Google Play & App Store Reviews Scraper - Many Countries

Scrape public App Store and Google Play reviews in one run: rating, title, text, author name, app version, date, helpful votes and the developer's reply (Google Play). Paste app links or ids from either store, pick one or many countries, and also get an app-details row per app and country: average rating, ratings count, installs (Google Play), version, genre, price, content rating, size, release and update dates, developer website.

No login, no API key, no browser.

Why this one

• Both stores, one format. Mix App Store URLs, Apple ids, Google Play URLs and Android package names in one list.
• Many countries per run. Reviews differ by country - compare the US, Brazil, Germany... in one dataset.
• App details included. One extra row per app and country with the listing data you usually need next to the reviews.
• Complaints only? Use the rating window (e.g. 1-2 stars) to pull just the negative reviews.

Use cases

• Find complaints. Collect the 1-2 star reviews of your app or a competitor's and read what users complain about, with the app version and the developer's reply next to each one.
• Compare countries and competitors. Pull the same apps from several storefronts and compare ratings and review text market by market.
• Build a reviews dataset. Google Play and App Store reviews share one format, ready for sentiment analysis, topic modeling or an LLM.
• Keep a weekly record. Run it on a schedule to track the latest reviews and the current average rating of your app and its rivals.

Input example

{
  "apps": ["https://apps.apple.com/us/app/spotify-music-and-podcasts/id324684580", "com.spotify.music", "com.whatsapp"],
  "countries": ["us", "br", "de"],
  "sort": "newest",
  "maxReviewsPerApp": 200,
  "minRating": 1,
  "maxRating": 2,
  "includeAppDetails": true
}

An App Store URL that contains a country (/us/app/...) keeps that country.

Output examples

A review row:

{
  "type": "review",
  "store": "google",
  "appId": "com.spotify.music",
  "appName": "Spotify: Music and Podcasts",
  "reviewId": "e048f919-3afd-48c3-bf48-73ea10fa35e0",
  "text": "You have to pay just to skip some small parts of a song...",
  "rating": 1,
  "authorName": "Julian E.",
  "version": "9.1.88.2204",
  "date": "2026-10-04T22:24:02.917Z",
  "helpfulVotes": 0,
  "developerReply": null,
  "country": "us",
  "language": "en",
  "url": "https://play.google.com/store/apps/details?id=com.spotify.music&reviewId=e048f919-..."
}

An app row (type: "app"): appName, developer, averageRating, ratingCount, installs, minInstalls, histogram, version, genre, contentRating, price, currency, free, offersIAP, containsAds, released, updated, recentChanges, developerWebsite, privacyPolicy, icon (Google Play); sizeMb, minimumOsVersion, currentVersionRating, languages, sellerName (App Store).

Apps that cannot be found come back as free failure rows (success: false, with the reason). The SUMMARY record lists per app and country: reviews fetched and pushed.

Run it on a schedule and connect it to your tools

Schedule: in Apify Console open Schedules → Create, pick this actor and your input, and set it to run every Monday at 07:00 (your time zone) for a weekly look at the latest reviews and the current average rating of your app and its competitors. Each run returns the full, current result set as a new dataset.

Integrations (Actor → Integrations tab, no code):

• Google Sheets — append every run's rows to a sheet and chart the rating per app and country.
• Make, Zapier, n8n — start the actor from a scenario/zap/workflow and use the rows in the next steps.
• Webhook — get a POST to your endpoint when a run succeeds, then download the dataset.
• Slack / email — notify your team when a scheduled run finishes.

AI agents (MCP) — Claude, ChatGPT, Cursor, VS Code or any MCP client can run it as a tool: add the Apify MCP server https://mcp.apify.com?actors=kalilfagundes.w/app-reviews-scraper (sign in with your Apify account) and ask for the data in plain language. The agent fills the input from the input schema and reads the dataset back.

API — call it from your code (pip install apify-client / npm i apify-client):

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("kalilfagundes.w/app-reviews-scraper").call(run_input={
    "apps": [
        "https://apps.apple.com/us/app/spotify-music-and-podcasts/id324684580",
        "com.whatsapp"
    ],
    "countries": [
        "us",
        "br"
    ],
    "maxReviewsPerApp": 20,
    "minRating": 1,
    "maxRating": 2
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('kalilfagundes.w/app-reviews-scraper').call({
  "apps": [
    "https://apps.apple.com/us/app/spotify-music-and-podcasts/id324684580",
    "com.whatsapp"
  ],
  "countries": [
    "us",
    "br"
  ],
  "maxReviewsPerApp": 20,
  "minRating": 1,
  "maxRating": 2
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

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Pricing

Pay per event, platform usage included: one review event per review and one app event per app-details row (see the Pricing tab). Failure rows are not charged.

Limits

• Apple's public feed exposes at most 500 reviews per app per country (10 pages of 50) and no developer replies.
• Google Play pages 150 reviews per request; deep pages take longer.
• Author names are the public display names shown in the stores; no e-mail or profile data is collected.

Feedback

If this actor saves you time, a quick rating on its Store page helps other people find it. Something not working? Open an issue in the Issues tab and it gets fixed fast.