Target Reviews Spider

Introduction

The Target Reviews Spider is a powerful Apify Actor designed to scrape and extract detailed customer reviews from Target.com product pages. It provides structured data on ratings, reviews, and secondary metrics, enabling businesses and researchers to gain valuable insights into product performance and customer sentiment. This tool simplifies the process of collecting review data at scale, making it ideal for market analysis, competitive intelligence, and automated workflows.

Features

• Comprehensive Review Extraction: Captures full review details including ratings, titles, text, author info, submission dates, and photos/videos.
• Structured JSON Output: Delivers clean, machine-readable data with secondary ratings for quality, taste, value, and more.
• Multi-URL Support: Handles multiple product URLs in a single run for efficient batch processing.
• High Reliability: Built with robust error handling to ensure consistent data extraction even from dynamic web pages.
• Fast Performance: Optimized scraping engine minimizes runtime while respecting rate limits.
• Apify Integration: Seamlessly integrates with Apify's platform for easy scheduling, monitoring, and data export.
• No Coding Required: User-friendly interface with simple input configuration for non-technical users.

Input Parameters

Parameter	Type	Required	Description	Example
ProductUrls	array	Yes	An array of Target.com product URLs to scrape reviews from. Must contain at least one valid URL.	["https://www.target.com/p/premium-basted-young-turkey-frozen-10-16lbs-price-per-lb-good-38-gather-8482/-/A-52610578"]

Example Usage

Input Configuration

{
  "ProductUrls": [
    "https://www.target.com/p/premium-basted-young-turkey-frozen-10-16lbs-price-per-lb-good-38-gather-8482/-/A-52610578"
  ]
}

Output Example

[
  {
    "Tcin": "95072089",
    "Review_Id": "f391442f-8323-4491-9c14-5a33a6c61598",
    "External_Id": "fa8049b9-f91f-5b8d-9799-3f05bbd4a48d",
    "Rating": 1,
    "Title": "Freezer burned",
    "Text": "Very disappointing. Defrosted the turkey to prep for thanksgiving and turned out the turkey has some sign of freezer burn and the smell has the freezer burn smell to it too.",
    "Is_Recommended": false,
    "Is_Verified": true,
    "Photos": [
      "https://target.scene7.com/is/image/Target/GUEST_e783da05-81c0-45ec-999c-e3a7887290a2",
      "https://target.scene7.com/is/image/Target/GUEST_4c88f5b0-5deb-4fa6-865d-747acd29c735"
    ],
    "Videos": [],
    "Author": "Kate",
    "Submitted_At": "2025-11-26T18:17:33.000+00:00",
    "Modified_At": "2025-12-23T18:20:51.000+00:00",
    "Secondary_Ratings": {
      "Quality": {
        "Id": "Quality",
        "Value": 1,
        "Label": "quality",
        "ValueRange": 5,
        "DisplayType": "NORMAL"
      },
      "Taste": {
        "Id": "Taste",
        "Value": 1,
        "Label": "taste",
        "ValueRange": 5,
        "DisplayType": "NORMAL"
      },
      "Value": {
        "Id": "Value",
        "Value": 1,
        "Label": "value",
        "ValueRange": 5,
        "DisplayType": "NORMAL"
      }
    },
    "actor_id": "0knWOq3abaPjpX2Bc",
    "run_id": "NG2Qal7RGDxAydnks"
  }
]

Use Cases

• Market Research: Analyze customer feedback to identify trends in product quality and satisfaction.
• Competitive Intelligence: Compare reviews across similar products to benchmark performance.
• Price Monitoring: Correlate review data with pricing strategies for e-commerce optimization.
• Content Aggregation: Build datasets for sentiment analysis or machine learning models.
• Academic Research: Collect real-world data for studies on consumer behavior.
• Business Automation: Automate review monitoring for brand reputation management.

Installation and Usage

1. Search for "Target Reviews Spider" in the Apify Store.
2. Click "Try for free" or "Run".
3. Configure input parameters by adding product URLs.
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 an array of JSON objects, each representing a single review. Key fields include:

• Tcin: Target's product identifier.
• Review_Id and External_Id: Unique review identifiers.
• Rating: Numerical rating (1-5).
• Title and Text: Review title and body.
• Is_Recommended and Is_Verified: Boolean flags for recommendation and verification.
• Photos and Videos: Arrays of media URLs.
• Author: Reviewer's name.
• Submitted_At and Modified_At: Timestamps in ISO format.
• Secondary_Ratings: Object with sub-ratings (e.g., Quality, Taste, Value) on a 1-5 scale.
• actor_id and run_id: Apify metadata for tracking.

Data is reliable and structured for easy integration into databases or analysis tools.

Error Handling

The Actor includes built-in error handling for common issues like invalid URLs, network timeouts, or page changes. Failed URLs are logged with details; retries are attempted automatically. If errors persist, check the run logs for diagnostics. For unresolved issues, contact support.

Rate Limiting and Best Practices

• Adheres to Target.com's terms of service; avoid overloading servers.
• Limit runs to 10-20 URLs per execution for optimal performance.
• Schedule runs during off-peak hours to minimize delays.
• Use Apify's proxy rotation for better success rates.
• Monitor usage to stay within free tier limits; upgrade for high-volume needs.

Limitations and Considerations

• Only scrapes publicly available reviews; does not access private or moderated content.
• Output may vary with Target.com updates; the Actor is maintained for compatibility.
• Large datasets (thousands of reviews) may require extended run times.
• Ensure URLs are direct product pages; category or search pages are not supported.

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!