Flipkart Reviews Scraper

Extract Flipkart product reviews in a clean, analysis-ready format. Collect review text, star ratings, helpful votes, verified purchase flags, reviewer location details, image attachments, and product variant data in seconds.

Features

• Fast collection — Pulls review payloads quickly across paginated review pages with minimal overhead
• Rich review data — Captures ratings, titles, full review text, helpful and unhelpful votes, image counts, and product variants
• Clean output — Removes duplicate reviews and skips empty fields instead of filling records with null-heavy placeholders
• Flexible input — Works with Flipkart product URLs, review URLs, and multi-URL runs
• Ready for analysis — Produces structured datasets for sentiment analysis, merchandising research, and review monitoring

Use Cases

Product Research

Study what buyers praise or criticize before launching, sourcing, or restocking similar products. Review images and variant details help validate quality claims.

Marketplace Monitoring

Track how customer opinion changes across products and categories. Helpful vote totals make it easier to identify the reviews that influence purchase decisions.

Sentiment Analysis

Build review datasets for language models, classifiers, and dashboards. The output keeps the original review text and enough metadata to segment by product, variant, and reviewer location.

Competitive Intelligence

Compare recurring complaints, sizing issues, and perceived product quality across competing listings. Variant and location fields help highlight region-specific patterns.

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Input Parameters

Parameter	Type	Required	Default	Description
startUrl	String	Yes	Review URL prefill	Flipkart product URL or review URL to scrape
startUrls	Array	No	[]	Optional list of Flipkart product or review URLs
results_wanted	Integer	No	20	Maximum number of reviews to collect
max_pages	Integer	No	20	Safety cap for pagination per product
proxyConfiguration	Object	No	Residential Apify Proxy	Optional proxy settings for reliability

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Output Data

Each dataset item can contain the following fields:

Field	Type	Description
product_name	String	Product name derived from the review page
product_id	String	Product identifier associated with the review
page_product_id	String	Product identifier found on the review page itself
listing_id	String	Flipkart listing identifier from the review page
review_id	String	Unique review identifier
rating	Number	Review rating value
title	String	Review headline
review_text	String	Full review text
author	String	Reviewer name
date	String	Review date shown on Flipkart
verified_purchase	Boolean	Whether the review is from a verified purchase
helpful_count	Number	Helpful vote total
unhelpful_count	Number	Unhelpful vote total
total_vote_count	Number	Combined helpful and unhelpful vote count
review_images	Array	Review image URLs when available
review_image_count	Number	Number of review images included
location	String	Combined reviewer location text
author_city	String	Reviewer city when available
author_state	String	Reviewer state when available
product_attributes	Object	Variant attributes such as color or size
product_variant	String	Human-readable variant summary
total_reviews	Number	Total review count shown for the product
aspect_id	String	Review aspect identifier from the page context
review_url	String	Direct review URL
url	String	Same direct review URL for convenience
page_number	Number	Review page number where the item was collected

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Usage Examples

Single Product Reviews

Collect reviews from one Flipkart review page:

{
  "startUrl": "https://www.flipkart.com/adidas-ampligy-m-running-shoes-men/product-reviews/itmab79cd4ce225d",
  "results_wanted": 20
}

Larger Review Sample

Increase the review count while capping pagination:

{
  "startUrl": "https://www.flipkart.com/adidas-ampligy-m-running-shoes-men/product-reviews/itmab79cd4ce225d",
  "results_wanted": 100,
  "max_pages": 15
}

Multiple Products

Collect reviews from several products in one run:

{
  "startUrls": [
    { "url": "https://www.flipkart.com/adidas-ampligy-m-running-shoes-men/product-reviews/itmab79cd4ce225d" },
    { "url": "https://www.flipkart.com/search?q=flipkart+product+url" }
  ],
  "results_wanted": 40
}

---

Sample Output

{
  "product_name": "adidas ampligy m running shoes men",
  "product_id": "SHOG9XNXUQQBHDEZ",
  "page_product_id": "SHOG9XNXUXWNFUQY",
  "listing_id": "LSTSHOG9XNXUXWNFUQYZVBUXK",
  "review_id": "09f9a2ef-3a95-40e0-b1c9-02c7eb810459",
  "rating": 5,
  "title": "Super!",
  "review_text": "Very good condition and original product very nice look I am happy",
  "author": "Virender Kumar",
  "date": "Apr, 2023",
  "verified_purchase": true,
  "helpful_count": 93,
  "unhelpful_count": 37,
  "total_vote_count": 130,
  "review_images": [
    "https://rukminim1.flixcart.com/blobio/1280/1280/imr/blobio-imr_a25625f18b6d43b3903c716c5dd39058.jpg?q=100"
  ],
  "review_image_count": 1,
  "location": "Hisar, Haryana",
  "author_city": "Hisar",
  "author_state": "Haryana",
  "product_attributes": {
    "Color": "CBLACK/FTWWHT/GRESIX",
    "Size": "11"
  },
  "product_variant": "Color: CBLACK/FTWWHT/GRESIX | Size: 11",
  "total_reviews": 90,
  "aspect_id": "overall",
  "review_url": "https://www.flipkart.com/reviews/SHOG9XNXUQQBHDEZ:33?reviewId=09f9a2ef-3a95-40e0-b1c9-02c7eb810459",
  "url": "https://www.flipkart.com/reviews/SHOG9XNXUQQBHDEZ:33?reviewId=09f9a2ef-3a95-40e0-b1c9-02c7eb810459",
  "page_number": 1
}

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Tips for Best Results

Use Review-Oriented URLs

• Start with Flipkart review URLs when possible
• Product URLs also work, but review URLs reduce redirects and context guessing

Scale Gradually

• Start with 20 to validate the target product
• Increase results_wanted once you confirm the product has enough reviews

Use Residential Proxies When Needed

• Residential proxies improve consistency if Flipkart throttles or blocks repeated requests
• Keep max_pages aligned with the size of the review set you actually need

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Integrations

Connect your review data with:

• Google Sheets — Share review samples with business teams
• Airtable — Build searchable review archives
• Looker Studio — Visualize rating trends and review volume
• Make — Trigger downstream automation from fresh review runs
• Zapier — Push new data into internal tools
• Webhooks — Send review datasets into your own pipelines

Export Formats

• JSON — For applications and data pipelines
• CSV — For spreadsheets and lightweight analysis
• Excel — For business reporting
• XML — For system integrations

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Frequently Asked Questions

How many reviews can I collect?

You can collect as many reviews as are available, subject to the results_wanted and max_pages values you set.

Can I scrape multiple products in one run?

Yes. Use startUrls to pass multiple product or review URLs.

Why are some optional fields absent on certain reviews?

Not every review includes images, detailed location info, or variant attributes. Empty optional fields are skipped instead of being filled with null values.

Does the actor remove duplicate reviews?

Yes. Reviews are deduplicated by review_id before they are pushed to the dataset.

Which reviews appear first?

Reviews are collected in the same ordering shown on the review pages, typically the most helpful view unless the product page context indicates a different aspect.

What if Flipkart slows down or blocks requests?

Retry with residential proxies and reduce the number of pages per run. This is especially useful during high-volume collection.

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Support

For issues or feature requests, use the Apify Console issue flow for this actor.

Resources

• Apify Documentation
• Apify API Reference
• Scheduling Runs

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Legal Notice

This actor is intended for legitimate data collection and analysis. You are responsible for complying with Flipkart terms, applicable laws, and responsible data-use practices.