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Target.com Review Scraper - Automated Review Extraction

Introduction

Target.com stands as one of America's largest retail platforms, hosting millions of customer reviews across countless products. These reviews represent invaluable insights into consumer behavior, product satisfaction, and market trends. Manual collection of this review data is time-intensive and impractical for businesses needing to analyze competitor products, monitor brand sentiment, or conduct market research at scale.

The Target Review Scraper addresses this challenge by automating the extraction of comprehensive review data from Target.com product pages. This tool transforms hours of manual work into minutes of automated data collection, enabling businesses to make data-driven decisions based on authentic customer feedback.

Comprehensive Review Data Extraction

The Target Review Scraper is designed specifically for extracting detailed customer review information from Target.com product pages. This specialized tool captures not just basic review content, but the complete metadata and contextual information that makes review analysis truly valuable.

The scraper excels at handling Target.com's dynamic content structure, ensuring reliable data extraction even from pages with heavy JavaScript implementation. It's built to respect rate limits and maintain consistent performance across large datasets, making it suitable for both small-scale research and enterprise-level data collection operations.

Primary users include market researchers, e-commerce analysts, brand managers, competitive intelligence teams, and data scientists who need structured access to Target's customer review ecosystem for sentiment analysis, product research, or consumer behavior studies.

Input and Output Details

Input Configuration

Example url 1: https://www.target.com/p/women-s-pleated-maxi-dress-a-new-day/-/A-94349635

Example url 2: https://www.target.com/p/hp-15-6-34-laptop-intel-pentium-n200-8gb-ram-256gb-ssd-storage-blue-15-fd0015tg/-/A-91188094#lnk=sametab

Example url 3: https://www.target.com/p/women-39-s-pleated-maxi-dress-a-new-day-8482-coral-xl/-/A-94199349

Example Screenshot of review information page:

The scraper accepts a JSON configuration with the following parameters:

{
  "max_retries_per_url": 2, // Maximum waiting time when accessing the links you provided.
  "proxy": { // Add a proxy to ensure that during the data collection process, you are not detected as a bot.
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL" 
    ],
    "apifyProxyCountry": "SG" // You should choose an Country that coincides with the Country you want to collect data from
  },
  "max_items_per_url": 20, // Total page you want scrape
  "urls": [ // Links to detail pages.
    "https://www.target.com/p/women-s-pleated-maxi-dress-a-new-day/-/A-94349635",
    "https://www.target.com/p/hp-15-6-34-laptop-intel-pentium-n200-8gb-ram-256gb-ssd-storage-blue-15-fd0015tg/-/A-91188094#lnk=sametab",
    "https://www.target.com/p/women-39-s-pleated-maxi-dress-a-new-day-8482-coral-xl/-/A-94199349"
  ]
}

Input Parameters Explained:

• max_retries_per_url: Controls reliability by setting retry attempts for failed requests
• proxy settings: Essential for avoiding bot detection during large-scale scraping operations
• max_items_per_url: Limits the number of reviews extracted per product to manage data volume
• urls: Array of specific Target product page URLs to scrape

Output:

The scraper delivers structured data with the following fields:

[ // List of review information
  {
  "id": "7d87dc26-34d8-499a-8a37-e3cc9b4a0622",
  "external_id": "8396d355-cdad-59fa-b836-ffa35963f42d",
  "channel": "TARGET",
  "tcin": "94349635",
  "rating": 1,
  "rating_range": 5,
  "secondary_ratings_order": [
    "Comfort",
    "Style",
    "Value"
  ],
  "secondary_ratings": {
    "comfort": {
      "id": "Comfort",
      "value": 2,
      "label": "comfort",
      "value_range": 5,
      "display_type": "NORMAL"
    },
    "style": {
      "id": "Style",
      "value": 3,
      "label": "style",
      "value_range": 5,
      "display_type": "NORMAL"
    },
    "value": {
      "id": "Value",
      "value": 1,
      "label": "value",
      "value_range": 5,
      "display_type": "NORMAL"
    }
  },
  "title": "Beware it is see through!",
  "text": "Loved it until I realized it was completely sheer and could see everything under it! If it was lined would have been perfect. I tried the coral color.",
  "is_verified": true,
  "status": "APPROVED",
  "photos": [],
  "badges_order": [
    "verifiedPurchaser"
  ],
  "badges": {
    "verified_purchaser": {
      "id": "verifiedPurchaser",
      "content_type": "REVIEW",
      "badge_type": "Custom"
    }
  },
  "source_client": "targetcom",
  "syndication_source": null,
  "is_ratings_only": false,
  "client_response_count": 0,
  "client_responses": [],
  "entities": [],
  "tags": [],
  "author": {
    "external_id": "448240110",
    "nickname": "Celeg"
  },
  "is_syndicated": false,
  "feedback": {
    "helpful": 3,
    "unhelpful": 0,
    "inappropriate": 0
  },
  "submitted_at": "2025-06-13T15:31:09.000+00:00",
  "modified_at": "2025-07-01T15:53:04.000+00:00",
  "reviewer_attributes": [],
  "is_incentivized": false,
  "from_url": "https://www.target.com/p/women-s-pleated-maxi-dress-a-new-day/-/A-94349635"
}, // ... Many other review details
]

Output Format

The scraper delivers comprehensive review data in structured JSON format with 26 distinct data fields:

Core Identifiers & Metadata:

• ID: Unique review identifier for database management
• External ID: Target's internal review reference
• Channel: Review source channel designation
• TCIN: Target's internal product catalog identifier

Rating Information:

• Rating: Primary numerical rating (typically 1-5 scale)
• Rating Range: Available rating scale parameters
• Secondary Ratings Order: Sequence of additional rating criteria
• Secondary Ratings: Detailed breakdown of aspect-specific ratings

Review Content:

• Title: Review headline or summary title
• Text: Complete review text content
• Photos: Associated review images or media
• Tags: Categorization labels assigned to reviews

Verification & Status:

• Is Verified: Indicates verified purchase status
• Status: Review publication and moderation status
• Badges Order: Sequence of review quality indicators
• Badges: Special designations (Top Reviewer, Verified Buyer, etc.)

Source Information:

• Source Client: Originating platform or application
• Syndication Source: Third-party review syndication data
• Is Syndicated: Flag for syndicated content
• Is Ratings Only: Indicates rating-only submissions without text

Interaction Data:

• Client Response Count: Number of responses from businesses
• Client Responses: Actual response content from Target or brands
• Feedback: Helpful/unhelpful votes and engagement metrics

Author Information:

• Author: Reviewer identification (anonymized as appropriate)
• Reviewer Attributes: Demographics and reviewer characteristics
• Is Incentivized: Indicates incentivized review status

Temporal Data:

• Submitted At: Original review submission timestamp
• Modified At: Last modification date and time

Additional Context:

• Entities: Named entities extracted from review text
• Is Ratings Only: Pure rating submissions without textual content

This comprehensive dataset enables sophisticated analysis including sentiment tracking, rating distribution analysis, reviewer behavior patterns, and temporal trend identification.

Implementation Guide

Step 1: URL Preparation Compile Target.com product URLs ensuring they follow the correct format. URLs should point directly to product detail pages where reviews are displayed.

Step 2: Configuration Setup Configure proxy settings using residential proxies to avoid detection. Set appropriate retry limits and item counts based on your data volume requirements.

Step 3: Rate Management Implement reasonable delays between requests. Target.com employs bot detection, so maintaining human-like browsing patterns is essential for consistent results.

Step 4: Data Validation Review extracted data for completeness and accuracy. Some products may have limited review data, while others contain extensive review histories.

Common Issues & Solutions:

• Empty results often indicate proxy issues or rate limiting
• Partial data extraction typically resolves with reduced request frequency
• JavaScript-heavy pages may require additional processing time

Business Value and Applications

Time Efficiency: Automated extraction replaces hours of manual data collection with minutes of automated processing, enabling real-time competitive analysis and market monitoring.

Market Intelligence: Access to structured review data enables comprehensive competitor analysis, product positioning insights, and consumer sentiment tracking across product categories.

Quality Assurance: Monitor product reception, identify quality issues early, and track customer satisfaction trends over time through comprehensive review analysis.

Strategic Planning: Data-driven insights support product development, pricing strategies, and marketing campaign optimization based on authentic customer feedback patterns.

The Target Review Scraper provides essential infrastructure for businesses requiring systematic access to Target.com's customer review ecosystem, enabling data-driven decision making in competitive retail environments.

Ready to Extract Target Review Data? Configure your scraper today and transform customer review analysis from manual effort into automated intelligence gathering that drives business growth.

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Your feedback

We are always working to improve Actors' performance. So, if you have any technical feedback about Target.com Review Query Scraper or simply found a bug, please create an issue on the Actor's Issues tab in Apify Console.