# Sephora Products & Reviews Scraper (`kibaale/sephora-product-reviews-scraper`) Actor

Scrapes Sephora product listings and customer reviews: brand, product name, price, SKU, rating, and full review text with author, date and helpful votes. Pick any category or product. No browser, no login.

- **URL**: https://apify.com/kibaale/sephora-product-reviews-scraper.md
- **Developed by:** [kibalee](https://apify.com/kibaale) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $7.00 / 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.

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

## Sephora Products & Reviews Scraper

Scrapes **Sephora product listings and customer reviews**. No browser, no login.

### What you get

One record per review:

```json
{
  "brandName": "rhode",
  "productName": "Glazing Milk Hydrating Ceramic Facial Essence",
  "productId": "P519160",
  "skuId": "2898419",
  "listPrice": "$20.00 - $32.00",
  "rating": 4.5,
  "reviewCount": 2595,
  "productUrl": "https://www.sephora.com/product/glazing-milk-P519160",
  "rating": 5,
  "title": null,
  "author": "Madsb13",
  "date": "2026-09-12T07:29:42.000+00:00",
  "text": "Found this product very light weight and dewy...",
  "isRecommended": true,
  "helpfulVotes": 3,
  "totalReviewCount": 2595
}
```

With `scrapeReviews` off, you get one record per product instead.

### Input

| Field | Description |
|---|---|
| `categoryUrls` | Category paths, e.g. `/shop/skincare`, `/shop/makeup` (default `["/shop/skincare"]`) |
| `maxProductsPerCategory` | Products per category, 1-100 (default `20`) |
| `scrapeReviews` | Fetch review text per product (default `true`) |
| `maxReviewsPerProduct` | Reviews per product, 1-1000 (default `20`) |

### What it does not do

- It does not cover Sephora pages that are not product categories or product pages.
- Review availability depends on what Sephora publishes per product; products with no reviews return the product record only.
- Each run is a snapshot — new reviews appear after re-runs.

### Output

One record per review (or per product) in the dataset, flattened fields as shown above.

# Actor input Schema

## `categoryUrls` (type: `array`):

Sephora category paths, e.g. /shop/skincare, /shop/makeup, /shop/fragrance.

## `maxProductsPerCategory` (type: `integer`):

How many products to scrape per category (category pages carry ~60).

## `scrapeReviews` (type: `boolean`):

Fetch review text for every product (rating, author, date, helpful votes).

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

Stop after this many reviews per product.

## `useProxy` (type: `boolean`):

Route requests through the account's residential proxy group (needed because Sephora blocks datacenter IPs).

## Actor input object example

```json
{
  "categoryUrls": [
    "/shop/skincare"
  ],
  "maxProductsPerCategory": 20,
  "scrapeReviews": true,
  "maxReviewsPerProduct": 20,
  "useProxy": true
}
```

# Actor output Schema

## `results` (type: `string`):

Review records stored in the run's default dataset

# 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 = {
    "categoryUrls": [
        "/shop/skincare"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("kibaale/sephora-product-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 = { "categoryUrls": ["/shop/skincare"] }

# Run the Actor and wait for it to finish
run = client.actor("kibaale/sephora-product-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 '{
  "categoryUrls": [
    "/shop/skincare"
  ]
}' |
apify call kibaale/sephora-product-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,kibaale/sephora-product-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/xOkiED0nSJn3VDrUW/builds/HMs5MCTzl8bvKkmlR/openapi.json