App Store Reviews Scraper - iOS Review Monitor & Alerts

Scrape Apple App Store reviews for any iOS app in any storefront country and export review text, star rating, title, app version, reviewer name, and date to JSON, CSV, or Excel. Filter by stars, date, or keyword, and turn on new-review monitoring to get only reviews you have not seen before on every scheduled run. No Apple API key, no App Store Connect account.

Real output from a verified run, cropped to a few rows and fields.

Real output from a default run of App Store Reviews Scraper in Apify Console.

What can this App Store reviews scraper do?

• Many apps and countries in one run - up to 30 app IDs x 30 storefronts (100 app-country pairs), interleaved so one app does not use up the whole limit.
• Paste App Store links - https://apps.apple.com/us/app/.../id389801252 works; the country in the link is used automatically.
• Star-rating filter - for example only 1-2 star reviews for a negative-review feed.
• Date filter - only reviews updated on or after a date, e.g. since your last release.
• Keyword filter - only reviews whose title or text contains crash, refund, subscription, ...
• New-review monitor - remembers review IDs between runs and outputs only new ones; start with a silent baseline so your first alert is not a flood.
• Spending-safe - checks your maximum run charge before each saved review and never emits more than you allowed.

What data can I extract from App Store reviews?

Field	Description
appId, appName, country	App and storefront
reviewId	Apple review ID (use with appId + country for deduplication)
rating	1 to 5 stars
title, text	Review headline and body
version	App version the review was written for, when Apple provides it
updatedAt	Apple's review timestamp (UTC)
reviewerName, reviewerUrl	Public reviewer name and profile link, when provided
reviewUrl	Apple review or app-reviews link
isNew	true when a monitor run finds a review it has not seen
scrapedAt	Collection timestamp

Each run also saves a SUMMARY (fetched, matched, and output counts per app-country pair, budget stop) and ERRORS to the key-value store.

How much does it cost to scrape App Store reviews?

Pay per review saved: $0.50 per 1,000 reviews, with Store discounts down to $0.40 per 1,000 on higher Apify plans. Plus one tiny start event ($0.00005 per GB). Platform usage is included.

Reviews saved	Price (standard rate)
100	$0.05
1,000	$0.50
10,000	$5.00

Filtered-out reviews and baseline runs produce no result charges. See the Pricing tab for current rates.

How to scrape App Store reviews

1. Enter one or more App IDs (the number after id in an App Store URL; 389801252 is Instagram) or paste App Store URLs.
2. Choose storefront Countries such as us, gb, ca, au, de.
3. Set Maximum output reviews (a global cap across all apps and countries).
4. Optional: star range, Since date, Text contains.
5. Click Start, then export from the Output tab.

Input example: critical reviews from two countries

{
  "appIds": ["389801252"],
  "countries": ["us", "gb"],
  "maxReviews": 100,
  "maxRating": 2,
  "sinceDate": "2026-09-01"
}

Input example: compare competitor apps

{
  "appIds": ["324684580", "1064216828"],
  "countries": ["us", "gb"],
  "maxReviews": 400
}

Input example: scheduled crash-review alert

{
  "appIds": ["389801252"],
  "countries": ["us"],
  "maxRating": 2,
  "textContains": "crash",
  "onlyNew": true,
  "monitorKey": "instagram-us-crashes",
  "initialRun": "baseline"
}

Save it as a task and schedule it hourly or daily. The first run silently remembers current reviews; later runs output only reviews that monitor has not seen.

Output example

{
  "appId": "389801252",
  "appName": "Instagram",
  "country": "US",
  "reviewId": "11223344556",
  "rating": 2,
  "title": "Keeps crashing after update",
  "text": "Since the last update the app closes when I open messages.",
  "updatedAt": "2026-10-20T14:05:00.000Z",
  "version": "402.0",
  "reviewerName": "example_user",
  "reviewerUrl": "https://itunes.apple.com/us/reviews/id000000000",
  "reviewUrl": "https://apps.apple.com/us/app/id389801252?see-all=reviews",
  "isNew": true,
  "scrapedAt": "2026-10-25T12:02:50.000Z"
}

Illustrative record, not a real customer review.

New-review monitoring: how it works

First-run mode	First run	Later runs
emit (default)	Outputs current matching reviews	Outputs matching reviews not seen before
baseline	Remembers reviews, outputs nothing	Outputs matching reviews not seen before

• State is stored in a named key-value store in your Apify account, scoped by monitorKey, app, country, and filters. Changing filters starts a new baseline.
• Up to 1,000 recent review IDs are remembered per app-country-filter combination.
• Don't run the same monitor twice at the same time; overlapping runs can emit duplicates.
• To send alerts, connect the task to Slack, email, Google Sheets, Make, Zapier, or n8n and forward only non-empty results.

Use cases

• Release QA - catch 1-2 star reviews mentioning crashes or login problems right after a release.
• Competitor research - compare complaints and feature requests across competing apps and countries.
• Voice of the customer - export review text with rating and version for tagging or LLM analysis.
• ASO and product teams - track rating mix per storefront over time with scheduled exports.

App Store Reviews API: run it from code

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("groupoject/app-store-review-monitor").call(run_input={
    "appIds": ["389801252"], "countries": ["us"], "maxReviews": 50, "maxRating": 2,
})
for r in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(r["rating"], r["title"])

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('groupoject/app-store-review-monitor').call(
  { appIds: ['389801252'], countries: ['us'], maxReviews: 20, maxRating: 2 },
  { maxTotalChargeUsd: 0.10 },
);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

cURL

curl -X POST "https://api.apify.com/v2/acts/groupoject~app-store-review-monitor/run-sync-get-dataset-items?maxTotalChargeUsd=0.10" \
  -H "Authorization: Bearer $APIFY_TOKEN" -H "Content-Type: application/json" \
  -d '{"appIds":["389801252"],"countries":["us"],"maxReviews":20,"maxRating":2}'

Also callable from AI agents through the Apify MCP server.

Use with AI agents (MCP)

Connect the Apify MCP server at https://mcp.apify.com?tools=groupoject/app-store-review-monitor in Claude Desktop, Cursor, VS Code or any MCP client, and your AI assistant can call this actor as a tool. Example prompt: "Get the newest 1-star reviews for this iOS app in the US store and summarize the top complaints."

FAQ

Do I need an Apple developer account or API key?

No. The Actor uses Apple's public customer-review feed and app lookup endpoint. It does not log in or access App Store Connect.

How many reviews can I get per app?

Apple's public feed exposes about 500 most recent reviews per app per country (10 pages of 50). To build a longer history, schedule the monitor and keep your exports. Add more countries to get more reviews for the same app.

Why did I get fewer reviews than maxReviews?

The feed window is exhausted, filters removed reviews, the storefront has few written reviews, or your run charge limit was reached. SUMMARY shows fetched, matched, and output counts per source.

Does it scrape Google Play reviews?

No, this Actor is Apple App Store only.

Does it include sentiment analysis?

No. Use the star filter, keyword filter, or your own analysis tool on the exported text.

Can it reply to reviews?

No. It only reads public reviews.

Is it legal to scrape App Store reviews?

The reviews are publicly visible. Use the data responsibly, respect Apple's terms, and avoid republishing personal information.

Related Actors

• Reddit Lead Finder & Sentiment Monitor - track what users say about your app on Reddit.
• YouTube Comments Scraper - feedback from video comments.
• Facebook Ads Library Scraper - see how competing apps advertise.