Target Reviews Scraper

Export public Target product reviews from product URLs or TCIN item IDs, including star ratings, review text, authors, recommendation signals, helpful votes, dates, and product summary fields.

Use this Actor when you need a repeatable CSV, JSON, Excel, API, or AI-agent export of Target customer feedback for ecommerce research, product quality analysis, brand monitoring, or review intelligence.

What Does Target Reviews Scraper Do?

Target Reviews Scraper turns public Target review pages into structured review rows.

• Scrape by product URL: paste one or more Target product URLs.
• Scrape by TCIN: use Target item IDs directly when you already have them.
• Collect review details: export rating, review title, review text, author nickname, date, recommendation status, helpful votes, and verified-purchaser signals.
• Include product context: repeat product URL, TCIN, title, brand, average rating, review count, and recommendation percentage on each row.
• Sort reviews: request most recent, highest rating, or lowest rating reviews.

Ready-to-run examples

• Scrape Recent Target AirPods Reviews
• Scrape Target Reviews By TCIN
• Monitor Target Product Feedback
• Find Lowest Rated Target Product Reviews
• Find Highest Rated Target Product Reviews
• Build AI Dataset From Target Reviews

Input Example

{
  "startUrls": [
    {
      "url": "https://www.target.com/p/apple-airpods-pro-2nd-generation-with-magsafe-case-usb-c/-/A-85978622"
    }
  ],
  "maxReviews": 25,
  "sortBy": "most_recent"
}

You can also run by TCIN:

{
  "tcins": ["85978622"],
  "maxReviews": 50,
  "sortBy": "lowest_rating"
}

Output Example

{
  "productUrl": "https://www.target.com/p/example/-/A-85978622",
  "tcin": "85978622",
  "productTitle": "Example Product",
  "brand": "Example Brand",
  "averageRating": 4.6,
  "ratingCount": 1240,
  "reviewCount": 1180,
  "recommendedPercentage": 91,
  "reviewId": "abc123",
  "reviewTitle": "Great sound quality",
  "reviewText": "Easy to use and good battery life.",
  "rating": 5,
  "authorNickname": "target_customer",
  "submittedAt": "2026-07-01",
  "isRecommended": true,
  "helpfulVotes": 12,
  "verifiedPurchaser": true,
  "isSyndicated": false,
  "dataSourceName": "Target",
  "sortBy": "most_recent",
  "scrapedAt": "2026-07-07T10:00:00.000Z"
}

Who Is It For?

User	Use case
Ecommerce teams	Monitor product feedback and recurring customer complaints.
Brands	Track ratings, review text, recommendation signals, and verified-purchase feedback.
Market researchers	Compare products, categories, sentiment themes, and rating distributions.
Data teams	Export Target reviews to spreadsheets, BI tools, warehouses, or AI pipelines.
AI agents	Run review exports through Apify API or MCP and summarize customer themes.

Input Settings

Setting	JSON key	What it does
Target product URLs	startUrls	One or more Target product URLs. URLs containing /A-12345678 are supported.
Target TCIN item IDs	tcins	Optional Target item IDs, such as 85978622. Use this when you already have item IDs.
Maximum reviews	maxReviews	Maximum review rows to save across all products.
Review sort order	sortBy	Use most_recent, highest_rating, or lowest_rating.
Proxy configuration	proxyConfiguration	Optional Apify Proxy settings. Leave default unless Target blocks your run.

Output Fields

Field	Description
productUrl, tcin	Target product URL and item ID.
productTitle, brand	Product name and brand when available.
averageRating, ratingCount, reviewCount	Product-level rating summary fields.
recommendedCount, notRecommendedCount, recommendedPercentage	Product-level recommendation signals.
reviewId	Review identifier.
reviewTitle, reviewText	Review headline and body text.
rating	Star rating for the review.
authorNickname	Public reviewer nickname when available.
submittedAt	Review submission date.
isRecommended	Whether the reviewer recommends the product.
helpfulVotes, notHelpfulVotes	Review helpfulness counts.
verifiedPurchaser	Whether Target marks the reviewer as a verified purchaser.
isSyndicated, dataSourceName	Source metadata for syndicated or external review content.
sortBy, scrapedAt	Sort mode used and timestamp when the row was saved.

Pricing

This Actor uses pay-per-event pricing.

Event	Price
Run started	$0.005 per run
Item extracted	BRONZE tier: $0.000024924 per saved review row, about $0.025 per 1,000 rows

The exact item price depends on your Apify plan tier. Runs that save fewer rows still include the one-time run-start event.

Tips For Better Results

• Use TCINs for stable inputs: product URLs are convenient, but TCINs are the cleanest identifier.
• Start with 20-50 reviews: test a product before increasing maxReviews.
• Use low-rating sort for issue discovery: lowest_rating is useful for product quality analysis.
• Use recent sort for monitoring: most_recent is best for recurring scheduled runs.
• Expect nulls: Target may omit author, verified status, brand, helpful votes, or recommendation fields for some reviews.

API Usage

Run the Actor with cURL:

curl "https://api.apify.com/v2/acts/fetch_cat~target-reviews-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"tcins":["85978622"],"maxReviews":25,"sortBy":"most_recent"}'

Run from JavaScript:

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor("fetch_cat/target-reviews-scraper").call({
  tcins: ["85978622"],
  maxReviews: 25,
  sortBy: "most_recent",
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

MCP And AI Agents

This Actor works with the official Apify MCP server. Use the focused MCP URL when you want your AI tool to expose only this Actor:

https://mcp.apify.com?tools=fetch_cat/target-reviews-scraper

Example prompts:

• "Run Target Reviews Scraper for this TCIN and summarize the most common complaints."
• "Collect the lowest-rated reviews for these Target products and group quality issues."
• "Export recent Target reviews and identify whether verified purchasers mention shipping or sizing."

Limits And Notes

• The Actor extracts public Target review data; it does not access private customer information.
• Product summary fields are repeated on review rows for easier filtering and grouping.
• Target can return fewer reviews than requested if fewer public reviews are available for the selected sort.
• If Target blocks requests, try Apify Proxy settings and keep runs modest.

FAQ

Can I scrape multiple Target products in one run?

Yes. Add multiple product URLs in startUrls or multiple item IDs in tcins.

Can I export Target reviews to CSV or Excel?

Yes. Export the Apify dataset as CSV, Excel, JSON, XML, or RSS after the run.

Can I collect only one-star reviews?

The Actor supports lowest_rating sorting. You can export low-rated reviews first, then filter the dataset by rating.

Does the Actor return product summary rows?

No separate product summary rows are created. Product summary fields are included on each review row.

Is this a Target reviews API alternative?

It can be used as an API-style export for public Target reviews through Apify API, datasets, schedules, webhooks, and MCP.

Related Actors

• ProductReview.com.au Scraper
• Steam Reviews Scraper
• Google Shopping Results Scraper
• Shopify Products Scraper
• Poshmark Sold Listings Scraper

Support

If a run fails or output looks wrong, report the issue from the Actor page and include the Apify run ID or run URL, your input JSON, expected output, actual output, and one reproducible public Target product URL or TCIN.

Changelog

0.1

• Initial public release.