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

• Build Ai Dataset From Target Reviews
• Monitor Target Product Feedback
• Scrape Target Reviews By Tcin
• Find Lowest Rated Target Product Reviews
• Find Highest Rated Target Product Reviews
• Scrape Recent Target Airpods Reviews

View all ready-to-run examples

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	Type / default	Description
Target product URLs	startUrls	array, default [{"url":"https://www.target.com/p/apple-airpods-pro-2nd-generation-with-magsafe-case-usb-c/-/A-85978622"}]	Paste one or more Target product URLs. URLs containing /A-12345678 are supported.
Target TCIN item IDs	tcins	array, default []	Optional Target item IDs (TCINs), for example 85978622. Use this when you already have item IDs instead of URLs.
Maximum reviews	maxReviews	integer, default 20	Maximum number of review rows to save across all products.
Review sort order	sortBy	string, default "most_recent"	Order used when requesting Target reviews.
Proxy configuration	proxyConfiguration	object, default {"useApifyProxy":true,"apifyProxyGroups":["RESIDENTIAL"]}	Uses Apify residential proxy by default because Target commonly rate-limits direct datacenter requests.

Output fields

JSON key	Label	Type	Description
productUrl	ProductUrl	string	Output field for producturl.
tcin	Tcin	string	Output field for tcin.
productTitle	ProductTitle	string / null	Output field for producttitle.
brand	Brand	string / null	Output field for brand.
averageRating	AverageRating	number / null	Output field for averagerating.
ratingCount	RatingCount	integer / null	Output field for ratingcount.
reviewCount	ReviewCount	integer / null	Output field for reviewcount.
recommendedCount	RecommendedCount	integer / null	Output field for recommendedcount.
notRecommendedCount	NotRecommendedCount	integer / null	Output field for notrecommendedcount.
recommendedPercentage	RecommendedPercentage	number / null	Output field for recommendedpercentage.
reviewId	ReviewId	string	Output field for reviewid.
reviewTitle	ReviewTitle	string / null	Output field for reviewtitle.
reviewText	ReviewText	string / null	Output field for reviewtext.
rating	Rating	number / null	Output field for rating.
authorNickname	AuthorNickname	string / null	Output field for authornickname.
submittedAt	SubmittedAt	string / null	Output field for submittedat.
isRecommended	IsRecommended	boolean / null	Output field for isrecommended.
helpfulVotes	HelpfulVotes	integer / null	Output field for helpfulvotes.
notHelpfulVotes	NotHelpfulVotes	integer / null	Output field for nothelpfulvotes.
verifiedPurchaser	VerifiedPurchaser	boolean / null	Output field for verifiedpurchaser.
isSyndicated	IsSyndicated	boolean / null	Output field for issyndicated.
dataSourceName	DataSourceName	string / null	Output field for datasourcename.
sortBy	SortBy	string	Output field for sortby.
scrapedAt	ScrapedAt	string	Output field for scrapedat.

Pricing

This Actor uses Apify pay-per-event pricing. The prices below come from the current Actor pricing configuration. Apify public plans map to Store discount tiers, so the table shows both the user-facing plan context and the pricing tier name. The final price shown in Apify depends on the user account plan and any custom agreement.

Event	What is charged	Free	Bronze	Silver	Gold	Platinum	Diamond
start	One-time charge when the scraper starts.	$0.005	$0.005	$0.005	$0.005	$0.005	$0.005
item	Charged per Target review extracted.	$0.000029	$0.000025	$0.000019	$0.000015	$0.000010	$0.000007

Apify may also charge platform usage for compute, storage, proxies, or data transfer outside this Actor pricing. Check the Actor run and the Apify Pricing tab for the exact cost shown to your account.

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 Target Reviews Scraper from your own code with the Apify API.

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const input = {
  "startUrls": [
    {
      "url": "https://www.target.com/p/apple-airpods-pro-2nd-generation-with-magsafe-case-usb-c/-/A-85978622"
    }
  ],
  "tcins": [],
  "maxReviews": 20,
  "sortBy": "most_recent",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
};

const run = await client.actor('fetch_cat/target-reviews-scraper').call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient
import os

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("fetch_cat/target-reviews-scraper").call(run_input={
  "startUrls": [
    {
      "url": "https://www.target.com/p/apple-airpods-pro-2nd-generation-with-magsafe-case-usb-c/-/A-85978622"
    }
  ],
  "tcins": [],
  "maxReviews": 20,
  "sortBy": "most_recent",
  "proxyConfiguration": {
    "useApifyProxy": True,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)

cURL

curl -X POST "https://api.apify.com/v2/acts/fetch_cat~target-reviews-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrls":[{"url":"https://www.target.com/p/apple-airpods-pro-2nd-generation-with-magsafe-case-usb-c/-/A-85978622"}],"tcins":[],"maxReviews":20,"sortBy":"most_recent","proxyConfiguration":{"useApifyProxy":true,"apifyProxyGroups":["RESIDENTIAL"]}}'

Use with AI agents via MCP

Target Reviews Scraper can be used by AI assistants through the hosted Apify MCP server.

Claude Code setup

$claude mcp add --transport http apify "https://mcp.apify.com?tools=fetch_cat/target-reviews-scraper"

Claude Desktop, Cursor, or VS Code JSON config

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=fetch_cat/target-reviews-scraper"
    }
  }
}

Example prompts

• "Run Target Reviews Scraper with this input JSON and summarize the dataset."
• "Export the latest Target Reviews Scraper results to a table I can review."
• "Schedule this Actor for monitoring and tell me what changed between runs."

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.
• The default residential proxy setting is recommended for reliable Target access; keep runs modest if Target slows responses.

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

• AliExpress Products Scraper
• Apple App Store Apps Scraper
• Apple App Store Reviews Scraper
• Craigslist Classifieds Scraper
• Google Play Apps Scraper

Support

Report bugs, wrong output, blocked runs, or missing fields from the Actor page. Include the Apify run ID or run URL, your input JSON, what you expected, what the Actor returned, and one reproducible public URL so the issue can be tested quickly.

Privacy and data handling

This Actor runs with Apify limited permissions and only processes data needed for the documented run. It uses review lookup inputs and public review results to produce the output dataset and sends requests to public Target Reviews pages/endpoints; results are stored in Apify run storage for your account. FetchCat does not use your inputs or outputs for advertising, does not use them for model training, and does not retain them outside the Apify run except for transient support debugging when you explicitly share run details. You are responsible for using the Actor lawfully, respecting the target site's terms, and avoiding unnecessary personal or sensitive data in inputs.