Wallgreens Reviews Parser Spider

Introduction

The Wallgreens Reviews Parser Spider is a powerful Apify Actor designed to extract and parse customer reviews from Walgreens product pages powered by Bazaarvoice. It efficiently scrapes review data, including ratings, sentiments, and metadata, enabling businesses and researchers to gain valuable insights into product performance and customer feedback. This tool streamlines data collection for market analysis, competitive intelligence, and decision-making processes.

Features

• Comprehensive Review Extraction: Captures detailed review information such as ratings, titles, bodies, and sentiments from Walgreens product pages.
• High Reliability: Built with robust error handling to ensure consistent data retrieval even from dynamic web content.
• Fast and Scalable: Optimized for performance, capable of processing multiple URLs quickly and handling large volumes of reviews.
• Structured Output: Delivers clean, JSON-formatted data with enriched fields like product IDs, brands, and timestamps for easy integration.
• Flexible Input: Accepts multiple URLs for batch processing, allowing users to scrape reviews from various products in a single run.
• Sentiment Analysis: Includes sentiment classification to help analyze customer opinions at a glance.
• No Coding Required: User-friendly interface on Apify Store, making it accessible for non-technical users.

Input Parameters

Parameter	Type	Required	Description	Example
Urls	array	Yes	An array of URLs pointing to Walgreens product pages from which to scrape reviews. Each URL must be a valid HTTP or HTTPS link.	["https://www.walgreens.com/store/c/coca-cola-soda,-fridge-pack-12-pack/ID=prod6061761-product"]

Example Usage

Input JSON

{
  "Urls": [
    "https://www.walgreens.com/store/c/coca-cola-soda,-fridge-pack-12-pack/ID=prod6061761-product"
  ]
}

Output JSON

[
  {
    "Product_Id": "prod6061761",
    "Review_Id": "369655881",
    "Rating": 5,
    "Title": null,
    "Body": null,
    "Sentiment": null,
    "Section": "",
    "Higher_Topic": null,
    "Granular_Topic": null,
    "Full_Review": "None: None",
    "Review_Type": "Product Review",
    "Title_Trans": null,
    "Body_Trans": null,
    "Full_Review_Trans": "None: None",
    "Product_Name_Trans": "Soda, Fridge Pack 12 pack",
    "Product_Segment": null,
    "Product_Segment2": null,
    "Year_Quarter": "2025-Q4",
    "Sub_Brand": {
      "Id": "352312",
      "Name": "Coca-Cola"
    },
    "Date": "11-17-2025",
    "Product_Name": "Soda, Fridge Pack 12 pack",
    "Brand": {
      "Id": "352312",
      "Name": "Coca-Cola"
    },
    "URL": "https://www.walgreens.com/store/c/coca-cola-soda,-fridge-pack-12-pack/ID=prod6061761-product",
    "Crawled_Date": "11-18-2025"
  }
]

Use Cases

• Market Research and Analysis: Analyze customer sentiments and ratings to understand product popularity and trends.
• Competitive Intelligence: Compare reviews across similar products to identify strengths and weaknesses.
• Price Monitoring: Track feedback related to pricing and value for products.
• Content Aggregation: Collect and aggregate reviews for content creation or reporting.
• Academic Research: Gather data for studies on consumer behavior and product reviews.
• Business Automation: Automate the collection of review data for dashboards or alerts on product performance.

Installation and Usage

1. Search for "Walgreens Reviews 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 data as a JSON array of objects, each representing a single review. Key fields include:

• Product_Id: Unique identifier for the product.
• Review_Id: Unique identifier for the review.
• Rating: Numerical rating (e.g., 1-5).
• Title/Body: Review title and content (may be null if not available).
• Sentiment: Analyzed sentiment of the review.
• Brand/Sub_Brand: Objects containing brand details.
• Date/Crawled_Date: Review date and scraping timestamp.
• URL: Source URL of the product page. Additional fields like translations and topics provide enriched metadata for deeper analysis.

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!