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Flipkart Price Tracker — Product Price, Rating & Search Result API

Track public Flipkart India product search results by keyword. Export structured marketplace records with title, brand, INR price, discount text, rating, review count, availability signals, image, seller when exposed, product URL, source URL, query, and rank. Returns clean JSON / CSV / Excel for India ecommerce price monitoring, offer tracking, category research, and AI shopping workflows.

TL;DR (40-word answer): Flipkart Price Tracker is a no-login Apify Actor for public Flipkart India search-result data. It returns normalized records with INR price, discount text, rating, reviews, availability, source URL, query, and rank. Pricing uses the result event from $0.0086 per result. Last updated 2026-06-29.

What it is NOT: Flipkart Price Tracker is not a checkout bot, seller API, or private Flipkart account tool. It reads public Flipkart search results and keeps platform-provided ranking and product signals.

Flipkart Price Tracker is an Apify Actor that accepts keyword, country, and max_results, then exports a source-linked product dataset with standardized fields for analysis. It keeps the user's query visible in query, preserves public source context in source_url, and does not hide platform-specific ranking behavior behind artificial sorting. Maintained by TrueFetch on the Apify Store.

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🛒 Why choose Flipkart Price Tracker

Flipkart Price Tracker is best for India ecommerce sellers, marketplace researchers, deal aggregators, and AI agents that need current Flipkart search data with price, discount, and ranking context intact.

• India-focused input surface: country is India and results come from Flipkart public search.
• Flipkart offer context stays visible through INR price, discount text, rating, review count, seller, availability text, and original result rank when those signals are exposed.
• Fields cover title, brand, price, INR currency, discount text, rating, review count, stock text, seller, image, product URL, and source URL when available.
• query, rank, platform, site, and country make each product row traceable back to the user input and Flipkart result page.
• Output uses the same normalized product schema as the rest of the TrueFetch shopping actors.
• Pay-per-result pricing uses the result event, so billing maps to exported records.

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🚀 Quick Start — run in 3 steps

Run in Apify Console

1. Open the Actor — go to Flipkart Price Tracker on Apify and click Try for free.
2. Configure inputs — enter keyword, choose country, and set max_results.
3. Click Start — the Actor streams product records to the default dataset. Export as JSON, JSONL, CSV, Excel, XML, RSS, or pull via the dataset API.

Run via Apify API

curl -X POST "https://api.apify.com/v2/acts/TrueFetch~flipkart-price-tracker/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "keyword": "smartphone",
  "country": "India",
  "max_results": 100
}'

Run via MCP (for AI agents)

Flipkart Price Tracker is callable from Claude, ChatGPT, Cursor, and any MCP-compatible client through the Apify MCP Server. Reference the Actor as TrueFetch/flipkart-price-tracker and pass the same JSON input as above.

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⚙️ Input parameters

Parameter	Type	Required	Description	Example
keyword	string	yes	Product search phrase, brand, model, category, or marketplace query to send to Flipkart.	smartphone
country	string	yes	Country/storefront to query. Supported values: India.	India
max_results	integer	yes	Maximum number of product records to return. The actor stops at this user limit or the platform's available result limit, whichever comes first.	100

Supported country values: India.

Default behavior: the Actor sends the supplied input through the platform adapter, respects the platform's public search behavior, and stops at max_results or the platform's available result boundary.

{
  "keyword": "smartphone",
  "country": "India",
  "max_results": 100
}

---

📦 Output dataset

Each run writes normalized product records to the default Apify dataset. The schema contains 58 product-analysis fields so records from different shopping platforms can be compared without renaming columns. Optional fields stay empty when the source platform does not expose them.

Field	Type	Description
title	string/null	Product or listing title returned by the source platform.
brand	string/null	Product brand when the platform exposes it clearly.
price, currency, price_text	number/string/null	Numeric price, ISO currency, and original display price text for verification.
was_price, discount_pct, discount_text, promo_text	mixed/null	Promotion and discount signals when present on the source.
stock_status, stock_text	string/null	Normalized and original availability text.
rating, review_count	number/integer/null	Public rating and review count when available.
seller, seller_url, seller_score	string/number/null	Seller or store signals when exposed by the platform.
main_image, image_urls	string/array/null	Product image URL fields with non-product placeholders filtered out.
product_id, sku, gtin, mpn, model	string/null	Product identifiers when the source provides them.
category, breadcrumbs, features, specifications	mixed/null	Product categorization, bullet points, and specs when available.
shipping_text, shipping_cost, delivery_text, pickup_text, return_text	mixed/null	Fulfillment, pickup, delivery, and return signals when present.
platform, site, country, product_url, source_url, query, rank	string/integer/null	Source traceability fields used to audit query-to-result correctness.
sponsored, processor, processed_at	boolean/string/null	Sponsored flag when known, actor URL, and UTC processing timestamp.

Sample output

{
  "main_image": "https://rukminim2.flixcart.com/image/example.jpeg",
  "image_urls": [
    "https://rukminim2.flixcart.com/image/example.jpeg"
  ],
  "title": "Motorola Edge Smartphone 128 GB",
  "brand": "Motorola",
  "category": "Mobiles",
  "price": 24999,
  "currency": "INR",
  "price_text": "₹24,999",
  "stock_status": "in_stock",
  "stock_text": "Available",
  "rating": 4.3,
  "review_count": 18542,
  "seller": "RetailNet",
  "platform": "Flipkart",
  "site": "flipkart.com",
  "country": "India",
  "product_url": "https://www.flipkart.com/example/p/itmexample",
  "source_url": "https://www.flipkart.com/search?q=smartphone",
  "query": "smartphone",
  "rank": 1,
  "sponsored": false,
  "processor": "https://apify.com/truefetch/flipkart-price-tracker",
  "processed_at": "2026-06-29T00:00:00+00:00"
}

---

💡 Use cases

For India ecommerce sellers monitoring Flipkart prices

• Problem: A seller needs recurring Flipkart price, discount, and availability snapshots for competing products in India.
• How Flipkart Price Tracker solves it: Schedule keyword runs and compare price, price_text, discount_text, seller, rating, review_count, and stock_text.
• Outcome: A structured Flipkart price-monitoring dataset with source URL and rank retained.

For deal aggregators and cashback sites

• Problem: A deal feed needs current Flipkart offers with prices, discount text, ratings, images, and product URLs.
• How Flipkart Price Tracker solves it: Run high-intent shopping keywords and publish rows with title, main_image, price_text, discount_text, rating, and product_url.
• Outcome: Fresh Flipkart product feeds exportable to CSV or API consumers.

For market researchers tracking India categories

• Problem: A research team wants to analyze price bands, rating depth, review density, and brand visibility for an India ecommerce product segment.
• How Flipkart Price Tracker solves it: Group results by brand, price, discount_text, rating, review_count, and rank.
• Outcome: A source-linked view of Flipkart category competition.

For AI agents needing live Flipkart data

• Problem: An AI assistant needs current Flipkart products for user shopping questions.
• How Flipkart Price Tracker solves it: Call TrueFetch/flipkart-price-tracker through Apify API or MCP and filter returned records by price, rating, and stock.
• Outcome: Grounded India ecommerce answers with product URLs.

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💰 Pricing, limits, and performance

Fact	Value
Pricing model	Pay-per-event
Dataset billing event	result
FREE result price	$0.0086 per result (about $8.60 per 1,000 results)
GOLD / PLATINUM / DIAMOND result price	$0.00774 per result
Result unit	One successful product/listing record pushed to the default dataset
Required inputs	keyword, country, max_results
Supported countries	India
Output schema	58 normalized product fields
Login / cookies required	No user login, cookies, or marketplace API key required
Export formats	JSON, JSONL, CSV, Excel, XML, RSS, dataset API

You are billed for dataset results through the configured result charge event. Use max_results to control requested volume; the final count can be lower when the source platform returns fewer public matches.

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⚖️ Compared with alternatives

Capability	Flipkart Price Tracker	Manual browsing	Custom scraper
Structured product records	yes	no	you build it
Source URL and query retained	yes	manual	depends on implementation
Normalized price/rating/image fields	yes	no	you maintain mapping
Respects platform public ranking	yes	manual observation	easy to accidentally override
Apify dataset exports and API	yes	no	you build storage/export
Setup time to first run	minutes	minutes per query	days to weeks

Verdict. Flipkart Price Tracker is built for India ecommerce analysis where INR price, discount text, review depth, availability, and Flipkart's public search ranking need to stay auditable.

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⚠️ Common mistakes to avoid

1. Using non-India marketplace assumptions. Flipkart Price Tracker supports India, uses INR, and should be queried with India ecommerce wording.
2. Ignoring discount and review context. Flipkart result cards can emphasize discount text, rating, review count, and seller signals; compare those alongside price.
3. Treating missing optional fields as parser failures. Flipkart does not expose every seller, stock, or promo field on every result. Audit optional fields with source_url.
4. Re-sorting without keeping rank. Preserve rank if you need to understand Flipkart's original search order.
5. Expecting checkout or seller-account data. This Actor returns public product/search data, not cart, order, account, or seller dashboard data.

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🛠️ Troubleshooting

Problem	Likely cause	Fix
Empty dataset	The keyword has no public results, the selected country is unsupported for that platform, or the platform returned no matches.	Try a broader keyword, verify country, and compare with the generated source_url when available.
Fewer rows than max_results	The platform exposed fewer public results than requested or hit its own result boundary.	Treat max_results as an upper bound, not a guarantee.
Price or rating is empty	The source result did not expose that field for the item.	Use price_text, stock_text, source_url, and product_url for audit.
Results look different from another run	Marketplace algorithms, location, availability, ads, and ranking can change.	Compare query, country, source_url, rank, and processed_at.

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❓ FAQ

What data does Flipkart Price Tracker return?

Flipkart Price Tracker returns normalized product records with fields such as title, brand, price, currency, price_text, rating, review_count, stock_text, seller, main_image, product_url, source_url, platform, site, country, query, rank, processor, and processed_at. Optional fields are populated only when the source platform exposes them.

How much does Flipkart Price Tracker cost?

Pricing is pay-per-event. The dataset billing event is result; current tiered pricing starts at $0.0086 per result on FREE and $0.00774 per result on GOLD, PLATINUM, and DIAMOND. Check the Apify pricing panel for the final account-specific charge.

Which countries does Flipkart Price Tracker support?

Supported country values are defined in the actor input schema. Current support: India.

Does Flipkart Price Tracker require a login or API key?

No. Flipkart Price Tracker is designed for public product/search data and does not require a shopper login, cookies, or a marketplace API key from the user.

Does Flipkart Price Tracker preserve the user's query and platform ranking?

Yes. The output keeps query, source_url, platform, site, country, and rank so users can compare the dataset against the original search intent and the platform's own ranking algorithm.

Can I export Flipkart results to CSV, Excel, or Google Sheets?

Yes. Apify datasets can be exported as JSON, JSONL, CSV, Excel, XML, RSS, or consumed through the dataset API. Google Sheets workflows can use Apify integrations, Make, Zapier, n8n, or a direct API pull.

Can I schedule Flipkart Price Tracker to monitor prices automatically?

Yes. Use Apify Schedules for recurring keyword runs and Webhooks to push completed datasets to your pricing system, BI pipeline, or automation workflow.

What is the maximum number of products per run?

Use max_results to control the requested result count. The actor returns up to that number unless the source platform has fewer public results for the query or reaches its own result boundary first.

How does Flipkart Price Tracker handle temporary result failures?

The actor follows the platform's public response behavior and keeps returned data source-linked. Temporary request failures, empty searches, or platform-side ranking differences should be audited with source_url, query, rank, and processed_at.

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🔌 Integrations

Flipkart Price Tracker plugs into the Apify ecosystem:

• Schedules — run recurring price and search monitoring jobs (docs).
• Webhooks — POST completed runs to your pricing database, BI stack, or workflow tool on ACTOR.RUN.SUCCEEDED (docs).
• Apify API — use run-sync-get-dataset-items for blocking calls or runs for async jobs (docs).
• MCP Server — call the Actor from Claude, ChatGPT, Cursor, and other agents (docs).
• No-code tools — connect with Make, Zapier, n8n, Pipedream, Google Sheets, Airtable, and other dataset consumers.

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🧱 Sister Actors from TrueFetch

Jobs

• Best Job Listing
• Glassdoor Job Listing
• Indeed Job Listing
• LinkedIn Job Listing

Shopping & Deals

• Product Price Tracker
• Amazon Price Tracker
• Argos Price Tracker
• eBay Price Tracker
• Flipkart Price Tracker
• Myntra Price Tracker
• Target Price Tracker
• Walmart Price Tracker

Vehicles

• AutoTrader Car Listing
• Cars.com Car Listing

Real Estate

• US Property Listing
• Zillow Property Listing

Local Business & Food

• BBB Business Profile
• Google Maps Business Listing
• Zomato Restaurant Listing

Classifieds

• Kleinanzeigen Listing
• OLX Listing

Social Media

• Instagram Profile
• Reddit Post Search
• Telegram Channel Message

Videos & Text

• TikTok Video
• YouTube Video

Content & Articles

• Medium Article
• Substack Article

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📞 Support, changelog, last updated

Support

• Telegram support: @AiAgentApi
• Telegram community: TrueFetch
• Apify Actor page: Flipkart Price Tracker

Changelog

• 2026-06-29: Replaced stale template copy with Flipkart Price Tracker SEO/GEO copy, current actor slug, current input schema, and normalized product dataset fields.

---

{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "Flipkart Price Tracker",
  "applicationCategory": "BusinessApplication",
  "operatingSystem": "Cloud",
  "url": "https://apify.com/truefetch/flipkart-price-tracker",
  "description": "Track public Flipkart India product search results. Export records with INR price, discount text, rating, reviews, availability, source URL, query, and rank.",
  "offers": {
    "@type": "Offer",
    "price": "0.0086",
    "priceCurrency": "USD",
    "description": "Pay-per-result pricing for the result event"
  },
  "provider": {
    "@type": "Organization",
    "name": "TrueFetch",
    "url": "https://apify.com/truefetch"
  }
}

Last updated: 2026-06-29. Schema: Product search and price tracking Actor. Maintained by TrueFetch.