runs out of results (two consecutive empty pages end that query), or reaches the internal safety ceiling (page 100 per source).

Because Flipkart categories hold tens of thousands of listings, you can realistically pull hundreds to thousands of products in a single run — just raise maxItems. Every record is de-duplicated by its unique Flipkart product ID, so the same item never appears twice even when it surfaces on multiple pages or across several queries. Combine broad queries (e.g. laptop, smartphone, shoes) in one run to build a wide, de-duplicated catalog, and use maxItems to cap cost and volume exactly where you want it. In testing the actor returned 500 unique products in ~53 seconds with zero duplicates.

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⚙️ How to use

1. Click Try for free / Start on the Apify Console.
2. Type one or more search queries — or paste a Flipkart search URL into startUrls.
3. Set maxItems to how many products you want.
4. Click Save & Start.
5. When the run finishes, open the Dataset tab and Export to JSON, CSV or Excel — or fetch it via the API.
6. Automate it: run on a schedule (daily/weekly) to keep a live price feed, or trigger it from your backend. Push results to Google Sheets, Airtable, Slack, Zapier, Make or any webhook.

Call via API (example)

curl -X POST "https://api.apify.com/v2/acts/haketa~flipkart-scraper/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{ "searchQueries": ["smartphone"], "maxItems": 500 }'

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('haketa/flipkart-scraper').call({
    searchQueries: ['laptop'],
    maxItems: 500,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

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💡 Tips

• Start narrow, then widen. Test one query with a small maxItems, confirm the fields, then scale up.
• Paste URLs for filtered pulls. Apply category, brand, price or sort filters on Flipkart and copy the resulting URL into startUrls.
• Rank by discount %. Sort or segment by discountPercent to surface the best deals in a category.
• Rank by demand. Use ratingCount and reviewCount as proxies for sales volume to find bestsellers.
• Combine queries for coverage. Pass several keywords at once — results are de-duplicated across all of them.
• Schedule for freshness. Prices and discounts change throughout the day; a scheduled run keeps your data current.

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❓ FAQ

Is scraping Flipkart legal? This actor collects only publicly available product information for lawful uses like price monitoring, market research and analytics. You are responsible for how you use the data — respect Flipkart's Terms of Service and robots.txt, and comply with all applicable laws.

Do I need a Flipkart account or API key? No. Just provide a search query or a Flipkart search URL. Flipkart has no open public product API, which is why this Flipkart scraper reads the product data Flipkart server-renders into each page.

How many products can I collect, and how fast? As many as the search returns — Flipkart categories contain tens of thousands of products. Control the volume with maxItems. A recent run collected 500 unique products in ~53 seconds.

Do I need proxies to scrape Flipkart? No manual setup — Apify Proxy is enabled by default and rotates automatically for reliable, uninterrupted results. Datacenter proxy is sufficient; you do not need residential proxies for normal runs.

Does it include discounts and MRP? Yes — selling price, mrp, discountPercent and discountAmount. These pricing-discount fields are present when a product is actually discounted; items sold at MRP have no strike-through price.

Does it include ratings, reviews and specifications? Yes — average rating, ratingCount, reviewCount, plus the keySpecs array and a warranty summary.

Is there a Flipkart API I can call? Flipkart has no public product API, but once your run finishes you get a clean dataset and a full JSON API endpoint on Apify to fetch results programmatically.

How fresh is the data? Every run reads live Flipkart pages, so prices, discounts, ratings and stock status reflect the moment the run executes. Schedule the actor to keep a continuously refreshed price feed.

Can I filter by category, brand or price? Yes. Apply the filters and sorting on Flipkart, then paste the resulting search URL into startUrls.

Are results deduplicated? Yes. Each product is uniquely identified by its Flipkart product ID and appears once per run, even across multiple pages and queries.

What export formats are supported? JSON, CSV, Excel, HTML, RSS and XML — via the Apify dashboard or the API.

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🔗 Related scrapers

Looking for more e-commerce, marketplace and B2B supplier data? Try these scrapers from the same author:

• IndiaMART Scraper — supplier listings, prices and contacts from India's largest B2B marketplace.
• TradeIndia Scraper — products, sellers and quotes from TradeIndia.
• Made-in-China Scraper — manufacturer and wholesale product data from Made-in-China.
• Woolworths Scraper — grocery and retail product prices from Woolworths.
• OfferUp Scraper — local marketplace listings, prices and seller details from OfferUp.
• YallaMotor Scraper — car listings, prices and specs from YallaMotor.

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⚖️ Legal & responsible use

This actor is intended for lawful data collection such as price monitoring, market research and analytics. You are responsible for how you use the collected data. Only collect publicly available information, respect the target website's Terms of Service and robots.txt, and comply with all applicable laws and regulations. This actor is an independent tool and is not affiliated with, endorsed by, or connected to Flipkart or its parent companies. All trademarks belong to their respective owners.

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⭐ If this Flipkart scraper saves you time, please leave a review — it really helps! Questions or feature requests? Open an issue on the actor's page.