IL MAKIAGE Reviews Scraper

Overview

This actor collects customer reviews from product pages on the IL MAKIAGE website and returns them in a clean, structured dataset suitable for analytics, dashboards, and downstream business workflows.

The scraper is designed to work with product page URLs and does not require manual product identifiers. It automatically gathers available review data and normalizes it into a consistent schema.

Why This Scraper Is Useful

Customer reviews contain valuable signals about: - Product quality and performance - Customer satisfaction and expectations - Market perception and sentiment trends - Regional and language-based feedback differences

Manually collecting and structuring this information is time-consuming and error-prone. This scraper automates the process and produces analysis-ready data.

Input

The actor accepts the following input:

Field Type Required Description

url string ✅ Yes IL MAKIAGE product page URL

max_reviews integer ✅ Yes Maximum number of reviews to collect

Example Input

{
  "url": "https://www.ilmakiage.com/mineral-baked-blush-2596",
  "max_reviews": 500
}

Output

The output is a dataset where each item represents a single review, with the following fields:

Field Description

total Total number of reviews available for the product id Review identifier score Rating score (1--5) votesUp Helpful votes votesDown Not helpful votes content Review text title Review headline createdAt Review date (YYYY-MM-DD) verifiedBuyer Indicates verified purchase sentiment Sentiment score isIncentivized Indicates incentivized review incentiveType Incentive type, if applicable displayName Reviewer display name sourceReviewId Source review identifier label Reviewer country/label productVariants Product variant information language Review language code

Example Output Record

{
  "id": 799801494,
  "score": 5,
  "content": "The color is perfect for my skin!",
  "title": "Baked blush",
  "createdAt": "2026-01-16",
  "verifiedBuyer": true,
  "sentiment": 0.93,
  "displayName": "Sharon S.",
  "language": "en"
}

How This Data Is Useful for Analysis

The structured output enables:

• Rating distribution analysis (1--5 star trends)
• Sentiment analysis over time
• Verified vs non-verified buyer comparisons
• Incentivized review impact evaluation
• Language and regional insights
• Product variant performance comparison

The dataset can be directly consumed by: - BI tools (Tableau, Power BI, Looker) - Data warehouses - Machine learning pipelines - Customer feedback dashboards

Business Value & Use Cases

Using this data, businesses can:

Product & R&D

• Identify recurring product issues
• Validate new product launches
• Improve formulations based on feedback

Marketing & Growth

• Highlight high-performing products
• Leverage authentic customer language in campaigns
• Track sentiment changes after promotions

Customer Experience

• Detect dissatisfaction early
• Prioritize responses to low-rated reviews
• Improve post-purchase experience

Competitive & Market Intelligence

• Monitor customer expectations
• Compare performance across product categories
• Identify gaps and opportunities in the market

Notes

• The actor respects pagination limits and stops automatically when no more reviews are available.
• Output is optimized for large-scale data analysis and automation workflows.

Disclaimer

This actor is intended for data analysis and research purposes. Users are responsible for ensuring compliance with applicable terms and policies when using the collected data.