Flipkart Reviews Scraper

What is Flipkart Reviews Scraper?

Flipkart Reviews Scraper lets sellers, brands and researchers extract Flipkart product reviews, star ratings, review photos and per-product rating summaries in bulk, without copying anything by hand. Paste Flipkart product or review URLs (or product IDs) and click Start, no coding needed. You can try it on the Apify Free plan, where each run returns up to 10 results.

Use it when you need Flipkart ratings and reviews in a spreadsheet, a database or an AI pipeline, whether you run an ecommerce team or analyze data.

• Brand reputation monitoring: track ratings and complaints across all your Flipkart listings with scheduled runs.
• Competitor review analysis: pull the most critical reviews of rival products and find their weak spots.
• Customer feedback monitoring: check new feedback on fit, size, quality or packaging every day or every week.
• Flipkart review analysis and NLP: build a Flipkart reviews dataset for sentiment models, topic mining or dashboards.
• Variant feedback: compare reviews by color and size with the product_attributes field.
• Visual quality checks: collect review photo URLs to see what customers actually received.

What can Flipkart Reviews Scraper do?

• 🔗 Extract Flipkart reviews in bulk from product URLs, product-review URLs or product IDs, all in one run
• 🔀 Sort like Flipkart: Most Helpful, Most Recent, Positive First or Negative First
• 🎯 Filter to verified buyers only, a star range, or one review aspect
• 📸 Review photos as image URLs in the width, height and quality you choose
• 📊 Rating summary per product: average rating, star breakdown, rating and review counts, and the positive and negative feedback percentages Flipkart shows for the product
• 🧹 Duplicate removal: a review that was already collected for the same product is skipped
• 💾 Live saving: each review is saved to your dataset as soon as it's collected, so nothing is lost if a run stops early
• 📦 Export and automate: JSON, CSV, Excel, XML or HTML, plus the Apify API, schedules, webhooks, monitoring and integrations

This is a Flipkart scraper focused on reviews and ratings only. For prices, specs, sellers and offers, use Flipkart Product Scraper.

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What data can Flipkart Reviews Scraper extract?

Each dataset item is one review. Here is the Flipkart review data you get for every review:

⭐ Star rating (1–5): rating	🙂 Sentiment label: sentiment
📝 Review title: title	📝 Review text: text
👤 Author name: author	📍 Author location: location, city, state
📅 Date as shown: date	📅 ISO date: date_iso
✅ Verified purchase: certified_buyer	👍 Helpful votes: upvotes
👎 Unhelpful votes: downvotes	🔢 Total votes: total_vote_count
📸 Flipkart review images (resized URLs): review_images	🔢 Review image count: review_image_count
🖼️ Original image URLs: images (when Include Raw (Unresolved) Image URLs is on)	🎬 Has video attachment: has_video
🛍️ Product name: product_name	🆔 Product ID: product_id
🏷️ Color, size and other variant details: product_attributes, product_variant	🔗 Flipkart review link (permalink): url
🔗 Product page URL: product_url	🔗 Scraped page URL: source_url
📄 Review page number: page_number	🔀 Sort order used: sort_order
🕒 Scraped at (UTC): scraped_at	🆔 Review ID: id

Note on sentiment: the sentiment field comes from the star rating (4–5 stars = positive, 3 = neutral, 1–2 = negative). It is a quick label, not text analysis. For real Flipkart sentiment analysis, run your own text model on the text field.

Note on missing values: location, votes, photos and variant details are empty when Flipkart doesn't show them for a review. product_name is built from the product URL in lowercase words, so it can differ slightly from the listing title. product_name and product_url are empty for reviews collected from a product ID alone. date_iso is a best-effort conversion: month-only dates become the 1st of that month, and relative dates such as "8 months ago" are estimated from the scrape time.

Flipkart rating summary per product

With Include Product Rating Summary on (the default), the Actor also saves one rating summary per product. It contains:

• product_rating_average: the product's average star rating
• product_rating_count and product_review_count: how many ratings and written reviews the product has on Flipkart
• product_rating_histogram: the star breakdown
• product_positive_feedback_percent and product_negative_feedback_percent: the positive and negative feedback percentages Flipkart shows for the product
• reviews_collected: how many reviews this run saved for the product
• the product ID, name and URL

To open it, go to your run's Output tab and click Product Rating Summaries. You can also find it in the run's Storage tab: open the key-value store and click the OUTPUT_PRODUCTS record.

A short run summary is saved in the same key-value store as the OUTPUT record (shown as Run Summary in the Output tab): products queued and processed, reviews collected, sort order, review cap and finish time.

What data can't Flipkart Reviews Scraper extract?

• Product prices, specifications, sellers and offers
• Seller ratings or seller reviews
• Review video files (you get the has_video flag only)
• Image files (you get image URLs, not downloaded photos)
• Reviewer profiles or contact details

For product prices, discounts, specs, sellers and offers, try Flipkart Product Scraper.

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How to scrape Flipkart reviews

Here's how to scrape reviews from Flipkart in five steps. The Flipkart review extractor runs on the Apify platform, so there's nothing to install.

1. Create a free Apify account using your email
2. Open Flipkart Reviews Scraper
3. The Flipkart Product / Review URLs field opens with an example product (a pair of adidas running shoes). Delete it and paste your own product URLs, or add IDs to Product IDs. If you keep the example URL, that product is scraped and charged too.
4. Click Start and wait for the run to finish
5. Download your data in JSON, CSV, Excel, XML or HTML

Reviews show up in the Output tab while the run is still going, so you can check the first rows right away.

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How much does it cost to scrape Flipkart reviews?

Flipkart Reviews Scraper uses pay-per-event pricing. Each run has three parts: a small start charge, a charge for every review saved, and the Apify platform usage of the run.

Event	Price	When it's charged
📄 Result	$0.0035 per review = $3.50 per 1,000 results on the Free plan (lower on paid plans, see below)	Each review saved to the dataset
🚀 Actor start	$0.00005 per GB of run memory	Once per run start: $0.00005 per run at the default 1 GB memory

Apify plan	Price per review	Price per 1,000 reviews
Free	$0.0035	$3.50
Starter	$0.00315	$3.15
Scale	$0.0028	$2.80
Business and higher	$0.00245	$2.45

Paid Apify plans get a lower result price. The plan discount applies to that price only. The start fee is the same on every plan, and platform usage is billed at your Apify plan's own rates.

Platform usage is charged on top of the event prices. It depends on the run (for example, how long it takes), so check it on the run's page after a small first test.

Free plan example: the input example below asks for 20 reviews, but a Free plan run stops at 10. That run costs $0.035 in result events (10 × $0.0035), plus $0.00005 for the start, plus platform usage.

Paid plan example: 1,000 reviews cost $3.15 in result events on the Starter plan (1,000 × $0.00315), $2.80 on Scale or $2.45 on Business, plus $0.00005 for the start, plus platform usage.

Run memory is set in the run options, not in the input form. Leave it at its default unless you have a reason to change it: the start charge grows with each GB of memory.

See the pricing tab for the current details.

Is scraping Flipkart reviews free?

You can start for free. The Apify Free plan includes $5 of monthly platform credit, which is spent on both the event charges and the platform usage. Free plan runs of this Actor return up to 10 results per run. Any paid Apify plan removes that per-run cap. Your own spending limit still applies: when a run reaches it, the Actor stops cleanly and keeps every review it has already saved.

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Flipkart Reviews Scraper input

To run Flipkart Reviews Scraper, you only need at least one Flipkart product URL, product-review URL or product ID. Every other field has a default, and most people can leave the advanced settings as they are.

Here's an example that collects the 20 most helpful reviews of one pair of running shoes (on the Free plan, the run stops at 10):

{
    "startUrls": [
        "https://www.flipkart.com/adidas-ampligy-m-running-shoes-men/product-reviews/itmab79cd4ce225d"
    ],
    "maxReviewsPerProduct": 20,
    "sortBy": "MOST_HELPFUL"
}

See the input tab for a full description of all fields.

Main settings

Name in the form	Field	What it does	Default
Flipkart Product / Review URLs	startUrls	Flipkart product or product-review URLs	the example product
Product IDs (alternative to URLs)	productIds	Flipkart product IDs, combined with any URLs	empty
Max Reviews per Product	maxReviewsPerProduct	Review cap per product (1–100,000)	30
Sort Reviews By	sortBy	Most Helpful, Most Recent, Positive First or Negative First (MOST_HELPFUL, MOST_RECENT, POSITIVE_FIRST, NEGATIVE_FIRST)	Most Helpful
Verified Buyers Only	certifiedBuyerOnly	Keep only reviews by verified buyers	off
Minimum Rating Filter / Maximum Rating Filter	minRating / maxRating	Keep a star range (1–5)	no filter

Advanced settings (safe to leave as default)

Name in the form	Field	What it does	Default
Max Pages per Product	maxPages	Cap on review pages read per product (1–500)	200
Review Aspect Filter	aspectId	Limit to one review aspect	overall
Review Image Width (px) / Height (px) / Quality	imageWidth / imageHeight / imageQuality	Size (100–3,000 px) and JPEG quality (1–100) of the URLs in review_images	1280 / 1280 / 100
Include Raw (Unresolved) Image URLs	includeRawImages	Also keep the original image URLs in the images field	on
Remove Duplicate Reviews	dedupeReviews	Skip a review that was already collected for the same product	on
Include Product Rating Summary	includeProductSummary	Save the rating summary per product	on
Concurrent Products / Concurrent Pages per Product	concurrency / pageConcurrency	Products in parallel (1–25) / review pages per product in parallel (1–10)	5 / 3
Max Retries per Request	maxRetries	How many times each page is attempted before giving up (1–10)	3
Delay Between Page Batches (seconds)	requestDelay	Optional pause between groups of page requests for one product (0–30)	0
Request Timeout (seconds)	requestTimeoutSecs	Timeout per request (1–120)	20
Detailed Real-Time Logging	verboseLogging	Detailed progress messages; turn off for a shorter log	on
Proxy Configuration	proxyConfiguration	Optional Apify Proxy settings	off

Flipkart Product / Review URLs

Each entry must point to one product. Product pages and "all reviews" pages both work.

• ✅ Good: https://www.flipkart.com/adidas-ampligy-m-running-shoes-men/product-reviews/itmab79cd4ce225d
• ❌ Bad: https://www.flipkart.com/search?q=running+shoes

⚠️ The form opens with the example URL above already filled in. Replace it with your own URLs, or it is scraped too. Search and category pages are not product pages. If you paste a review URL that already has a sort order, a verified-buyer filter, an aspect or a page number selected on Flipkart, the Actor keeps those settings for that URL and starts from that page. In that case, the product's rating summary can be empty. For predictable results, paste clean product URLs and choose the sort and filters in the input.

Product IDs

Use product IDs when you have them in a spreadsheet. A Flipkart product ID is the value after pid= in a product URL: in a link that contains ?pid=SHOG9XNXUQQBHDEZ, the product ID is SHOG9XNXUQQBHDEZ. The code that starts with itm in the URL path (for example itmab79cd4ce225d in the example URL) is not a product ID. Every review in your results also shows its product's ID in the product_id field, so you can reuse IDs from earlier runs. If you're not sure which part is the ID, paste the full product URL into Flipkart Product / Review URLs instead.

• ✅ Good: SHOG9XNXUQQBHDEZ
• ❌ Bad: adidas running shoes, itmab79cd4ce225d

⚠️ Reviews from a product ID alone have no product_name or product_url. If you use only Product IDs, delete the example URL from Flipkart Product / Review URLs. When the URL field is left out of the input, the example URL is used as its default, so in the JSON view of the input (or through the API) send "startUrls": [] together with your productIds.

Max Reviews per Product

This is a cap per product, not per run. Five products with "maxReviewsPerProduct": 100 can return up to 500 reviews.

• ✅ Good: "maxReviewsPerProduct": 100 to get up to 100 reviews from each product
• ❌ Bad: expecting "maxReviewsPerProduct": 100 with five products to stop at 100 reviews in total

⚠️ A product can return fewer reviews if it has fewer, if your filters remove some, or if Max Pages per Product is reached first. Free plan runs stop at 10 results.

Flipkart verified buyer reviews and star filters

Turn on Verified Buyers Only ("certifiedBuyerOnly": true) to keep only Flipkart verified buyer reviews. Use Minimum Rating Filter and Maximum Rating Filter to filter by Flipkart review rating. For example, to collect Flipkart negative reviews, set Sort Reviews By to Negative First ("sortBy": "NEGATIVE_FIRST") and Maximum Rating Filter to 2 ("maxRating": 2).

Review Aspect Filter

aspectId limits the reviews to one aspect tab (such as comfort, fit or camera). It needs the aspect's ID, not the visible name.

• ✅ Good: overall
• ❌ Bad: Comfort

⚠️ Leave it as overall (all reviews) unless you know the aspect ID.

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Flipkart Reviews Scraper output

Reviews are stored in a dataset in the run's Output tab (also under Storage). You can switch between the Reviews Overview and Full Review Data views, view the data as a table or JSON, and pick only the fields you need. To start a Flipkart review download, click Export and choose JSON, CSV, Excel, XML or HTML.

JSON example

Results for the input example above (one review, selected fields):

[
    {
        "id": "09f9a2ef-3a95-40e0-b1c9-02c7eb810459",
        "product_name": "adidas ampligy m running shoes men",
        "product_id": "SHOG9XNXUQQBHDEZ",
        "rating": 5,
        "sentiment": "positive",
        "title": "Super!",
        "text": "Very good condition and original product very nice look",
        "author": "Virender Kumar",
        "location": "Hisar, Haryana",
        "date": "Apr, 2023",
        "certified_buyer": true,
        "upvotes": 92,
        "downvotes": 19,
        "product_attributes": { "Color": "FTWWHT/AMBSKY/STONE", "Size": "9" },
        "url": "https://www.flipkart.com/reviews/SHOG9XNXUQQBHDEZ:33?reviewId=09f9a2ef-3a95-40e0-b1c9-02c7eb810459"
    }
]

Reviews with photos also carry review_images (a list of full image URLs), review_image_count and, with Include Raw (Unresolved) Image URLs on, images.

Where to find each part of the output

Where	What you get
⭐ Output tab → Reviews (Overview / Full data)	One row per review
📈 Output tab → Product Rating Summaries (key-value store record OUTPUT_PRODUCTS)	One rating summary per product
🧾 Output tab → Run Summary (key-value store record OUTPUT)	Totals for the whole run
📜 The run's Log tab	Progress messages, warnings and the final summary of the run

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Flipkart Reviews Scraper tips and advanced usage

How many reviews can you scrape with Flipkart Reviews Scraper?

Max Reviews per Product accepts up to 100,000, and Max Pages per Product (default 200, up to 500) limits how many review pages are read for each product. Whichever limit is reached first stops that product, so if you need a lot of reviews, raise both. The real number also depends on how many reviews the product has, your filters, the Free plan cap of 10 results per run, and your spending limit. The best way to know for your use case is a quick test run with a small cap.

How to get cheaper results

• Set Max Reviews per Product to what you really need. Every saved review is charged.
• Use Verified Buyers Only and the rating filters. Reviews that don't match your filters are not saved, so they're not charged.
• Turn off Include Raw (Unresolved) Image URLs if the resized photo URLs in review_images are enough. Your output gets smaller.
• Leave the run memory at its default: the start charge is per GB of memory.

For a long list of products, raising Concurrent Products lets more products be processed in parallel.

Proxy settings

You can leave Proxy Configuration off. If you turn on Apify Proxy in this field, the Actor uses your Apify Proxy settings for all its requests.

Known issues

• If a review page still fails after all attempts, that product stops early and the run continues with the next product. Run that product again later, or raise Max Retries per Request.
• Optional fields such as location, votes and photos are empty when Flipkart doesn't show them.

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Integrations and API

Can I use Flipkart Reviews Scraper as a Flipkart review API?

Yes. With the Apify API you can start runs, schedule them and fetch the results from your own code, so the Actor works as a Flipkart scraper API for review data (not for prices or product details). Use the apify-client NPM package for Node.js or the apify-client PyPI package for Python. The API tab has ready-to-use code.

How to scrape data from Flipkart using Python

You don't need to write Flipkart web scraping Python code from scratch. Install the client with pip install apify-client, copy your API token from Apify Console → Settings → API & Integrations, then run:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("insights_data/flipkart-reviews-scraper").call(run_input={
    "startUrls": [
        "https://www.flipkart.com/adidas-ampligy-m-running-shoes-men/product-reviews/itmab79cd4ce225d"
    ],
    "maxReviewsPerProduct": 20,
    "sortBy": "MOST_HELPFUL",
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["rating"], item["sentiment"], item["title"])

To use product IDs only, send "startUrls": [] together with "productIds": ["SHOG9XNXUQQBHDEZ"]. This saves you from building and maintaining your own Flipkart review scraper.

Flipkart reviews sentiment analysis using Python

Load the items into pandas and use the rating, sentiment and text fields. Keep in mind that sentiment is only a label based on the star rating. For Flipkart reviews sentiment analysis of the review text itself, feed the text field into your own model.

Can I integrate Flipkart Reviews Scraper with other apps?

Yes. Connect Flipkart Reviews Scraper with almost any cloud service through Apify integrations: Make, Zapier, Slack, Google Sheets, Google Drive, Airbyte, GitHub, LangChain and more. Use webhooks to trigger actions when a run finishes.

Example workflow: schedule a weekly run on your products with Sort Reviews By set to Most Recent, send the new reviews to a Google Sheet, and post a Slack message when the run finishes.

Can I use Flipkart Reviews Scraper with AI agents (MCP)?

Yes. Connect Flipkart Reviews Scraper to Claude and other AI assistants through the Apify MCP server. Open the MCP tab for setup steps.

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Other Flipkart scrapers

Need more than reviews? These Actors from the same author cover other data. If you're looking for a Flipkart data scraper for prices and product details, start with the first one.

Actor	What it does
🛒 Flipkart Product Scraper	Flipkart products by keyword or category URL: prices, discounts, ratings, specs, sellers and offers
📈 Stocktwits Scraper	Stock and crypto messages with bullish/bearish sentiment for sentiment analysis and trading research
📢 Google Ads Transparency Center Scraper & API	Ads by brand, domain or advertiser ID for competitor ad intelligence

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❓ FAQ

Is it legal to scrape Flipkart reviews?

Web scraping is generally legal if you extract publicly available data, and Flipkart reviews are public. However, reviews include personal data such as reviewer names and locations, so collect and store it only with a legitimate reason and in line with data protection laws such as GDPR. Read more in the Apify article Is web scraping legal?. This is not legal advice.

Does Flipkart allow web scraping?

Flipkart sets its own rules for using its website in its Terms of Use, so read them before you start a project. Flipkart Reviews Scraper reads only publicly visible review pages, and you don't need a Flipkart account to use it. This Actor is an independent tool. It is not affiliated with, endorsed by or sponsored by Flipkart.

How does Flipkart Reviews Scraper work?

Flipkart Reviews Scraper is a Flipkart review fetcher that reads a product's public review pages the way a visitor would. You give it product or review page URLs (or product IDs). It reads every review on each page, applies your filters and sort order, and saves each review to the dataset right away. It moves page by page until it reaches your review cap, the page cap or the last review page, then saves a rating summary for the product.

Can I use it as a Flipkart rating scraper?

Yes. Every review comes with its star rating, and the rating summary adds each product's average rating, star breakdown and rating count. It doesn't collect ratings without the reviews they belong to.

How is Flipkart Reviews Scraper different from Flipkart Product Scraper?

Flipkart Reviews Scraper collects what buyers say about a product; Flipkart Product Scraper collects the product listing itself. Use them together for a full picture.

	Flipkart Reviews Scraper	Flipkart Product Scraper
Input	Product URLs, review URLs or product IDs	Keyword or category URL
Main data	Review text, star ratings, authors, dates, votes, review photos, verified-buyer flags, rating summaries	Prices, discounts, ratings, specs, sellers and offers
Best for	Sentiment and feedback research, reputation monitoring	Price monitoring, catalog research, competitive analysis
Prices, specs, sellers, offers	❌	✅

Why scrape Flipkart reviews?

Flipkart customer reviews show what buyers like, what they return and what they wish were different.

• Product development: find recurring complaints about size, fit or quality, broken down by variant.
• Brand health: watch your average rating and the share of negative reviews over time.
• Competitor research: compare your products' reviews with rival products in the same category.
• Machine learning: build a Flipkart product reviews dataset with ratings and labels for training and testing.
• Marketing: find the words customers use in positive reviews and reuse them in your listings.

Does it work for other Indian shopping sites?

No. Flipkart Reviews Scraper is an ecommerce review scraper for Flipkart only. If you found this page by searching for "Flipkart customer reviews India" or "product review scraper India", note that reviews from other Indian shopping sites are not covered.

How do I export Flipkart reviews to Excel?

Open the run's Output tab, click Export and pick Excel. To export Flipkart reviews to Excel on a regular basis, schedule the Actor and send the results to Google Sheets or Google Drive. That gives you a recurring Flipkart review exporter without any code.

Why am I getting fewer results than expected?

Check these in order:

1. Free plan cap: on the Apify Free plan, each run returns at most 10 results.
2. Caps: Max Reviews per Product (default 30) and Max Pages per Product limit each product.
3. Filters: Verified Buyers Only, the rating filters and Review Aspect Filter remove reviews that don't match.
4. The product itself: it may simply have fewer reviews than your cap.
5. The URL: a pasted review URL that starts on a later page skips the earlier pages.
6. The run log: open the run's Log tab. If a page kept failing, that product stopped early. Run it again or raise Max Retries per Request.
7. Spending limit: the run stops when it reaches your spending limit.

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Support and feedback

Found a bug or have a feature request? Please create an issue on the Issues tab.

Need a custom solution, more fields or a scraper for another site? Contact us at hello.insights.data@gmail.com.

Built and maintained by Insights Data.