# Shopsy Reviews Scraper (`stealth_mode/shopsy-reviews-scraper`) Actor

Automate product review collection from Shopsy.in with this powerful scraper. Extract author details, ratings, review text, certification status, and 12+ fields per review — perfect for sentiment analysis, market research, and competitor tracking.

- **URL**: https://apify.com/stealth\_mode/shopsy-reviews-scraper.md
- **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community)
- **Categories:** Automation, Developer tools, E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#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

## Shopsy Reviews Scraper: Extract Product Reviews & Ratings Effortlessly

***

### What Is Shopsy.in?

Shopsy.in is an Indian e-commerce platform featuring a wide range of products including cosmetics, fashion, electronics, and more. Each product listing includes a dedicated reviews section where customers share detailed feedback, ratings, and experiences. Manually collecting and analyzing hundreds of reviews is labor-intensive — the **Shopsy Reviews Scraper** automates this process, delivering structured review data ready for analysis.

***

### Overview

The **Shopsy Reviews Scraper** extracts comprehensive product review data from Shopsy.in pages, transforming unstructured customer feedback into clean, structured datasets. It is designed for:

- **E-commerce analysts** monitoring product sentiment and ratings trends
- **Market researchers** conducting competitive product analysis
- **Quality assurance teams** tracking customer feedback patterns
- **Data scientists** building sentiment analysis and NLP models
- **Brands** tracking competitor product perception

The scraper handles multiple reviews per URL, supports error resilience via `ignore_url_failures`, and configurable collection limits to match your research scope and budget.

***

### Input Format

The scraper accepts a JSON configuration object with three main parameters:

```json
{
  "urls": [
    "https://www.shopsy.in/onfroi-lipstick-combo-pack-8-liquid-matte-long-lasting-smudge-proof/product-reviews/itmab6007e15a0be?pid=XLPHE92VVRNRSJFZ&lid=LSTXLPHE92VVRNRSJFZLVB69H&mid=FLIPKART&cat=ShopsyMakeupFragrances&vert=ShopsyLipstick&page=3"
  ],
  "ignore_url_failures": true,
  "max_items_per_url": 200
}
```

| Parameter | Description | Example |
|---|---|---|
| `urls` | Array of Shopsy product review page URLs to scrape. Include full URLs with query parameters. | Review page URLs with `product-reviews` path |
| `max_items_per_url` | Maximum number of reviews to extract per URL (1–200). Controls volume and execution time. | `200` for comprehensive collection; `20` for quick samples |
| `ignore_url_failures` | Boolean flag. If `true`, the scraper continues if individual URLs fail; if `false`, it stops on first failure. | `true` for reliability in bulk runs |

> **Tip:** Use complete review page URLs including pagination parameters. Each URL typically contains 15–30 reviews per page; adjust `max_items_per_url` accordingly.

***

### Output Format

**Example output record:**

```json
{
  "author": "Ruchi Verma",
  "certified_buyer": true,
  "created": "6 months ago",
  "downvote": {
    "type": "VoteValue",
    "count": 21,
    "is_selected": false
  },
  "review_property_map": {
    "v_e_r_i_f_i_e_d__p_u_r_c_h_a_s_e": true
  },
  "review_type_display_text": null,
  "text": "Very nice product 😀 \nI am very happy with this product 🙂",
  "title": "Excellent",
  "total_count": 64,
  "upvote": {
    "type": "VoteValue",
    "count": 43,
    "is_selected": false
  },
  "url": "/reviews/XLPHE92VVRNRSJFZ:2?reviewId=ce2be012-0934-4237-9178-cba7ecf1fe11",
  "user_badge": null,
  "from_url": "https://www.shopsy.in/onfroi-lipstick-combo-pack-8-liquid-matte-long-lasting-smudge-proof/product-reviews/itmab6007e15a0be?pid=XLPHE92VVRNRSJFZ&lid=LSTXLPHE92VVRNRSJFZLVB69H&mid=FLIPKART&cat=ShopsyMakeupFragrances&vert=ShopsyLipstick"
}
```

Each scraped review returns a structured record with 12+ fields:

#### Review Content & Author Information

| Field | Meaning |
|---|---|
| `Author` | Username or display name of the reviewer |
| `Text` | Full review text written by the customer |
| `Title` | Review headline or summary title |
| `Certified Buyer` | Boolean indicating whether the reviewer purchased the product (verified badge) |
| `User Badge` | Special badges or labels assigned to the reviewer (e.g., "Trusted Reviewer," "Top Contributor") |

#### Rating & Engagement

| Field | Meaning |
|---|---|
| `Upvote` | Number of "helpful" votes the review received |
| `Downvote` | Number of "not helpful" votes the review received |
| `Total Count` | Total engagement count (sum of upvotes and downvotes) |
| `Created` | Timestamp when the review was posted |

#### Review Metadata

| Field | Meaning |
|---|---|
| `URL` | Direct link to the individual review on Shopsy |
| `Review Type Display Text` | Classification of the review (e.g., "Positive," "Negative," "Neutral") or star rating displayed |
| `Review Property Map` | Additional metadata object containing structured review properties (rating scale, category flags, etc.) |
-----------------------------------------------------------------------------------------------------------------------------------

### How to Use

1. **Locate review URLs** — Navigate to a Shopsy product page and scroll to the "Customer Reviews" section. Click on a review page or filter; copy the full URL from your browser.
2. **Prepare configuration** — Paste URLs into the `urls` array. Set `max_items_per_url` based on how many reviews you need (20 for quick tests, 100–200 for comprehensive analysis).
3. **Handle errors** — Enable `ignore_url_failures: true` for bulk runs. This ensures the scraper continues if one URL fails due to network or structure changes.
4. **Run the scraper** — Submit the configuration and monitor the execution log for status updates.
5. **Process results** — Export as JSON, CSV, or Excel. Clean and standardize the `Created` dates and `Review Property Map` for downstream analysis.

**Common best practices:**

- Test with 1–2 URLs first to verify output structure.
- Use `max_items_per_url: 50–100` to balance completeness and speed.
- Reviews from "Certified Buyer" accounts typically carry more weight in sentiment analysis.

***

### Use Cases & Business Value

- **Sentiment analysis:** Train models to classify positive/negative reviews at scale
- **Competitor benchmarking:** Compare product ratings and customer feedback across competitors
- **Quality insights:** Identify common product issues or praised features from customer feedback
- **Marketing research:** Understand customer pain points and messaging opportunities
- **Reputation monitoring:** Track brand perception changes over time

By automating review collection, you save days of manual work and unlock insights that guide product development, marketing strategy, and customer service improvements.

***

### Conclusion

The **Shopsy Reviews Scraper** is an essential tool for anyone serious about e-commerce intelligence. Whether you're conducting market research, analyzing sentiment, or tracking competitor products, this scraper delivers structured review data in minutes. Leverage customer feedback to make data-driven business decisions and stay ahead in the competitive Indian e-commerce landscape.

# Actor input Schema

## `urls` (type: `array`):

Add the URLs of the product reviews urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.

## `ignore_url_failures` (type: `boolean`):

If true, the scraper will continue running even if some URLs fail to be scraped.

## `max_items_per_url` (type: `integer`):

The maximum number of items to scrape per URL.

## Actor input object example

```json
{
  "urls": [
    "https://www.shopsy.in/onfroi-lipstick-combo-pack-8-liquid-matte-long-lasting-smudge-proof/product-reviews/itmab6007e15a0be?pid=XLPHE92VVRNRSJFZ&lid=LSTXLPHE92VVRNRSJFZLVB69H&mid=FLIPKART&cat=ShopsyMakeupFragrances&vert=ShopsyLipstick&page=3"
  ],
  "ignore_url_failures": true,
  "max_items_per_url": 20
}
```

# 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 = {
    "urls": [
        "https://www.shopsy.in/onfroi-lipstick-combo-pack-8-liquid-matte-long-lasting-smudge-proof/product-reviews/itmab6007e15a0be?pid=XLPHE92VVRNRSJFZ&lid=LSTXLPHE92VVRNRSJFZLVB69H&mid=FLIPKART&cat=ShopsyMakeupFragrances&vert=ShopsyLipstick&page=3"
    ],
    "ignore_url_failures": true,
    "max_items_per_url": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("stealth_mode/shopsy-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 = {
    "urls": ["https://www.shopsy.in/onfroi-lipstick-combo-pack-8-liquid-matte-long-lasting-smudge-proof/product-reviews/itmab6007e15a0be?pid=XLPHE92VVRNRSJFZ&lid=LSTXLPHE92VVRNRSJFZLVB69H&mid=FLIPKART&cat=ShopsyMakeupFragrances&vert=ShopsyLipstick&page=3"],
    "ignore_url_failures": True,
    "max_items_per_url": 20,
}

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

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

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

```

## CLI example

```bash
echo '{
  "urls": [
    "https://www.shopsy.in/onfroi-lipstick-combo-pack-8-liquid-matte-long-lasting-smudge-proof/product-reviews/itmab6007e15a0be?pid=XLPHE92VVRNRSJFZ&lid=LSTXLPHE92VVRNRSJFZLVB69H&mid=FLIPKART&cat=ShopsyMakeupFragrances&vert=ShopsyLipstick&page=3"
  ],
  "ignore_url_failures": true,
  "max_items_per_url": 20
}' |
apify call stealth_mode/shopsy-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=stealth_mode/shopsy-reviews-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/YvpMQWl5lkmse7ThB/builds/TWSx6gJqF5WbIlSFm/openapi.json