Dollartree Review Parser Spider

The Dollartree Review Parser Spider is an Apify Actor designed to scrape and extract detailed product reviews from Dollartree.com. It efficiently collects review data, including ratings, sentiments, and metadata, enabling users to analyze customer feedback for products like baby wipes and other items. This tool is ideal for businesses, researchers, and analysts seeking actionable insights from e-commerce reviews.

Features

• Comprehensive Review Extraction: Captures full review details such as ratings, titles, bodies, and sentiments from Dollartree product pages.
• Structured Data Output: Provides clean, JSON-formatted data with fields like Review_Id, Rating, and Product_Name for easy integration.
• High Reliability: Handles dynamic web content and ensures data accuracy through robust parsing logic.
• Scalable Performance: Processes multiple URLs efficiently, supporting batch scraping for large-scale data collection.
• Metadata Enrichment: Includes additional attributes like product segments, brands, and timestamps for deeper analysis.
• Error-Resilient: Built-in handling for common scraping challenges, such as rate limits and page variations.
• Apify Integration: Seamlessly runs on the Apify platform with simple input configuration and export options.

Input Parameters

Parameter	Type	Required	Description	Example
Urls	array	No	An array of URLs pointing to Dollartree product pages from which to extract reviews. Each URL must be a valid HTTP or HTTPS link.	["https://www.dollartree.com/smart-care-fisher-price-fragrance-free-baby-wipes-72ct-packs/323039"]

Example Usage

To run the Actor, provide the input in JSON format:

{
  "Urls": [
    "https://www.dollartree.com/smart-care-fisher-price-fragrance-free-baby-wipes-72ct-packs/323039"
  ]
}

Example output:

[
  {
    "Product_Id": "",
    "Review_Id": "243042517",
    "Rating": 5,
    "Title": null,
    "Body": null,
    "Sentiment": null,
    "Section": "",
    "Higher_Topic": null,
    "Granular_Topic": null,
    "Source": "Flipkart",
    "Full_Review": "None: None",
    "Review_Type": "Product Review",
    "Title_Trans": null,
    "Body_Trans": null,
    "Full_Review_Trans": "None: None",
    "Product_Name_Trans": "",
    "Product_Segment": "Wipes",
    "Gender": "Unisex",
    "Product_Segment2": "Fragrance Free",
    "Year_Quarter": "2025-Q3",
    "Sub_Brand": "Fisher Price",
    "Format": "Pants",
    "Country": "India",
    "Date": "07-03-2025",
    "Product_Name": "",
    "Brand": "Fisher Price",
    "URL": "https://www.dollartree.com/smart-care-fisher-price-fragrance-free-baby-wipes-72ct-packs/323039",
    "Crawled_Date": "01-14-2026",
    "Product_Name_Slug": "smart-care-fisher-price-fragrance-free-baby-wipes-72ct-packs"
  }
]

Use Cases

• Market Research: Analyze customer sentiments on Dollartree products to identify trends and preferences.
• Competitive Intelligence: Compare review data across similar products to benchmark performance.
• Price Monitoring: Track reviews alongside pricing for dynamic e-commerce strategies.
• Content Aggregation: Collect and aggregate reviews for content creation or reporting.
• Academic Research: Study consumer behavior through structured review data.
• Business Automation: Automate data pipelines for regular insights into product feedback.

Installation and Usage

1. Search for "Dollartree Review Parser Spider" in the Apify Store
2. Click "Try for free" or "Run"
3. Configure input parameters
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 objects, each representing a review. Key fields include:

• Review_Id: Unique identifier for the review.
• Rating: Numerical rating (e.g., 5).
• Body: Review text content.
• Sentiment: Analyzed sentiment (if available).
• Product_Name: Name of the product.
• Brand: Associated brand (e.g., "Fisher Price").
• Date: Review date.
• URL: Source URL.
• Additional metadata like Product_Segment, Country, and Crawled_Date for context.

Data is structured for easy parsing and integration into databases or 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!

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