Femaledaily Reviews Scraper: Extract Beauty Product Reviews at Scale

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What Is Femaledaily.com?

Femaledaily.com is one of Asia's largest beauty and cosmetics review platforms, hosting hundreds of thousands of user-generated product reviews. Beauty brands, retailers, and researchers rely on Femaledaily reviews to understand consumer sentiment, product performance, and market trends. Manually collecting review data is inefficient — the Femaledaily Reviews Scraper automates extraction, delivering structured reviewer insights and product feedback at scale.

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Overview

The Femaledaily Reviews Scraper extracts comprehensive product reviews from Femaledaily.com, converting unstructured feedback into machine-readable records. It captures reviewer demographics, ratings, photos, recommendations, and detailed comments — everything needed for sentiment analysis or product intelligence.

Ideal users include:

• Beauty brands monitoring consumer perception and product feedback
• Market researchers analyzing cosmetic product trends and competitor positioning
• Sentiment analysts building datasets for NLP and feedback analysis
• E-commerce platforms aggregating review data for product comparison tools
• Retailers tracking product performance across beauty categories

Key features include flexible filtering by skin type, age range, and review order; configurable item limits; and error resilience via ignore_url_failures.

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Input Format

The scraper accepts a JSON configuration object:

{
  "urls": [
    "https://reviews.femaledaily.com/products/cleanser/toner/viva-cosmetics/air-mawar?cat=&cat_id=0&age_range=&skin_type=&skin_tone=&skin_undertone=&hair_texture=&hair_type=&order=newest&page=2"
  ],
  "ignore_url_failures": true,
  "max_items_per_url": 200
}

Configuration Parameters

Parameter	Type	Description
urls	Array	Direct links to Femaledaily product review pages. Can include filter parameters for skin type, age range, tone, undertone, or sort order (newest, most helpful, etc.)
max_items_per_url	Integer	Maximum number of reviews to extract per URL (e.g., 200 for comprehensive collection)
ignore_url_failures	Boolean	If true, scraper continues if some URLs fail; if false, entire run stops on first error

URL Structure

Femaledaily review URLs follow this pattern:

https://reviews.femaledaily.com/products/[category]/[subcategory]/[brand]/[product]

Optional query parameters allow filtering:

• page=2 — target specific review pages
• skin_type=oily — filter by skin type
• age_range=25-30 — filter by reviewer age
• order=newest or order=most_helpful — sort reviews
• skin_tone=tan, skin_undertone=warm — demographic filters

Tip: Use filter parameters to collect reviews from specific user segments, enabling targeted market research.

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Output Format

Sample output

{
  "id": 0,
  "reviewer_id": 2814310,
  "date": "2026-02-08T07:11:11.915Z",
  "text": "Produk dari viva ini ga usa di ragukan lagi deh bestieee.. baguss pol. \nBuat skin barier dan melebab kan kulit. \nProduk dr viva kebanyakan cocok di kulitku yang kering dan oily ini. \nMantaappp produk viva 🫶🏻\nSemoga tetap dan semakin berjaya yaaa",
  "is_like": false,
  "total_likes": 0,
  "total_comments": 0,
  "is_recommended": "y",
  "duration_of_use": "3 months - 6 months",
  "place_to_get": {
    "place": "Shopee",
    "order": [
      "Online",
      "E-Commerce",
      "Shopee"
    ],
    "is_freetext": false
  },
  "is_expand": false,
  "comment": "",
  "comments": {
    "data": [],
    "pagination": {}
  },
  "rating": {
    "average": 0,
    "user": 5,
    "total": 0
  },
  "user": {
    "id": 1743565,
    "username": "Miraayunanda",
    "is_verified": false,
    "picture": "http://image.femaledaily.com/dyn/480/images/user-pics/72acded3acd45e4c8b6ed680854b8ab1u43uwt1770533174790.jpeg",
    "age_range": "19 - 24",
    "info": "Dry Skin,19 - 24",
    "skin": {
      "type": "Dry",
      "tone": "Medium",
      "undertone": "Warm"
    }
  },
  "product": {
    "id": 2500,
    "image": "https://image.femaledaily.com/dyn/210/images/prod-pics/product_1630998319_307543_1_800x800.jpg",
    "name": "",
    "slug": "air-mawar",
    "shade": "",
    "brand": {
      "name": "Viva Cosmetics",
      "slug": "viva-cosmetics"
    },
    "category": {
      "name": "",
      "slug": "",
      "parent": {
        "name": "",
        "slug": ""
      }
    }
  },
  "photos": [
    {
      "img_url": "https://s3.ap-southeast-1.amazonaws.com/assets.femaledaily.com/images/user-review/imgfdn-6fba17c3-9690-4126-95b9-daa7767aa76b.jpg",
      "rvwr_image_id": 233328,
      "img_alt": "Air Mawar imgfdn-a4c924b2-4e70-47b4-bd1e-29b6a0cbb203",
      "rvwr_unique_code": "imgfdn-a4c924b2-4e70-47b4-bd1e-29b6a0cbb203"
    }
  ],
  "from_url": "https://reviews.femaledaily.com/products/cleanser/toner/viva-cosmetics/air-mawar?cat=&cat_id=0&age_range=&skin_type=&skin_tone=&skin_undertone=&hair_texture=&hair_type=&order=newest&page=2"
}

Each scraped review returns 17 fields capturing review metadata, content, and engagement:

Review Identity & Metadata

Field	Meaning	Example
ID	Unique review identifier in the Femaledaily system	"review_12345"
Reviewer ID	Unique identifier for the user who posted the review	"user_789"
Date	Review submission date	"2024-01-15"
Product	Product name and metadata	"Viva Cosmetics Air Mawar Toner"
User	Reviewer's username and profile info	"beauty_blogger_123"

Review Content

Field	Meaning	Usage
Text	Main review body — detailed written feedback on product quality, effectiveness, and user experience	Sentiment analysis, feedback mining, product insights
Comment	Additional reviewer notes or follow-up comments	Context for review sentiment
Comments	Nested comments or replies from other users	Community engagement metrics
Photos	Array of review images uploaded by the reviewer	Visual product demonstrations, packaging photos

Review Ratings & Recommendations

Field	Meaning	Impact
Rating	Numerical score given by reviewer (typically 1–5 stars)	Overall satisfaction measurement, aggregation for average ratings
Is Recommended	Boolean flag: whether reviewer recommends the product	Purchase intent signal
Is Like	Boolean flag: whether reviewer marked the review as helpful/liked	Review credibility and usefulness
Total Likes	Count of other users who found this review helpful	Credibility ranking for review sorting
Total Comments	Number of community responses to the review	Engagement and discussion level

Product Usage & Demographics

Field	Meaning	Segmentation Value
Duration Of Use	How long the reviewer has used the product (e.g., "3 months", "1 year")	Product reliability and long-term satisfaction
Place To Get	Where reviewer purchased the product (online store, physical retail, etc.)	Channel performance insights
Is Expand	Indicates if the review was expanded/read in full by other users	Review relevance and visibility

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How to Use

1. Navigate Femaledaily — Visit https://reviews.femaledaily.com and browse product reviews by category (cleansers, toners, serums, etc.).

2. Copy review page URLs — Find a product with reviews you want to extract. Copy the full URL, including any filter parameters (skin type, age range, sort order).

3. Configure input JSON — Paste URLs into the urls array. Set max_items_per_url based on your needs (e.g., 200 for all available reviews, 50 for a sample).

4. Enable failure tolerance — Set ignore_url_failures: true for bulk runs to skip broken links without interrupting the scrape.

5. Execute the scraper — Start the actor and monitor the run log for errors or completion status.

6. Export & analyze — Download results as JSON, CSV, or Excel. Use the data for sentiment analysis, competitive research, or trend identification.

Handling common issues:

• If a URL returns no reviews, verify it's a product review page (not a category listing).
• Use URL filters to narrow results before scraping, reducing quota usage.
• For large datasets, split URLs across multiple runs to improve reliability.

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Use Cases & Business Value

Beauty brand teams monitor how their products are perceived versus competitors, identifying strengths (long-lasting, affordable) and weaknesses (irritation, packaging).

Market researchers track emerging trends — e.g., increased demand for K-beauty ingredients or sustainable packaging — by analyzing review text and ratings over time.

Product development teams use feedback to guide formulation improvements and feature requests mentioned in reviews.

E-commerce platforms integrate review data into product cards, enriching search results and building customer confidence.

Influencers and beauty bloggers use Femaledaily review data to identify trending products and develop content strategies.

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Conclusion

The Femaledaily Reviews Scraper transforms raw review pages into actionable consumer intelligence. With 17 detailed data fields and flexible filtering, it enables brands, researchers, and retailers to understand market sentiment at scale — replacing hours of manual copying with instant, structured data exports.