Target Reviews Scraper

What does Target Reviews Scraper do?

Target Reviews Scraper collects customer reviews and rating data from a single Target product page. Provide a Target product URL or its TCIN, choose how many reviews to save, and receive one structured dataset item per review. The output includes review text, star ratings, recommendation and verification signals, helpful votes, media links, timestamps, and product-level rating summaries.

This Target product review scraper is useful for product quality research, voice of customer analysis, ecommerce reporting, merchandising decisions, sentiment workflows, and competitive intelligence. Results can be downloaded from Apify in JSON, CSV, Excel, or XML, or connected to an existing workflow through the Apify API, webhooks, and integrations.

Why use Target Reviews Scraper?

• Product-level review collection - Focus each run on one Target product and keep the resulting dataset easy to analyze.
• Detailed customer feedback - Save review titles, full text, star ratings, author signals, badges, tags, responses, and secondary ratings when Target publishes them.
• Rating context - Include the product average rating, rating count, review count, recommendation totals, and rating distribution with each review record.
• Media-aware results - Capture review photo and video URLs when customers have attached media.
• Controlled data volume - Set results_wanted to collect a small sample for testing or a larger set for analysis.
• Automation-ready output - Schedule repeat runs, send results to webhooks, or export the dataset for spreadsheets, BI tools, and data pipelines.
• Flexible identification - Use a full Target product URL or pass the product TCIN directly. If both are provided, productId takes precedence for product identification.

What data can you extract from Target product reviews?

Each saved item represents one review. Fields that are missing or empty on the source review are omitted from that item.

Field	Type	Description
product_id	String	Target TCIN used for the run.
product_url	String	Target product page associated with the review.
position	Integer	Sequential position of the review in the run.
page	Integer	Review page index reported for the item.
total_reviews_available	Integer	Total reviews reported for the product.
total_pages_available	Integer	Total review pages reported for the product.
review_id	String	Review identifier.
external_review_id	String	Source review identifier when available.
tcin	String	Product identifier included in the review record when available.
rating	Integer	Star rating assigned by the reviewer.
rating_range	String	Rating scale or range supplied by the source.
title	String	Review title.
text	String	Full review text.
author_nickname	String	Public reviewer nickname.
author_external_id	String	Source author identifier when available.
is_verified	Boolean	Whether the review has a verified purchaser signal.
is_recommended	Boolean	Whether the reviewer recommends the product.
status	String	Review status when supplied by Target.
photos	Array	Photo URLs attached to the review.
videos	Array	Video URLs attached to the review.
badges	Array	Review badges and related display values.
tags	Array	Review tags supplied by the source.
secondary_ratings	Object	Additional scores, such as quality or value, when available.
feedback_helpful	Integer	Helpful votes recorded for the review.
feedback_unhelpful	Integer	Unhelpful votes recorded for the review.
feedback_inappropriate	Integer	Inappropriate feedback votes when available.
client_response_count	Integer	Number of responses associated with the review.
client_responses	Array	Response details when published by the source.
entities	Array or Object	Review entities or extracted source metadata when available.
reviewer_attributes	Array or Object	Reviewer attributes supplied with the review.
is_ratings_only	Boolean	Whether the item contains a rating without full review text.
is_syndicated	Boolean	Whether the source marks the review as syndicated.
is_incentivized	Boolean	Whether the source marks the review as incentivized.
submitted_at	String	Original review submission timestamp.
modified_at	String	Last review modification timestamp.
statistics_review_count	Integer	Product review count at collection time.
statistics_question_count	Integer	Product question count when available.
statistics_recommended_count	Integer	Number of recommending customers when available.
statistics_not_recommended_count	Integer	Number of non-recommending customers when available.
statistics_recommended_percentage	Number	Product recommendation percentage when available.
statistics_reviews_with_images_count	Integer	Number of reviews with images.
statistics_reviews_with_videos_count	Integer	Number of reviews with videos.
statistics_average_rating	Number	Product average star rating.
statistics_rating_count	Integer	Product rating count.
statistics_positive_percentage	Number	Positive rating percentage when available.
statistics_rating_distribution	Object	Rating counts grouped by star level.
statistics_secondary_averages	Object	Product averages for secondary rating dimensions.
scraped_at	String	ISO timestamp for when the item was saved.

How to scrape Target product reviews

1. Open Target Reviews Scraper on Apify.
2. Enter a public Target product URL containing its product identifier, or enter the TCIN in productId.
3. Set results_wanted to the maximum number of reviews you want to save.
4. Enable an Apify Proxy configuration if your run needs additional request reliability.
5. Start the run and inspect the dataset preview.
6. Download the results or connect the dataset to your reporting, monitoring, or automation workflow.

The Actor processes review pages until it reaches your requested limit or Target reports that no more review pages are available. It does not apply a star-rating filter, so results are returned in the source sorting order.

Input Parameters

Parameter	Type	Required	Default	Description
productUrl	String	No*	Target product URL prefill	Full Target product page URL. The TCIN is read from the URL when available.
productId	String	No*	TCIN prefill	Target product TCIN. If supplied, it takes precedence over the TCIN found in productUrl.
results_wanted	Integer	No	20	Maximum number of reviews to save. Must be at least 1.
proxyConfiguration	Object	No	{ "useApifyProxy": false }	Optional Apify Proxy settings for request routing and reliability.

* Provide at least one of productUrl or productId for a successful run.

Usage Examples

Collect Reviews From a Target Product URL

Use a full Target product URL when you want the output to retain the source page address.

{
  "productUrl": "https://www.target.com/p/women-s-slim-fit-modern-ribbed-button-front-tank-top-a-new-day/-/A-94913194",
  "results_wanted": 20
}

Collect Reviews by TCIN

Use productId when you already have the Target product identifier and do not need to provide a product page URL.

{
  "productId": "94913194",
  "results_wanted": 100
}

Collect a Larger Dataset with Proxy Routing

Enable an Apify residential proxy group for larger or scheduled collection jobs when additional request reliability is useful.

{
  "productUrl": "https://www.target.com/p/women-s-slim-fit-modern-ribbed-button-front-tank-top-a-new-day/-/A-94913194",
  "results_wanted": 200,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

Sample Output

The following example shows one review item. Optional fields are included only when the source provides them.

{
  "product_id": "94913194",
  "product_url": "https://www.target.com/p/women-s-slim-fit-modern-ribbed-button-front-tank-top-a-new-day/-/A-94913194",
  "position": 1,
  "page": 0,
  "total_reviews_available": 61,
  "total_pages_available": 4,
  "review_id": "1d44b330-317a-4e69-829a-ef7b9fb39a2d",
  "tcin": "94913194",
  "rating": 5,
  "title": "Great top",
  "text": "Love this tank top. It fits perfectly and feels great.",
  "author_nickname": "Christina",
  "is_recommended": true,
  "is_verified": false,
  "feedback_helpful": 0,
  "submitted_at": "2026-04-05T16:09:21+05:00",
  "statistics_average_rating": 3.56,
  "statistics_rating_count": 101,
  "statistics_review_count": 61,
  "statistics_rating_distribution": {
    "5": 52,
    "4": 19,
    "3": 12,
    "2": 8,
    "1": 10
  },
  "scraped_at": "2026-04-07T10:00:00.000Z"
}

Tips for Best Results

• Use a complete product URL - URLs containing a numeric /A- product identifier make it easier to confirm that the intended product is being collected.
• Test with a small limit - Start with results_wanted: 20 and review the dataset before requesting a larger collection.
• Use the TCIN when available - productId is useful for repeat runs and product lists that already contain Target identifiers.
• Expect optional fields - Photos, videos, badges, responses, and reviewer signals depend on what each review and product page publishes.
• Schedule repeat runs for monitoring - Regular runs can help track new feedback, rating changes, and review volume over time.
• Report source changes - Public product pages can change. Use the Actor's Issues tab if fields stop appearing or a run behaves unexpectedly.

Integrations and Export Formats

• Google Sheets - Review customer feedback in a shared spreadsheet.
• Airtable - Build searchable product and sentiment records.
• Make or Zapier - Send new datasets to downstream business tools.
• Webhooks - Trigger processing after a run finishes.
• Apify API - Read datasets programmatically or connect scheduled collection to your application.

Apify datasets can be exported as JSON, CSV, Excel, XML, and other supported formats. JSON is suitable for data pipelines, CSV is convenient for spreadsheet analysis, and Excel is useful for business reporting.

Frequently Asked Questions

Can I run the Actor with only a product ID?

Yes. Set productId to the Target TCIN and leave productUrl empty. The Actor creates the product page reference from the TCIN for the run.

Can I collect all available reviews?

Set results_wanted higher than the expected review count. The Actor stops when it reaches that limit or when Target reports that there are no more review pages.

Can I collect reviews from multiple products in one run?

No. Each run is designed for one Target product. Start separate runs for multiple TCINs, then combine the resulting datasets in your workflow.

Can I filter reviews by star rating?

No. This version collects available reviews in the source sorting order. Use the rating field to filter the dataset after collection.

Are review photos and videos included?

Yes. When a review includes media and Target makes the links available, they are saved in photos and videos.

Why are some fields missing?

Fields are omitted when the source review does not publish a value. This is normal for optional content such as media, author signals, secondary ratings, and merchant responses.

Can I schedule repeat review collections?

Yes. Create an Apify schedule to run the Actor hourly, daily, weekly, or at a custom interval, then compare datasets to monitor changes.

Is collecting Target review data legal?

Public web data can be subject to website terms, privacy rules, and other laws. You are responsible for using the data lawfully, respecting Target's terms and access controls, and collecting only what you have a legitimate reason to use.

Related Actors

• Target Product Scraper - Collect Target product listings, prices, ratings, availability, images, and product URLs for catalog and price research.
• Tokopedia Reviews Scraper ⭐ - Collect product reviews and ratings from Tokopedia for ecommerce comparison and customer feedback analysis.
• Shopify Product Scraper - Collect product catalogs, prices, variants, images, and availability from Shopify-powered stores.

Support

For issues, feature requests, or field questions, use the Target Reviews Scraper Issues tab on Apify.

Legal Notice

This Actor is intended for legitimate collection and analysis of publicly available product review data. You are responsible for complying with Target's website terms, applicable laws, privacy requirements, and any restrictions on storing, sharing, or using review content.