# Target Reviews & Ratings Scraper (`blackfalcondata/target-reviews-scraper`) Actor

Scrape Target.com reviews and ratings by keyword or product URL, and get a rating-distribution summary per product. Search "laptops" and every matching product returns its reviews plus star split, sentiment trend and best- and worst-rated attributes.

- **URL**: https://apify.com/blackfalcondata/target-reviews-scraper.md
- **Developed by:** [Black Falcon Data](https://apify.com/blackfalcondata) (community)
- **Categories:** E-commerce, Lead generation, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

### What does Target Reviews & Ratings Scraper do?

Target Reviews & Ratings Scraper extracts structured listing data from [target.com](https://target.com) — including full descriptions and seller ratings. It supports keyword search and controllable result limits, so you can run the same query consistently over time. The actor also offers detail enrichment (full descriptions) where the source provides them.

**New to Apify?** [Sign up free](https://console.apify.com/sign-up?fpr=1h3gvi) and use the included $5 monthly platform credit to test this actor.

### Key features

- **🔔 Notifications** — Telegram, Slack, Discord, WhatsApp Cloud API, and generic webhook out of the box. Pair with incremental for daily new-listing alerts without pipeline glue.
- **📋 Detail enrichment** — toggle two-stage scraping: first collect listings, then enrich each with full description + detail-page-only fields. Off by default to keep runs fast; flip on when you need the deep payload.
- **📧 Email + phone extraction** — best-effort regex extraction of contact emails and phone numbers from descriptions — emitted as `extractedEmails[]` and `extractedPhones[]` on every record.
- **🔗 URL + social-profile extraction** — every record carries `extractedUrls[]` plus a structured `socialProfiles { linkedin, twitter, instagram, facebook, youtube, tiktok, github, xing }` parsed from the description.
- **📦 Compact mode** — AI-agent and MCP-friendly payloads with core fields only.
- **✂️ Description truncation** — cap description length with `descriptionMaxLength` to control LLM prompt cost and dataset size — set 0 for full descriptions, or any char-limit to trim.
- **📌 Change classification** — each record carries a `changeType` of NEW / UPDATED / UNCHANGED / REAPPEARED / EXPIRED. Default emits NEW + UPDATED + REAPPEARED; opt into the others with `emitUnchanged` / `emitExpired`.
- **🔌 MCP connectors** — export your results into Notion via Apify's MCP connectors — a clean run-summary page, no glue code. Opt-in via the App connector field; deterministic field-mapping, no AI. Built on Apify's connector framework, so more destinations open up as their catalog grows.
- **📝 Description format selection** — pick a single description representation — `text`, `html`, or `markdown` — and the unused variants are dropped from each record. Halves payload size when your pipeline only consumes one format.
- **♻️ Incremental mode** — recurring runs emit and charge only for listings that are new or whose tracked content changed. First run builds the baseline; subsequent runs emit only NEW / UPDATED / REAPPEARED records (UNCHANGED + EXPIRED opt-in). Saves 80–95% on daily monitoring.
- **🧹 Empty-field stripping** — drop null, empty-string, and empty-array fields from each record before push. Smaller payloads for AI agents and dashboards that already handle missing fields gracefully.

### What data can you extract from target.com?

Each result includes Core listing fields (`tcin`, `product_id`, `product_url`, `portalUrl`, `product_title`, `product_brand`, `product_image_url`, and `product_category`, and more) and detail fields when enrichment is enabled (`descriptionText`, `descriptionHtml`, `descriptionMarkdown`, and `detailFetched`). In standard mode, all fields are always present — unavailable data points are returned as `null`, never omitted. In compact mode, only core fields are returned.

Enable detail enrichment in the input to get richer fields such as full descriptions where the source provides them.

### Input

The main inputs are a search keyword and a result limit. Additional filters and options are available in the input schema.

Key parameters:

- **`query`** — Find products by keyword (e.g. "laptops") and read their reviews. Use 🛒 Products instead when you already know the exact products. A product URL or TCIN pasted here also works.
- **`maxProducts`** — How many products each search term resolves to. Every product costs its own review requests, so this is the main lever on run size. Ignored when you list products directly. (default: `10`)
- **`products`** — Target.com product URLs or bare TCINs, when you know exactly which products you want. Leave empty to search by keyword instead.
- **`maxResults`** — Maximum REVIEW records across all products (0 = as many as Target serves). Target paginates at most 2,550 reviews per product. Product summary records, when enabled, are additional and not counted against this. (default: `100`)
- **`onlyVerified`** — Only reviews Target marks as a verified purchase. (default: `false`)
- **`onlyWithPhotos`** — Only reviews that include customer photos. (default: `false`)
- **`minRating`** — Drop reviews below this rating (1–5). Leave empty for all ratings. Ratings-only records (products with stars but no written review) are always kept.
- **`sortBy`** — Order of the delivered reviews. Target ignores sort requests, so this is applied to the reviews this run collected: with a Max Reviews cap the run reads the first N in Target's own order and sorts those. To rank across every review of a product, set Max Reviews to 0. (default: `"source"`)
- **`includeDetails`** — Add the product title, brand, image and category to every review. Costs one extra request per product, not per review. (default: `true`)
- **`includeProductSummary`** — Add one analysis record per product: the star distribution as percentages, positive/negative split, verified and photo shares, review counts per year, a 12-month rating trend, the best- and worst-rated attributes, and the most helpful review. Computed from the reviews the run already fetched — no extra requests. Adds one record per product to the results. (default: `true`)
- **`descriptionMaxLength`** — Truncate the review body to N characters. 0 = no truncation. (default: `0`)
- **`compact`** — Core fields only (for AI-agent/MCP workflows). (default: `false`)
- ...and 19 more parameters

### Input examples

**Basic search** — Keyword-driven search with a result cap.

→ Full payload per result — all standard fields populated where the source provides them.

```json
{
  "query": "laptops",
  "maxResults": 50
}
```

**Incremental tracking** — Only emit listings that changed since the previous run with this `stateKey`.

→ First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set `emitUnchanged: true` to include unchanged records as well.

```json
{
  "query": "laptops",
  "maxResults": 200,
  "incrementalMode": true,
  "stateKey": "laptops-tracker"
}
```

**Compact output for AI agents** — Return only core fields for AI-agent and MCP workflows.

→ Small payload with the most important fields — ideal for piping into LLMs without token overhead.

```json
{
  "query": "laptops",
  "maxResults": 50,
  "compact": true
}
```

### Output

Each run produces a dataset of structured listing records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

### Example listing record

```json
{
  "tcin": "91122045",
  "product_id": "91122045",
  "product_url": "https://www.target.com/p/apple-macbook-neo-a18-pro-2026-laptop/-/A-95288385",
  "portalUrl": "https://www.target.com/p/apple-macbook-neo-a18-pro-2026-laptop/-/A-95288385",
  "product_title": "Apple MacBook Neo (A18 Pro, 2026) Laptop",
  "product_brand": "Apple",
  "product_image_url": "https://target.scene7.com/is/image/Target/GUEST_b9b8e7c7-e6c1-4d99-b5bc-fb167801174a",
  "product_category": "Traditional Laptops",
  "position": 1,
  "page": 1,
  "total_reviews_available": 114,
  "total_pages_available": 3,
  "review_id": "fecc22e2-72cf-41cb-a48d-1e50c4132eae",
  "external_review_id": "f6ce49c0-1e1f-5422-b7f4-1f5db0e8778e",
  "channel": "TARGET",
  "rating": 5,
  "rating_range": 5,
  "title": "Neo",
  "text": "So flexible for all my usage reasons . I dod noticed har dents on box though.",
  "is_recommended": true,
  "is_verified": true,
  "is_ratings_only": false,
  "is_syndicated": false,
  "is_incentivized": false,
  "status": "APPROVED",
  "source_client": "targetcom",
  "badges": {
    "verifiedPurchaser": {
      "Id": "verifiedPurchaser",
      "ContentType": "REVIEW",
      "BadgeType": "Custom"
    }
  },
  "badges_order": [
    "verifiedPurchaser"
  ],
  "client_response_count": 0,
  "secondary_ratings": [
    {
      "id": "Display",
      "label": "display",
      "value": 5,
      "range": 5
    },
    {
      "id": "Ease of use",
      "label": "ease of use",
      "value": 5,
      "range": 5
    },
    {
      "id": "Features",
      "label": "features",
      "value": 5,
      "range": 5
    },
    {
      "id": "Speed",
      "label": "speed",
      "value": 5,
      "range": 5
    },
    {
      "id": "Value",
      "label": "value",
      "value": 5,
      "range": 5
    }
  ],
  "secondary_ratings_order": [
    "Display",
    "Ease of use",
    "Features",
    "Speed",
    "Value"
  ],
  "author_external_id": "7987353824",
  "feedback_helpful": 0,
  "feedback_unhelpful": 0,
  "feedback_inappropriate": 0,
  "submitted_at": "2026-08-04T19:39:59.000+00:00",
  "modified_at": "2026-08-04T20:18:03.000+00:00",
  "statistics_average_rating": 3.99,
  "statistics_rating_count": 265,
  "statistics_review_count": 114,
  "statistics_rating_distribution": {
    "1": 55,
    "2": 7,
    "3": 10,
    "4": 8,
    "5": 185
  },
  "statistics_positive_percentage": 76,
  "statistics_recommended_count": 60,
  "statistics_not_recommended_count": 16,
  "statistics_recommended_percentage": 78,
  "statistics_reviews_with_images_count": 9,
  "statistics_reviews_with_videos_count": 0,
  "statistics_question_count": 90,
  "statistics_secondary_averages": [
    {
      "id": "display",
      "label": "display",
      "value": 4.42,
      "range": 5
    },
    {
      "id": "ease of use",
      "label": "ease of use",
      "value": 4.29,
      "range": 5
    },
    {
      "id": "features",
      "label": "features",
      "value": 4.36,
      "range": 5
    },
    {
      "id": "speed",
      "label": "speed",
      "value": 4.37,
      "range": 5
    },
    {
      "id": "value",
      "label": "value",
      "value": 4.3,
      "range": 5
    }
  ],
  "descriptionText": "So flexible for all my usage reasons . I dod noticed har dents on box though.",
  "descriptionHtml": "<p>So flexible for all my usage reasons . I dod noticed har dents on box though.</p>",
  "descriptionMarkdown": "So flexible for all my usage reasons . I dod noticed har dents on box though.",
  "scraped_at": "2026-08-05T12:56:02.936Z",
  "listingId": "7b3f5d991cd186934ea629688679024a03f20d8684f7cb1a1d1e1514e59f8fc6",
  "searchQuery": "91122045",
  "contentQuality": "full",
  "detailFetched": true,
  "scrapedAt": "2026-08-05T12:56:02.936Z",
  "source": "target.com",
  "contentHash": "83eada92c8ce146b75f5cec535fecd590b6b671a772ef8ba928e5f9e95f918fd"
}
```

### Incremental fields

When incremental mode is on, each record also carries:

- `changeType` — one of `NEW`, `UPDATED`, `UNCHANGED`, `REAPPEARED`, `EXPIRED`. Default output covers `NEW` / `UPDATED` / `REAPPEARED`; set `emitUnchanged: true` or `emitExpired: true` to opt into the others.

### How to scrape target.com

1. Go to [Target Reviews & Ratings Scraper](https://apify.com/blackfalcondata/target-reviews-scraper?fpr=1h3gvi) in Apify Console.
2. Enter a search keyword.
3. Set `maxResults` to control how many results you need.
4. Enable `includeDetails` if you need full descriptions.
5. Click **Start** and wait for the run to finish.
6. Export the dataset as JSON, CSV, or Excel.

### Use cases

- Extract listing data from target.com for market research and competitive analysis.
- Monitor new and changed listings on scheduled runs without processing the full dataset every time.
- Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
- Export clean, structured data to dashboards, spreadsheets, or data warehouses.
- Benchmark seller / dealer reputation using rating fields.

### How much does it cost to scrape target.com?

Target Reviews & Ratings Scraper uses [pay-per-event](https://docs.apify.com/platform/actors/paid-actors/pay-per-event) pricing. You pay a small fee when the run starts and then for each result that is actually produced.

- **Run start:** $0.005 per run
- **Per result:** $0.0005 per listing record

Example costs:

- 10 results: **$0.01**
- 25 results: **$0.018**
- 100 results: **$0.055**
- 200 results: **$0.11**
- 500 results: **$0.26**

#### Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.

Example setup: 250 listings per run, daily polling (30 runs/month). Costs scale linearly with the number of listings.

| Churn rate | Full re-scrape run cost | Incremental run cost | Savings vs full re-scrape | Monthly cost after baseline |
|---|---:|---:|---:|---:|
| 5% — stable niche query | $0.13 | $0.01 | $0.12 (91%) | $0.34 |
| 15% — moderate broad query | $0.13 | $0.02 | $0.11 (82%) | $0.71 |
| 30% — high-volume aggregator | $0.13 | $0.04 | $0.09 (67%) | $1.27 |

Full re-scrape monthly cost at the same cadence: $3.90. First month with incremental costs $0.46 / $0.82 / $1.36 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

### FAQ

#### How many results can I get from target.com?

The number of results depends on the search query and available listings on target.com. Use the `maxResults` parameter to control how many results are returned per run.

#### Does Target Reviews & Ratings Scraper support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.

#### Can I integrate Target Reviews & Ratings Scraper with other apps?

Yes. Target Reviews & Ratings Scraper works with Apify's [integrations](https://apify.com/integrations?fpr=1h3gvi) to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

#### Can I use Target Reviews & Ratings Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the [Apify API](https://docs.apify.com/api/v2). Client libraries are available for JavaScript, Python, and other languages.

#### Can I use Target Reviews & Ratings Scraper through an MCP Server?

Yes. Apify provides an [MCP Server](https://apify.com/apify/actors-mcp-server?fpr=1h3gvi) that lets AI assistants and agents call this actor directly. Use compact mode, `descriptionMaxLength`, a single `descriptionFormat`, and `excludeEmptyFields` to keep payloads manageable for LLM context windows.

#### Is it legal to scrape target.com?

This actor extracts publicly available data from target.com. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

#### Your feedback

If you have questions, need a feature, or found a bug, please [open an issue](https://apify.com/blackfalcondata/target-reviews-scraper/issues?fpr=1h3gvi) on the actor's page in Apify Console. Your feedback helps us improve.

### You might also like

- [Agoda Reviews — Hotel Guest Reviews](https://apify.com/blackfalcondata/agoda-reviews-scraper?fpr=1h3gvi) — Scrape guest reviews for any Agoda hotel — star ratings · full review text in the original language.
- [Airbnb Reviews — vacation rental review data](https://apify.com/blackfalcondata/airbnb-reviews-scraper?fpr=1h3gvi) — Scrape airbnb.com reviews for any listing URL or a whole city. Get flat rows covering guest.
- [Booking \[Just 💰$1\] — Reviews by Hotel or Destination](https://apify.com/blackfalcondata/booking-reviews-scraper?fpr=1h3gvi) — 💰 $1 per 1,000 reviews. Scrape Booking.com guest reviews by hotel URL or destination. Each record.
- [Clutch — B2B Agency Ratings & Reviews](https://apify.com/blackfalcondata/clutch-scraper?fpr=1h3gvi) — Scrape clutch.co — B2B service providers with ratings · review counts · service lines · hourly.
- [Jameda \[Just 💰$2\] — German doctor reviews](https://apify.com/blackfalcondata/jameda-scraper?fpr=1h3gvi) — 💰 $2 per 1,000 reviews. Scrape jameda.de — physician name & specialty · clinic address.
- [Kununu \[Just 💰$1\] — Employer Reviews & Ratings (DACH)](https://apify.com/blackfalcondata/kununu-scraper?fpr=1h3gvi) — 💰 $1 per 1,000 records. Scrape kununu.com across DACH — company ratings, employee reviews & salary.
- [ReclameAqui — Brazil Complaints & Company Reputation](https://apify.com/blackfalcondata/reclameaqui-scraper?fpr=1h3gvi) — Scrape ReclameAqui Brazil — full consumer complaint threads with every company reply, not just a.
- [Trustpilot $0.25💰 Reviews/Ratings/Replies/Bypass 200 Limit](https://apify.com/blackfalcondata/trustpilot-reviews-scraper?fpr=1h3gvi) — 💰 $0.25 per 1,000 reviews. Scrape full Trustpilot history for any company — bypass the 200-review.

### Getting started with Apify

New to Apify? [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=1h3gvi) — no credit card required.

1. Sign up — $5 platform credit included
2. Open this actor and configure your input
3. Click **Start** — export results as JSON, CSV, or Excel

Need more later? [See Apify pricing](https://apify.com/pricing?fpr=1h3gvi).

### Disclaimer

This actor accesses only publicly available data on target.com. You are responsible for how you use the extracted data — in particular any personal information such as names, phone numbers, or email addresses — and for complying with Target Reviews & Ratings's terms of use, applicable data-protection law (including the GDPR where it applies), and the anti-spam rules of your jurisdiction.

This actor is not affiliated with, endorsed by, or connected to Target Reviews & Ratings.

### Search keywords

target scraper, target api, apify target, target data extraction, target reviews & ratings scraper, target reviews & ratings api, apify target reviews & ratings, target reviews & ratings data extraction, target.com scraper, target.com data, target.com api.

# Actor input Schema

## `query` (type: `string`):

Find products by keyword (e.g. "laptops") and read their reviews. Use 🛒 Products instead when you already know the exact products. A product URL or TCIN pasted here also works.

## `maxProducts` (type: `integer`):

How many products each search term resolves to. Every product costs its own review requests, so this is the main lever on run size. Ignored when you list products directly.

## `products` (type: `array`):

Target.com product URLs or bare TCINs, when you know exactly which products you want. Leave empty to search by keyword instead.

## `maxResults` (type: `integer`):

Maximum REVIEW records across all products (0 = as many as Target serves). Target paginates at most 2,550 reviews per product. Product summary records, when enabled, are additional and not counted against this.

## `onlyVerified` (type: `boolean`):

Only reviews Target marks as a verified purchase.

## `onlyWithPhotos` (type: `boolean`):

Only reviews that include customer photos.

## `minRating` (type: `integer`):

Drop reviews below this rating (1–5). Leave empty for all ratings. Ratings-only records (products with stars but no written review) are always kept.

## `sortBy` (type: `string`):

Order of the delivered reviews. Target ignores sort requests, so this is applied to the reviews this run collected: with a Max Reviews cap the run reads the first N in Target's own order and sorts those. To rank across every review of a product, set Max Reviews to 0.

## `includeDetails` (type: `boolean`):

Add the product title, brand, image and category to every review. Costs one extra request per product, not per review.

## `includeProductSummary` (type: `boolean`):

Add one analysis record per product: the star distribution as percentages, positive/negative split, verified and photo shares, review counts per year, a 12-month rating trend, the best- and worst-rated attributes, and the most helpful review. Computed from the reviews the run already fetched — no extra requests. Adds one record per product to the results.

## `descriptionMaxLength` (type: `integer`):

Truncate the review body to N characters. 0 = no truncation.

## `compact` (type: `boolean`):

Core fields only (for AI-agent/MCP workflows).

## `descriptionFormat` (type: `string`):

Which representations of the review body to emit. `all` keeps text + descriptionText + descriptionHtml + descriptionMarkdown. `text` / `html` / `markdown` keep only one variant.

## `excludeEmptyFields` (type: `boolean`):

Drop null / empty-string / empty-array fields from each output record. Off by default to preserve dataset schema compatibility; turn on to slim output for LLM / agent consumption.

## `incrementalMode` (type: `boolean`):

Compare against the previous run and emit only new or changed reviews. Leave State Key empty and each product set is tracked separately.

## `stateKey` (type: `string`):

Optional. Stable identifier for the tracked product set. Leave empty to auto-generate from the product list.

## `emitUnchanged` (type: `boolean`):

Also emit reviews that have not changed since the last run (incrementalMode only).

## `emitExpired` (type: `boolean`):

Also emit reviews that have disappeared since the last run — deleted or moderated away (incrementalMode only). Suppressed automatically when a filter or Target's own pagination window means the run did not see every review of a product.

## `telegramToken` (type: `string`):

Telegram bot token (from @BotFather). Required for Telegram notifications.

## `telegramChatId` (type: `string`):

Telegram chat or channel ID (e.g. "-100123456789"). Required when telegramToken is set.

## `discordWebhookUrl` (type: `string`):

Discord incoming webhook URL. Server Settings → Integrations → Webhooks → New Webhook.

## `slackWebhookUrl` (type: `string`):

Slack incoming webhook URL. api.slack.com/messaging/webhooks.

## `notificationLimit` (type: `integer`):

Maximum number of reviews included in each notification message (1–20).

## `notifyOnlyChanges` (type: `boolean`):

When Incremental Mode is on, only send notifications for NEW and UPDATED reviews. Has no effect outside incremental mode.

## `whatsappAccessToken` (type: `string`):

WhatsApp Cloud API permanent access token (System User token from Meta Business). Recipient must have messaged the business number within the last 24h.

## `whatsappPhoneNumberId` (type: `string`):

Your WhatsApp Business phone-number ID (numeric, from Meta dashboard). Required when whatsappAccessToken is set.

## `whatsappTo` (type: `string`):

Recipient phone in E.164 format without + (e.g. "436641234567").

## `webhookUrl` (type: `string`):

Receives a JSON POST with {metadata, items} after each run. Universal escape hatch for n8n / Make / Zapier / custom backends.

## `webhookHeaders` (type: `object`):

Optional JSON object of custom headers (e.g. {"Authorization":"Bearer ..."}).

## `appConnector` (type: `string`):

Optional. Pick a connected app under Settings → API & Integrations to receive your results. Best-effort across MCP connectors as Apify expands its catalog.

## `mcpIssueTeam` (type: `string`):

Only when the connected app is an issue tracker: the team (name or ID) the summary issue is created under, if that app requires one.

## Actor input object example

```json
{
  "query": "laptops",
  "maxProducts": 5,
  "maxResults": 50,
  "onlyVerified": false,
  "onlyWithPhotos": false,
  "sortBy": "source",
  "includeDetails": true,
  "includeProductSummary": true,
  "descriptionMaxLength": 0,
  "compact": false,
  "descriptionFormat": "all",
  "excludeEmptyFields": false,
  "incrementalMode": false,
  "emitUnchanged": false,
  "emitExpired": false,
  "notificationLimit": 5,
  "notifyOnlyChanges": false
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "query": "laptops",
    "maxProducts": 5,
    "maxResults": 50
};

// Run the Actor and wait for it to finish
const run = await client.actor("blackfalcondata/target-reviews-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "query": "laptops",
    "maxProducts": 5,
    "maxResults": 50,
}

# Run the Actor and wait for it to finish
run = client.actor("blackfalcondata/target-reviews-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "query": "laptops",
  "maxProducts": 5,
  "maxResults": 50
}' |
apify call blackfalcondata/target-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,blackfalcondata/target-reviews-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/AzsAULUC63IoXR3Zc/builds/3wYVEDChEEYQ21Nh4/openapi.json