Pampers Reviews Spider

Introduction

The Pampers Reviews Spider is a powerful Apify Actor designed to scrape and extract detailed customer reviews from Pampers product pages on the official website. It enables users to gather authentic feedback, ratings, and insights into diaper performance, helping businesses and researchers make data-driven decisions. With reliable data extraction and customizable options, this Actor streamlines the process of collecting high-quality review data for analysis.

Features

• Comprehensive Review Extraction: Captures key details like ratings, titles, full review text, user nicknames, submission times, and verification status from Pampers product pages.
• Flexible URL Input: Supports multiple URLs for batch processing, allowing targeted scraping of specific products or categories.
• Customizable Item Limits: Set maximum items to process, ensuring efficient runs without overwhelming resources.
• High-Quality Data: Ensures data integrity with structured JSON output, including metadata like actor and run IDs for traceability.
• Fast and Scalable: Built on Apify's robust infrastructure for quick execution and handling large volumes of reviews.
• Error-Resilient: Includes built-in handling for common scraping challenges, such as dynamic content or rate limits.
• Export-Ready: Outputs data in JSON format, easily convertible to CSV or Excel for further analysis.

Input Parameters

Parameter	Type	Required	Description	Example
Urls	array	Yes	An array of URLs pointing to Pampers product review pages to scrape. Each URL must be a valid HTTP/HTTPS link.	["https://www.pampers.com/en-us/products/pampers-swaddlers-diapers"]
itemLimit	integer	No	The maximum number of review items to process and extract. Defaults to 10 if not specified.	50

Example Usage

Input Configuration

{
  "Urls": [
    "https://www.pampers.com/en-us/products/pampers-swaddlers-diapers"
  ],
  "itemLimit": 10
}

Output Example

[
  {
    "product_id": "Pampers_Swaddlers",
    "product_url": "https://www.pampers.com/en-us/products/pampers-swaddlers-diapers",
    "review_id": "246264815",
    "rating": 5,
    "title": "Best choice",
    "review_text": "I switched to pampers after I found that Huggies was not a good fit for my son. Pampers has better absorbency, holds more liquids, doesn\u2019t leave behind particles on the skin and fits comfortably. The price point is lies than other major brands and I love that they have reward points for purchasing diapers.",
    "user_nickname": "Brandy",
    "submission_time": "2025-12-01T12:00:37.000+00:00",
    "is_recommended": null,
    "total_feedback_count": 0,
    "total_positive_feedback": 0,
    "total_negative_feedback": 0,
    "verified_purchaser": false,
    "incentivized_review": "False",
    "actor_id": "Qmg8kvfUZezuL1h3G",
    "run_id": "pw3doGecaRZ9ZDO1d"
  }
]

Use Cases

• Market Research: Analyze customer sentiment and trends in diaper preferences to inform product development.
• Competitive Intelligence: Compare Pampers reviews with competitors to identify strengths and weaknesses.
• Price Monitoring: Track feedback related to pricing and value, aiding in dynamic pricing strategies.
• Content Aggregation: Collect reviews for content marketing, such as blog posts or social media insights.
• Academic Research: Gather data for studies on consumer behavior in baby care products.
• Business Automation: Automate review collection for dashboards or reporting tools in e-commerce operations.

Installation and Usage

1. Search for "Pampers Reviews Spider" in the Apify Store.
2. Click "Try for free" or "Run".
3. Configure input parameters (e.g., URLs and item limit).
4. Click "Start" to begin extraction.
5. Monitor progress in the log.
6. Export results in your preferred format (JSON, CSV, Excel).

Output Format

The Actor outputs a JSON array of review objects. Each object includes fields such as product_id (unique product identifier), product_url (source URL), review_id (unique review ID), rating (numerical rating out of 5), title (review headline), review_text (full review content), user_nickname (reviewer's name), submission_time (ISO timestamp), is_recommended (boolean or null), feedback counts, verified_purchaser (boolean), incentivized_review (string), and metadata like actor_id and run_id. This structured format ensures easy parsing and integration into analytics tools.

Support

For custom/simplified outputs or bug reports, please contact:

• Email: support@getdataforme.com
• Subject line: "custom support"
• Contact form: https://getdataforme.com/contact/

We're here to help you get the most out of this Actor!