Fast Apple App Store Reviews Scraper API: Extract iOS App Reviews, Ratings & User Feedback at Scale

The App Store Reviews Scraper is an Apify Actor that extracts user reviews, star ratings, review titles, reviewer profiles, and app version data from any Apple App Store listing. This app store review scraper api collects 11 structured fields per review at speeds up to 200 reviews per second—across any country or all countries simultaneously.

$0.10 per 1,000 reviews. Extract iOS app reviews from the Apple App Store at scale with no API key, no developer account, and no complex authentication. Target specific apps by ID or URL, filter by country, and retrieve reviews with date filtering using the until parameter for continuous monitoring.

Use this apple app store review extractor for app sentiment analysis, user feedback monitoring, competitive benchmarking, or NLP training data. Download App Store reviews to JSON, CSV, or Excel for product analytics, feature prioritization, and app store optimization (ASO).

Note: Due to Apple's API limitations, you can retrieve a maximum of 500 reviews per country. Set country to all to collect reviews across every App Store locale.

Pricing: $0.10 per 1,000 reviews | No API key required | Up to 200 reviews/second

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Table of Contents

1. What Does the App Store Reviews Scraper Do?
2. Features and Capabilities
3. Pricing
4. Input Parameters
5. Output Format and Data Fields
6. Custom Map Function
7. AI Agent Integration via MCP
8. Related Tools
9. Demo Mode and Free Testing
10. Automated Scheduling and Monitoring
11. Quick Start Guide
12. Use Cases and Industries
13. Troubleshooting
14. Frequently Asked Questions
15. Contact

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What Does the App Store Reviews Scraper Do?

App Store review extraction is the automated process of collecting user reviews, ratings, feedback text, and metadata from iOS app listings on the Apple App Store. The App Store hosts over 1.8 million apps with millions of user reviews—making it a critical source of structured user feedback for iOS and macOS applications.

The Agents App Store Reviews Scraper is a high-performance data extraction tool built to scrape App Store reviews from any app listing at scale. Extract structured review data at up to 200 reviews per second—without needing an Apple Developer account, App Store Connect access, or complex authentication flows.

This tool delivers comprehensive review data at $0.10 per 1,000 reviews, including review titles, user profiles, app version data, and country-specific feedback that's essential for global app intelligence.

What You Get From Every Review

When you extract App Store reviews, you receive:

Review Content and Rating

• Full review text and review title
• Star rating (1–5)
• Publication date (ISO 8601)
• Direct review URL on iTunes

App and Version Context

• App ID (numeric App Store identifier)
• App version at time of review
• Country code of the App Store locale

Reviewer Profile

• Reviewer username
• Reviewer profile URL on iTunes

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Features and Capabilities

Input Flexibility

Input Type	Example	Best For
App ID	389801252	Targeting specific apps by numeric ID
Direct URL	https://apps.apple.com/us/app/instagram/id389801252	Scraping from an App Store listing URL

Core Features

• High-Speed Extraction — Up to 200 reviews per second
• Global Coverage — Extract reviews from any country or all countries simultaneously
• Date Filtering — Use until parameter to extract only reviews newer than a specific date
• Review Titles — Capture both title and body text (unique to App Store reviews)
• App Version Tracking — See which version each reviewer was using
• Reviewer Profiles — Username and iTunes profile URL for each reviewer
• Multiple Export Formats — JSON, CSV, Excel direct download
• Custom Transformations — Reshape output with custom JavaScript map functions
• API Integration — RESTful API for Python, Node.js, or any HTTP client
• Scheduled Runs — Automate recurring extraction for continuous monitoring
• Multi-Country Support — Set country to all to fetch reviews from every App Store locale

Apple API Limitation: Maximum 500 reviews per country per app. To maximize coverage, use country: "all" to collect up to 500 reviews from each country.

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Pricing

Simple Per-Review Pricing

No subscriptions, no hidden fees. This app store reviews scraper uses straightforward per-review pricing:

Metric	Price
Per 1,000 reviews	$0.10
Per review	$0.0001

Example: Extracting 500 reviews from 10 countries (5,000 reviews total) costs $0.50. Extracting reviews from all available countries for a popular app costs under $5.00.

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Input Parameters

Field	Type	Description	Default
appIds	array	App IDs extracted from the App Store URL (exclude any trailing "id" part)	[]
country	string	Country code for the App Store locale. Set to all to fetch reviews from each country separately	us
startUrls	array	Direct App Store review URLs—scraping begins immediately from these endpoints	[]
maxItems	number	Maximum number of reviews to output	Infinity
until	string	Returns only reviews newer than this date	null
customMapFunction	string	JavaScript function to transform each review object (transformation only, not filtering)	null

Input Examples

Single App — US Store:

{
    "appIds": ["389801252"],
    "country": "us",
    "maxItems": 500
}

Multiple Apps — Competitive Comparison:

{
    "appIds": ["389801252", "686449807", "835599320"],
    "country": "us",
    "maxItems": 500
}

Global Coverage — All Countries:

{
    "appIds": ["389801252"],
    "country": "all",
    "maxItems": 500
}

Date-Filtered — Recent Reviews Only:

{
    "appIds": ["389801252"],
    "country": "us",
    "until": "2025-01-01",
    "maxItems": 500
}

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Output Format and Data Fields

Each extracted review is a structured JSON object containing 11 fields. Here is a sample:

{
  "id": "12260365349",
  "date": "2025-02-01T22:53:54-07:00",
  "userName": "Fox3782",
  "userUrl": "https://itunes.apple.com/gb/reviews/id566053959",
  "version": "365.0.0",
  "score": 1,
  "title": "Filters",
  "text": "INSTAGRAM WHERE ARE MY CUTE FILTERS?! Bring them back.",
  "url": "https://itunes.apple.com/gb/review?id=389801252&type=Purple%20Software",
  "country": "GB",
  "appId": "389801252"
}

Complete Field Reference

Field	Type	Description
id	string	Unique review identifier
date	string	ISO 8601 review publication date
userName	string	Reviewer's display name
userUrl	string	Reviewer's iTunes profile URL
version	string	App version the reviewer was using
score	number	Star rating (1-5)
title	string	Review title (headline)
text	string	Full review body text
url	string	Direct link to the review on iTunes
country	string	App Store country code
appId	string	Numeric App Store application ID

Data Fields by Use Case

Use Case	Key Fields
Sentiment Analysis	text, title, score, date, country
App Store Optimization (ASO)	score, text, title, version, country
Competitive Benchmarking	appId, score, text, title, date
NLP Training Data	text, title, score (as label)
Release Impact Tracking	version, score, text, date
Global Market Research	country, score, text, date, appId

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Custom Map Function

Transform each review before it's saved to the dataset. The customMapFunction parameter accepts a JavaScript function that reshapes every review object. Use this to extract specific fields, rename properties, or compute derived values.

Important: The custom map function is for transformation only, not filtering. Every review will still be saved.

Example: Flatten for Sentiment Analysis

(review) => ({
    app: review.appId,
    rating: review.score,
    headline: review.title,
    body: review.text,
    date: review.date,
    version: review.version,
    country: review.country
})

Example: Extract for Cross-Platform Comparison

(review) => ({
    platform: "App Store",
    appId: review.appId,
    rating: review.score,
    text: review.text,
    date: review.date,
    country: review.country,
    reviewer: review.userName
})

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AI Agent Integration via MCP

Apify provides a hosted Model Context Protocol (MCP) server at mcp.apify.com that allows AI agents and LLM-based applications to discover and run Apify Actors as tools—including this App Store Reviews Scraper.

What This Means

If you're building AI agents using Claude Desktop, VS Code with MCP support, or any framework that implements the MCP specification, you can give your agent the ability to extract App Store reviews autonomously. The agent can call this scraper as a tool, receive structured JSON results, and use them in downstream analysis.

How to Connect

Add this scraper to your MCP client configuration:

https://mcp.apify.com?tools=agents/appstore-reviews

Or use the CLI for local development:

$npx @apify/actors-mcp-server --tools agents/appstore-reviews

Use Cases for AI Agent Integration

• Automated app monitoring — An AI agent periodically extracts new reviews and summarizes sentiment trends, flagging negative spikes for product teams.
• Cross-platform analysis — Combine App Store reviews with Google Play Reviews in a single agent workflow for unified iOS + Android sentiment reporting.
• Multi-step research pipelines — Extract reviews, run sentiment classification, and generate actionable product recommendations within one agent session.

For full setup instructions, see the Apify MCP documentation.

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Related Tools

Agents Data Intelligence Suite

All tools below are built and maintained by Agents—a team of ex-Big Tech engineers, former ad agency strategists, and data specialists delivering intelligence, precision, and impact at scale.

Tool	What It Extracts	Best For
App Store Reviews Scraper	iOS app reviews, ratings, titles, reviewer profiles	iOS app intelligence (You are here)
Google Play Reviews Scraper	Android app reviews, ratings, developer replies, feature ratings	Android app intelligence
Google Maps Reviews Scraper	Business reviews, ratings, reviewer profiles, location data	Local business intelligence
Google Maps Search Scraper	Business listings, contact, ratings, hours	Lead generation, directories
Google Maps Business Scraper	Full business profiles, attributes, review distribution	Deep profiling, due diligence
Trustpilot Reviews Scraper	Reviews, TrustScores, company replies	SaaS/B2B analysis
Yelp Reviews Scraper	Reviews, ratings, reviewer profiles	Restaurant/hospitality
Yelp Business Scraper	Business profiles, ratings, contact	Business data, prospecting
TripAdvisor Reviews Scraper	Hotel/restaurant reviews, ratings	Hospitality intelligence

App Store Reviews vs. Google Play Reviews

Feature	App Store (This Tool)	Google Play
Platform	iOS / macOS	Android
Review titles	Yes	No (title field often null)
Developer replies	No	Yes (replyText, replyDate)
Feature ratings (criterias)	No	Yes (per-feature quality ratings)
Max reviews per country	500 (Apple limitation)	No hard limit
Speed	Up to 200 reviews/second	High-speed
Multi-country	country: "all"	country parameter

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Demo Mode and Free Testing

You can test this app store reviews scraper on Apify's Free plan with limited results before committing to larger runs. Validate the output format, data quality, and field coverage before scaling.

How to Test:

• Run the scraper with a small maxItems value (e.g., 10-50 reviews)
• Verify the output structure matches your pipeline requirements
• Confirm country filtering works for your target market
• Test the customMapFunction with a sample transformation

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Automated Scheduling and Monitoring

App reviews appear continuously. For product teams and reputation managers, set up automated recurring runs to capture new reviews as they're posted.

Why Schedule Review Extraction?

• Release monitoring — Track user sentiment after each app update by filtering with until
• Continuous feedback loop — Feed fresh reviews into product analytics dashboards
• Competitor tracking — Monitor competitor iOS app reviews weekly for feature gaps
• Rating trend analysis — Detect rating drops before they impact App Store ranking
• Agency reporting — Automated data for client app performance dashboards

How to Set Up Scheduled Runs

1. Open the Actor in Apify Console
2. Configure your input parameters (appIds, country, until)
3. Click Schedule and set frequency (daily, weekly, after each release)
4. Optionally add a webhook to push new data to your pipeline

Webhook Integration

Combine scheduled runs with webhooks to build fully automated review monitoring:

Scheduled Run -> New Reviews Extracted -> Webhook fires -> Your system receives data

Use webhooks to trigger:

• Slack alerts for 1-star reviews mentioning crashes or bugs
• Database updates with new review data
• Dashboard refreshes with latest sentiment metrics
• Jira ticket creation for critical user-reported issues

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Quick Start Guide

For Non-Technical Users (Apify Console)

1. Go to App Store Reviews Scraper on Apify
2. Click Try for free
3. Enter an App ID (e.g., 389801252 for Instagram) in the appIds field
4. Set country and maxItems
5. Click Start and wait for results
6. Export App Store reviews to CSV from the Storage tab

For Developers (Python API)

from apify_client import ApifyClient
client = ApifyClient("YOUR_TOKEN")
run = client.actor("agents/appstore-reviews").call(run_input={
    "appIds": ["389801252"],
    "country": "us",
    "maxItems": 500
})
items = client.dataset(run["defaultDatasetId"]).list_items().items

For Product Teams (Release Monitoring)

{
    "appIds": ["YOUR_APP_ID"],
    "country": "us",
    "until": "2025-03-01",
    "maxItems": 500
}

Schedule after each release. Use the until parameter set to the release date to capture only post-update feedback. Compare sentiment before and after to measure release impact.

For Cross-Platform Analysis (iOS + Android)

Run this scraper for App Store reviews, then run the Google Play Reviews Scraper for the same app on Android. Use matching customMapFunction outputs to normalize fields across platforms:

// Use this customMapFunction on both scrapers for unified output
(review) => ({
    platform: "App Store",
    rating: review.score,
    text: review.text || review.title,
    date: review.date,
    country: review.country,
    appId: review.appId
})

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Use Cases and Industries

iOS App Sentiment Analysis and NLP

Extract hundreds of App Store reviews with full text, titles, and star ratings for training sentiment classifiers, topic modeling, or aspect-based sentiment analysis. App Store reviews uniquely include review titles (headlines) that often summarize the user's core sentiment—providing a natural short-text label for NLP training alongside the full review body.

Key fields: text, title, score, date, version, country

App Store Optimization (ASO)

Analyze review content to identify keywords users associate with your app. Track how ratings change across versions and countries. Discover what features drive positive reviews and what pain points cause negative ones. Review titles are particularly valuable for ASO—they often contain the exact phrases users search for in the App Store.

Key fields: score, text, title, version, country

Cross-Platform App Intelligence

Compare user sentiment between iOS (App Store) and Android (Google Play) for the same app. Identify platform-specific issues, feature gaps, and satisfaction differences. Combine with the Google Play Reviews Scraper for unified cross-platform dashboards.

Key fields: appId, score, text, date, country

Product Management and Feature Prioritization

Feed review data into product analytics to identify the most-requested features and the most-reported bugs. Cross-reference with version to track whether fixes in new releases actually improved user satisfaction. Review titles provide quick-scan summaries of user priorities.

Key fields: text, title, score, version, date

Competitive Benchmarking

Extract reviews from competing apps in the same App Store category to compare user sentiment, feature gaps, and pain points. Run multi-app extractions in a single scraper run by providing multiple App IDs. Identify where competitors are weak and where they excel.

Key fields: appId, score, text, title, date

Global Market Research

Collect reviews from multiple App Store locales to understand how user sentiment varies by country. Cultural preferences, localization quality, and regional feature availability all affect reviews. Use country: "all" to build a comprehensive global dataset, then segment analysis by country code.

Key fields: country, score, text, date, appId

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Troubleshooting

Common Issues and Solutions

Issue	Cause	Solution
Only 500 reviews returned	Apple's API limit per country	This is an Apple platform limitation—use country: "all" to collect up to 500 reviews from each country
Fewer reviews than expected	App has fewer reviews in target country	Check the app's review count in the target App Store locale
Unexpected result quantity	maxItems set higher than available reviews	Adjust maxItems or check available reviews in the target country
Missing data in output	Results stored in Apify dataset	Check the "Storage" section in your task results for the complete dataset
Empty results	Invalid App ID format	Ensure you're using the numeric App ID (e.g., 389801252), not the app name or bundle ID

Performance Tips

• Start small: Test with maxItems: 50 to validate your setup before scaling
• Use date filtering: Set the until parameter to avoid re-extracting old reviews on scheduled runs
• Maximize coverage: Set country: "all" to collect reviews from every App Store locale (up to 500 per country)
• Multiple apps in one run: Provide multiple App IDs in the appIds array for competitive analysis
• Monitor billing: You are billed per review extracted, not per maxItems setting—if fewer reviews exist, you pay only for what's delivered

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Frequently Asked Questions

What App Store review data can I extract?

Extract review text, review titles (headlines), star ratings (1-5), review dates, reviewer usernames, reviewer profile URLs, app version at review time, country codes, App Store IDs, and direct review URLs—all in structured JSON or CSV format.

Can I export App Store reviews to CSV?

Yes. Download App Store reviews directly from Apify Console in JSON, CSV, or Excel format. This is ideal for spreadsheet analysis, database import, and product analytics dashboards.

Can I scrape reviews from multiple apps at once?

Yes. Provide multiple App IDs in the appIds array (e.g., ["389801252", "686449807"]). Each app's reviews are extracted within a single Actor run, with the appId field identifying which app each review belongs to.

Can I filter reviews by date?

Yes. Use the until parameter to extract only reviews newer than a specific date. This is ideal for continuous monitoring—on each scheduled run, set until to the date of your last extraction to avoid duplicates.

Can I scrape reviews from all countries?

Yes. Set the country parameter to all to fetch reviews from every App Store locale separately. Due to Apple's API limitations, each country returns a maximum of 500 reviews. This is the best way to maximize review coverage for popular apps.

Why is there a 500-review limit per country?

This is an Apple platform limitation, not a scraper limitation. Apple's public API returns a maximum of 500 reviews per country per app. To maximize your dataset, use country: "all" to collect up to 500 reviews from each available App Store locale.

Does this extract developer replies?

No. Unlike Google Play, the Apple App Store public API does not expose developer replies in review data. For app review data that includes developer responses, use the Google Play Reviews Scraper.

How is this different from the Google Play Reviews Scraper?

The App Store Reviews Scraper extracts iOS app reviews with review titles (headlines) and reviewer profile URLs. The Google Play Reviews Scraper extracts Android app reviews with developer replies, feature-specific quality ratings (criterias), and thumbs-up counts. Use both for cross-platform app intelligence. See the comparison table in Related Tools.

Can I use Python to scrape App Store reviews?

Yes. Full Python support via the Apify Client library. See the Quick Start Guide above for Python integration with client.actor("agents/appstore-reviews").

Can AI agents use this scraper?

Yes. Through Apify's Model Context Protocol (MCP) server, AI agents built with Claude Desktop, VS Code, or any MCP-compatible framework can call this scraper as a tool. This enables automated app monitoring, cross-platform analysis, and multi-step research pipelines. See the AI Agent Integration via MCP section for setup details.

How fast is the extraction?

Up to 200 reviews per second. Speed depends on the number of reviews available and Apple's response times, but this scraper is optimized for maximum throughput.

How many reviews can I extract per app?

Due to Apple's API limitations, the maximum is 500 reviews per country per app. To maximize coverage, set country: "all" to collect up to 500 reviews from each available App Store locale. For a popular app available in 40+ countries, this can yield 20,000+ reviews.

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Contact

Built by Agents — Where others search, we uncover. Our team of ex-Big Tech engineers, growth hackers, and data specialists builds high-performance scraping tools engineered for speed, precision, and reliability.

For questions or further assistance:

• Email: Reach out at whoaretheagents@gmail.com
• Discord: Join our community to connect with our support team

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Ready to start extracting App Store review data? At $0.10 per 1,000 reviews with up to 200 reviews/second and no API key required, this App Store Reviews Scraper API by Agents is the definitive tool for iOS app sentiment analysis, ASO research, competitive benchmarking, and cross-platform app intelligence. Start scraping today.