# Flipkart Reviews Scraper (`insights_data/flipkart-reviews-scraper`) Actor

Scrape Flipkart product reviews, star ratings, photos, and rating summaries in bulk. Extract verified-buyer feedback and sentiment from any product URL or ID. Ideal for reputation monitoring, VOC research, and review datasets — export JSON/CSV.

- **URL**: https://apify.com/insights\_data/flipkart-reviews-scraper.md
- **Developed by:** [Insights Data](https://apify.com/insights_data) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.50 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

### What does Flipkart Reviews Scraper do?

> **Disclaimer:** This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Flipkart Internet Private Limited or any of its subsidiaries. "Flipkart" is referenced only to describe the publicly available website this Actor collects data from.

This **Flipkart reviews scraper** turns public Flipkart product pages into clean, structured **Flipkart review data** you can export, schedule, and reuse. Paste product URLs, product-review URLs, or bare product IDs — then **extract Flipkart reviews**, star ratings, photos, and per-product rating summaries in bulk. ✅

As a **Flipkart product reviews** tool and practical **Flipkart review API** alternative, it helps teams run **ecommerce review scraper** workflows, **product review mining**, and **ecommerce reputation monitoring** across India’s largest marketplace — without building a custom crawler.

Open it in [Apify Console](https://console.apify.com), paste your URLs, hit **Start** — reviews stream into your dataset as they arrive.

#### ✨ What can this Flipkart review scraper do?

- 🔗 **Flexible bulk input** — product URLs, review-page URLs, bare product IDs, or a mix
- ⭐ **Reviews + summaries** — every individual review **and** a per-product rating roll-up
- 🔀 **Sort like Flipkart** — most helpful, most recent, positive first, or negative first
- ✅ **Verified buyers** — optional certified-buyer / verified-purchase filter
- 🎯 **Rating filters** — keep only the star range you need for **Flipkart sentiment analysis**
- 🖼️ **Review photos** — resolve **Flipkart review photos** to the width / height / quality you choose
- 🧹 **Clean duplicates** — drop repeat review IDs automatically
- ⚡ **Live results** — watch **Flipkart customer reviews** land while the run is still going
- 🗂️ **Sectioned output** — Reviews · Product summaries · Run summary
- 🧩 **Apify platform powers** — scheduling, monitoring, API access, MCP, webhooks, and 1,000+ integrations

#### 📦 What data can you extract from Flipkart reviews?

| 🗂️ Section | 📌 What you get |
|---|---|
| ⭐ Review core | Title, body, **Flipkart star ratings** (1–5), derived sentiment |
| 👤 Reviewer | Author name, city / state / location when published |
| 📅 Dates | Display date + normalized ISO |
| ✅ Trust signals | Certified buyer / verified purchase flags |
| 👍 Engagement | Upvotes, downvotes, total votes |
| 🖼️ Media | Review image URLs, image count, video flag |
| 🛍️ Product context | Product name, ID, attributes / variants (color, size…) |
| 🔗 Links | Review URL, product URL, source URL |
| 📊 Product summary | Average rating, histogram, review count, positive / negative feedback % |

### 🌟 Why scrape Flipkart reviews?

Public **Flipkart customer reviews** are a goldmine for VOC, brand health, and competitor quality signals. A dedicated **Flipkart feedback scraper** and **product review scraper India** workflow helps you:

- 📈 Track **Flipkart rating scraper** trends and spikes after launches or price changes
- 🧠 Build a **Flipkart review dataset** for NLP, topic mining, or **Flipkart sentiment analysis**
- 🛡️ Run **ecommerce reputation monitoring** across SKUs and categories
- 🖼️ Collect **Flipkart review photos** for visual quality and unboxing insights
- 📤 Use this **Flipkart review exporter** to feed Sheets, warehouses, or agent pipelines

### 🚀 How to scrape Flipkart reviews (Apify Console)

1. Open **Flipkart Reviews Scraper** in [Apify Console](https://console.apify.com)
2. Paste one or more Flipkart product or product-review URLs into **Flipkart Product / Review URLs** (bulk supported)
3. Optionally add bare **Product IDs** from spreadsheets
4. Set **Max Reviews per Product**, sort order, and any rating / verified-buyer filters
5. Click **Start** and follow live progress in the log
6. Open **Output**, switch sections, and export JSON / CSV / Excel / XML — or pull via API

💡 Tip: URLs that include `pid` (and `lid` when available) give the most reliable **scrape Flipkart ratings** results.

### 📥 Input

Simple JSON — no coding required:

```json
{
    "startUrls": [
        "https://www.flipkart.com/adidas-ampligy-m-running-shoes-men/product-reviews/itmab79cd4ce225d"
    ],
    "maxReviewsPerProduct": 50,
    "sortBy": "MOST_HELPFUL",
    "certifiedBuyerOnly": false
}
```

| Field | Description |
|---|---|
| 🔗 `startUrls` *(required)* | Product or product-review URLs — core of this **Flipkart reviews scraper** |
| 🆔 `productIds` | Bare Flipkart product IDs as an alternative / addition to URLs |
| ⭐ `maxReviewsPerProduct` | Cap reviews collected per product |
| 📄 `maxPages` | Safety cap on review pages per product |
| 🔀 `sortBy` | `MOST_HELPFUL` · `MOST_RECENT` · `POSITIVE_FIRST` · `NEGATIVE_FIRST` |
| ✅ `certifiedBuyerOnly` | Only verified-purchase reviews |
| ⭐ `minRating` / `maxRating` | Keep a star range for focused **product review mining** |
| 🏷️ `aspectId` | Advanced aspect tab filter (e.g. Comfort, Camera) |
| 🖼️ Image options | Width / height / quality for resolved photo URLs |
| 🧹 `dedupeReviews` | Drop duplicate review IDs |
| 📊 `includeProductSummary` | Save per-product rating summaries |
| Performance | Concurrency, retries, timeouts, polite delay |

See the **Input** tab for every option with helpful defaults.

### 📤 Output

One dataset item per review — ready for CRM import, spreadsheets, or your own **Flipkart VOC data** pipeline:

```json
{
    "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,
    "review_images": ["https://rukminim1.flixcart.com/blobio/1280/1280/imr/....jpg?q=100"],
    "product_attributes": { "Color": "FTWWHT/AMBSKY/STONE", "Size": "9" },
    "url": "https://www.flipkart.com/reviews/SHOG9XNXUQQBHDEZ:33?reviewId=09f9a2ef-3a95-40e0-b1c9-02c7eb810459"
}
```

#### 🗂️ Output views & files

| View / file | Shows |
|---|---|
| ⭐ **Reviews** | One row per review (Overview + Full data views) |
| 📊 **Product summaries** | Rating averages, histograms, feedback % (`OUTPUT_PRODUCTS`) |
| 📑 **Run summary** | Totals for the run (`OUTPUT`) |

### 🤖 Use via API (Flipkart review API style)

Call the Actor like a lightweight **Flipkart review API** and get dataset items back:

```bash
curl -X POST "https://api.apify.com/v2/acts/<YOUR_USERNAME>~flipkart-reviews-scraper/run-sync-get-dataset-items" \
     -H "Authorization: Bearer $APIFY_TOKEN" \
     -H "Content-Type: application/json" \
     -d '{
           "startUrls": ["https://www.flipkart.com/adidas-ampligy-m-running-shoes-men/product-reviews/itmab79cd4ce225d"],
           "maxReviewsPerProduct": 50
         }'
```

Schedule **Flipkart review monitoring**, connect Zapier / Make / n8n, or pipe results into agents via [Apify MCP](https://docs.apify.com/platform/integrations/mcp).

### 🎯 Best use cases for this ecommerce review scraper

- 🛡️ **Ecommerce reputation monitoring** across SKUs and competitors
- 🧠 **Flipkart sentiment analysis** and topic mining on **Flipkart customer reviews**
- ⭐ Track **Flipkart star ratings** and histogram shifts after campaigns
- 🖼️ Collect **Flipkart review photos** for QA and visual research
- 📤 **Flipkart review exporter** workflows into Sheets, warehouses, or BI tools
- 🧪 Build a reusable **Flipkart review dataset** for ML / NLP projects

### 🔗 Integrations & related Actors

This **Flipkart product reviews** Actor works with Apify’s API, schedules, webhooks, and popular destinations (Sheets, Slack, warehouses, and more).

| Actor | What it helps with |
|---|---|
| [Flipkart Product Scraper](https://apify.com) | Full product, price, specs, seller, and offer data |
| [Google Ads Transparency Center Scraper & API](https://apify.com) | Competitor ad creatives and brand ad tracking |
| [Y Combinator Scraper](https://apify.com) | Startup directory, founders, and job listings |

Need a custom pipeline (alerts, multi-marketplace VOC, or private enrichment)? Email **hello.insights.data@gmail.com**.

### ❓ FAQ

#### Can I use a product URL instead of a review URL?

Yes — both product and product-review URLs are accepted by this **Flipkart reviews scraper**.

#### Can I scrape multiple products in one run?

Yes — add as many rows as you like to `startUrls`, or mix in `productIds` for bulk **extract Flipkart reviews** jobs.

#### Why are some fields empty?

Flipkart does not publish every field for every review (location, photos, etc.). Empty fields reflect what is publicly shown.

#### Can I keep only verified buyers or a star range?

Yes — use `certifiedBuyerOnly` and `minRating` / `maxRating` for focused **Flipkart feedback scraper** runs.

#### Can I get results in Python or JavaScript?

Yes. Use the Apify API / SDKs to pull **Flipkart review data** into Python, Node.js, or any HTTP client — the same pattern as a lightweight **Flipkart review API**.

#### Is scraping Flipkart reviews allowed for research?

This Actor collects only publicly available review content. Use the data responsibly and in line with Flipkart’s terms and applicable laws. For compliance questions on a custom deployment, contact **hello.insights.data@gmail.com**.

### 🛟 Support & custom solutions

Bugs or feature ideas? Open an issue on this Actor’s **Issues** tab in Apify Console.

For custom scrapers, scheduled **Flipkart review monitoring**, private enrichment, or enterprise exports of **Flipkart review data**, email **hello.insights.data@gmail.com** — we build tailored solutions on top of this Actor.

***

*Data is collected only from Flipkart’s publicly available product and review pages. Intended for legitimate market research, reputation monitoring, and product analytics. Not affiliated with Flipkart.*

# Actor input Schema

## `startUrls` (type: `array`):

Paste one or more Flipkart product page URLs or product-review page URLs (bulk supported — one per line or add multiple rows). URLs that include `pid` and `lid` query parameters give the most reliable results.

## `productIds` (type: `array`):

🧩 Optional. Add bare Flipkart product IDs (the value after `pid=` in any product URL) instead of full URLs — handy for bulk lists from a spreadsheet. Combined with any URLs above.

## `startUrl` (type: `string`):

Legacy single-URL field kept for backward compatibility with older integrations. Prefer '🔗 Flipkart Product / Review URLs' above for new setups.

## `maxReviewsPerProduct` (type: `integer`):

🎯 Stop collecting once this many reviews have been gathered for a single product. Pagination is handled automatically behind the scenes.

## `resultsWanted` (type: `integer`):

Legacy alias for '⭐ Max Reviews per Product'. Kept for compatibility with older automations — the field that was changed away from its own default wins.

## `maxPages` (type: `integer`):

🛑 Safety cap on how many review pages the Actor will paginate through for a single product, even if 'Max Reviews per Product' hasn't been reached yet.

## `sortBy` (type: `string`):

Choose the order Flipkart returns reviews in — mirrors the sort pills on the live review page.

## `certifiedBuyerOnly` (type: `boolean`):

Only collect reviews written by Flipkart-certified (verified-purchase) buyers.

## `minRating` (type: `integer`):

Only keep reviews with a star rating greater than or equal to this value (1-5). Leave empty for no minimum.

## `maxRating` (type: `integer`):

Only keep reviews with a star rating less than or equal to this value (1-5). Leave empty for no maximum.

## `aspectId` (type: `string`):

Advanced: filter reviews to one aspect tab shown on the product page (e.g. Comfort, Fit, Camera) using its internal aspect ID. Leave as 'overall' to collect every review.

## `imageWidth` (type: `integer`):

Width to render resolved review-photo URLs at.

## `imageHeight` (type: `integer`):

Height to render resolved review-photo URLs at.

## `imageQuality` (type: `integer`):

JPEG quality (1-100) to render resolved review-photo URLs at.

## `includeRawImages` (type: `boolean`):

Also keep Flipkart's original templated image URLs (before width/height/quality is filled in) alongside the resolved ones.

## `concurrency` (type: `integer`):

How many products to scrape in parallel. Higher is faster but more resource-intensive.

## `pageConcurrency` (type: `integer`):

How many review pages of the SAME product to fetch in parallel.

## `maxRetries` (type: `integer`):

How many times to retry a single request (page fetch) before giving up on it — also the retry budget used once escalated to a Residential proxy.

## `requestDelay` (type: `number`):

Polite pause between batches of page fetches for the same product. Float seconds; a little jitter is added automatically.

## `requestTimeoutSecs` (type: `number`):

Maximum time to wait for a single page fetch before treating it as failed.

## `dedupeReviews` (type: `boolean`):

Drop reviews with a review ID already seen for the same product (can happen across sort orders / pages).

## `includeProductSummary` (type: `boolean`):

Also save one roll-up record per product (average rating, rating histogram, total review count) to the key-value store as a downloadable JSON file, in addition to the individual review dataset.

## `verboseLogging` (type: `boolean`):

Show friendly, real-time progress logs (products queued, pages fetched, reviews collected, proxy events) while the run is in progress.

## `proxyConfiguration` (type: `object`):

🛡️ Smart proxy strategy: the Actor tries a direct connection first (no proxy) for maximum speed. If Flipkart blocks or rate-limits a request, it automatically escalates to an Apify Datacenter proxy, and finally to a Residential proxy — then sticks with Residential for the rest of the run. Leave this OFF to let the built-in auto-escalation handle everything, or turn it ON / choose specific groups to force your own proxy from the start.

## Actor input object example

```json
{
  "startUrls": [
    "https://www.flipkart.com/adidas-ampligy-m-running-shoes-men/product-reviews/itmab79cd4ce225d"
  ],
  "productIds": [],
  "startUrl": "",
  "maxReviewsPerProduct": 30,
  "resultsWanted": 20,
  "maxPages": 200,
  "sortBy": "MOST_HELPFUL",
  "certifiedBuyerOnly": false,
  "aspectId": "overall",
  "imageWidth": 1280,
  "imageHeight": 1280,
  "imageQuality": 100,
  "includeRawImages": true,
  "concurrency": 5,
  "pageConcurrency": 3,
  "maxRetries": 3,
  "requestDelay": 0,
  "requestTimeoutSecs": 20,
  "dedupeReviews": true,
  "includeProductSummary": true,
  "verboseLogging": true,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `reviewsOverview` (type: `string`):

The most useful fields for every collected review.

## `reviewsFull` (type: `string`):

Every field collected for every review.

## `productSummaries` (type: `string`):

One roll-up record per scraped product: average rating, rating histogram, review counts. Downloadable as JSON, mirroring output\_products.json.

## `runSummary` (type: `string`):

Totals for this run: products processed, reviews collected, proxy tier used, and timing.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "startUrls": [
        "https://www.flipkart.com/adidas-ampligy-m-running-shoes-men/product-reviews/itmab79cd4ce225d"
    ],
    "productIds": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("insights_data/flipkart-reviews-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "startUrls": ["https://www.flipkart.com/adidas-ampligy-m-running-shoes-men/product-reviews/itmab79cd4ce225d"],
    "productIds": [],
}

# Run the Actor and wait for it to finish
run = client.actor("insights_data/flipkart-reviews-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "startUrls": [
    "https://www.flipkart.com/adidas-ampligy-m-running-shoes-men/product-reviews/itmab79cd4ce225d"
  ],
  "productIds": []
}' |
apify call insights_data/flipkart-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,insights_data/flipkart-reviews-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/gX77yyHafYcD0aiTR/builds/LaL4QaBmz8qG0FDo1/openapi.json