Flipkart Reviews Scraper

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Scrape Flipkart product reviews at scale by pasting a Flipkart product URL or product-reviews URL. Returns one clean record per review — star rating, title, full review text, reviewer name and location, verified-purchase flag, date, helpful/unhelpful votes, the reviewed variant, and any review images — plus a per-product rating summary. Built for AI agents (MCP-ready) and analysts alike.

What you get

Plus, per product, one recordType: "product_summary" row with totalRatings, totalReviews, averageRating, and the 5→1 star ratingDistribution.

When to use it

• Mine sentiment and feature feedback on your own or competitors' Flipkart listings
• Track ratings, verified-buyer share, and review velocity over time
• Pull review corpora for LLM summarization, topic modelling, or QA
• Feed an AI agent that needs structured Flipkart review data from a single product link

Not a search or category scraper — give it specific product links (each must contain an itm... id and a pid= parameter).

Pricing

Pay-per-event:

• Actor start — $0.00005 per run
• Review scraped — $0.004 per review written to the dataset (the product summary record is free)

A run of 1 product × 100 reviews costs about $0.40. Use maxReviews to cap spend per product; the actor logs the maximum possible cost before charging anything.

Input

{
"productUrls":[
"https://www.flipkart.com/apple-iphone-15-black-128-gb/p/itm6ac6485515ae4?pid=MOBGTAGPAQNVFZZY"
],
"maxReviews":100,
"sortBy":"MOST_HELPFUL",
"includeProductSummary":true
}

Output sample

{
"recordType":"review",
"productKey":"MOBGTAGPAQNVFZZY",
"rating":5,
"title":"Mind-blowing purchase",
"body":"Fully satisfied using iphone 15. Camera and battery are excellent.",
"author":"subhabrata paul",
"location":"Teliamura",
"isVerifiedPurchase":true,
"reviewDate":"Oct, 2024",
"helpfulCount":438,
"unhelpfulCount":83,
"variant":"Color Black, Storage 128 GB",
"images":["https://rukminim2.flixcart.com/.../blobio-imr_...jpeg?q=90"],
"scrapedAt":"2026-06-21T00:00:00.000Z"
}

How it works

Flipkart protects its pages with reCAPTCHA Enterprise and serves two different review front-ends (a classic web build and a newer React-Native-Web build), both using rotating, obfuscated CSS class names. This actor uses a real browser (Chromium with fingerprinting) over residential India IPs, and a layout-agnostic extractor that anchors on the stable buyer-label text and reads fields by position — so it keeps working across Flipkart's front-end A/B variants and class-name churn. Reviews are paginated via &page=N, de-duplicated across pages, and truncated bodies are expanded before extraction. Image/media/font bytes are blocked to keep proxy bandwidth (and your cost) low while preserving image URLs.

If every page is blocked, the run fails honestly with an actionable message rather than silently returning an empty dataset.

Tips & limits

• Proxy: datacenter IPs do not work on Flipkart. Keep the default Apify Residential / country IN, or supply your own residential/mobile proxy.
• Review dates are returned exactly as Flipkart displays them (absolute or relative); convert downstream if you need a normalized timestamp.
• Region: Flipkart serves India. Prices/availability shown reflect the India store.

FAQ

Can I pass a search results URL? No — pass individual product or product-reviews URLs. Use Flipkart search yourself, then feed the product links here.

Does it need login or cookies? No. Reviews are public; no credentials required.

How many reviews can I get? Up to maxReviews per product (max 1000). Flipkart paginates 10 per page.

Why might a run return fewer reviews than the product shows? Flipkart caps how deep its public review pagination goes, and de-duplication removes repeats across pages.

Legal

This actor scrapes only publicly available review content. You are responsible for using the data in compliance with Flipkart's Terms of Use, applicable laws (including data-protection and copyright law), and for not using personal data (reviewer names/locations) in violation of privacy regulations. This actor is not affiliated with or endorsed by Flipkart.