App Store Reviews Tracker

Pull Apple App Store reviews and ratings for any iOS app, storefront by storefront. One row per review: rating, title, text and date, plus the storefront's rating summary (average, number of ratings and the count for each star). No login, no API key.

Each storefront has its own reviews and its own ratings, so one run over us, gb, de, jp and br shows how the same app is rated in five markets.

What you get

{
  "snapshotAt":            "2026-10-23T10:12:44+00:00",
  "appId":                 "310633997",
  "appName":               "WhatsApp Messenger",
  "country":               "us",
  "reviewId":              "13657831289",
  "rating":                5,
  "title":                 "WhatsApp not bad",
  "body":                  "WhatsApp’s not bad at all ...",
  "date":                  "2026-01-21T04:48:38.000Z",
  "storefrontRating":      4.7,
  "storefrontRatingCount": 18826665,
  "stars5":                15890695,
  "stars4":                1460947,
  "stars3":                570035,
  "stars2":                256139,
  "stars1":                648849,
  "url":                   "https://apps.apple.com/us/app/whatsapp-messenger/id310633997?see-all=reviews"
}

Apple shows about 10 reviews per app and storefront; the actor returns those, so a run gives up to about 10 rows for every app and country pair. Reviewer names are never included; e-mail addresses and phone numbers inside review text are replaced with [email removed] / [phone removed].

How to use

Input.

{
  "appIds":    ["389801252", "544007664"],
  "countries": ["us", "gb", "de"],
  "sortBy":    "mostRecent"
}

appIds: numeric Apple App Store IDs or App Store URLs. The ID is the number at the end of the URL: apps.apple.com/us/app/.../id<NUMBER>. Common examples:

App	ID
Instagram	389801252
YouTube	544007664
X / Twitter	333903271
Netflix	363590051
Spotify	324684580
Snapchat	447188370
TikTok	835599320
Reddit	1064216828
Slack	618783545
WhatsApp	310633997

countries: two-letter storefront codes. Each storefront has its own reviews and ratings: useful for multi-market sentiment and rating tracking. A code that is not an App Store storefront is skipped and named in the log.

sortBy: mostRecent (default) lists each storefront's reviews newest first; mostHelpful keeps the order Apple shows them in.

Schedule it daily or weekly: every run is a new snapshot of the rating summary, so the star counts show how ratings move release over release.

Pricing

Pay per event. Price per 1,000 events:

Event	Base price	Bronze	Silver	Gold
Apple App Store review extracted	$0.30	$0.27	$0.24	$0.21

Bronze, Silver and Gold are the discounts Apify gives users of its paid plans. The Pricing tab always shows the current prices.

Buyer

• Mobile growth teams running weekly review sentiment reviews.
• Competitor watch: how a competitor's rating moves in each market.
• Product managers reading critical reviews after a release.
• ASO consultants comparing ratings across storefronts.
• Crisis detection: flag a sudden drop in the average rating.

Run it through the API

Python, with the apify-client package:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("v0iddo/app-store-reviews-tracker").call(run_input={"appIds": ["389801252", "544007664"]})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript, with the apify-client package:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('v0iddo/app-store-reviews-tracker').call({"appIds": ["389801252", "544007664"]});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

One HTTP call that waits for the run and returns the rows (for runs that finish within 5 minutes):

curl -X POST "https://api.apify.com/v2/acts/v0iddo~app-store-reviews-tracker/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"appIds": ["389801252", "544007664"]}'

Use it from an agent (MCP)

Claude, Cursor, VS Code and other MCP clients can call this actor as a tool through the Apify MCP server. Add it to the client's MCP configuration:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=v0iddo/app-store-reviews-tracker",
      "headers": {
        "Authorization": "Bearer <YOUR_APIFY_TOKEN>"
      }
    }
  }
}

FAQ

Do I need an account, cookies or an API key?

No. The actor reads public data without logging in. You only need an Apify account to start it.

How am I charged?

Pay per event, at the prices on the Pricing tab for your Apify plan (the Pricing section of this page lists them). The platform usage of the run is included in those prices, and your spending limit for a run is always respected.

Why did my run return no results?

The status message and the log of the run say why: usually nothing matched the input, or the source did not answer for a moment. Check the input against the example above and run it again.

Can I run it on a schedule?

Yes. Save your input as a task and add a schedule in the Apify Console (daily, hourly or with a cron expression). Each run gets its own dataset, so you keep a history.

Which formats can I export?

JSON, CSV, Excel, XML, HTML table and RSS from the Output tab or the API. Integrations send the rows to Google Sheets, Slack, Make, Zapier, n8n or a webhook.

Is collecting this data allowed?

The actor collects data that the source publishes openly, without a login. Public data can still be personal data under laws such as the GDPR, and sources have their own terms: make sure your use of the data follows the rules that apply to you.

What happens when the source changes?

An automated test runs the actor every day on the example input and checks the rows, not only that the run finished. When a check fails, the actor is repaired and rebuilt; the build history on this page shows each update.

Something is missing or wrong. Where do I report it?

Open an issue on the Issues tab of this actor with the run link. Requests for a new field are welcome too.

Related actors

• App Store Scraper: App Details, Ratings, Prices
• App Store Search Scraper: Apps by Keyword
• App Store Top Charts Scraper: Ranks by Country and Genre
• Android App Metadata Scraper: Google Play Details, Ratings
• App Store Developer Scraper: All Apps by Developer
• AliExpress Scraper: Prices, Sold Counts / $1.50 per 1,000

Source

The app's public App Store page for each storefront, https://apps.apple.com/<country>/app/id<APP_ID>?see-all=reviews, which the App Store's robots.txt allows. The actor reads the data the page carries (reviews and the rating summary) and paces 0.5 s between pages.