# App Store & Google Play Reviews Scraper – Both Stores, One Run (`nourishing_courier/app-reviews-scraper`) Actor

App Store Reviews Scraper and Google Play Reviews Scraper in one run. Rating, title, text, version, date, helpful votes and developer replies in one unified schema for iOS and Android. Filter by star rating, collect several countries, no API key, no start fee – pay only for delivered reviews.

- **URL**: https://apify.com/nourishing\_courier/app-reviews-scraper.md
- **Developed by:** [Ani Björkström](https://apify.com/nourishing_courier) (community)
- **Categories:** E-commerce, Business, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$2.00 / 1,000 reviews

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## App Store & Google Play Reviews Scraper – Both Stores, One Run

The **App Store Reviews Scraper** and **Google Play Reviews Scraper** you would otherwise run separately, in one actor with one unified schema. Paste App Store URLs, Google Play URLs, Apple numeric IDs or Android package names in any mix and get every review as a flat row: star rating, title, text, version, date, helpful votes and the **developer reply**.

- **Both stores, one schema.** `store`, `appId`, `rating`, `text`, `version`, `date`, `developerReply` mean the same thing whether the review came from iOS or Android, so one spreadsheet, one dashboard or one LLM prompt covers your whole app.
- **Pay only for delivered reviews, no start fee.** An app that returns nothing produces an explanatory row and costs nothing.
- **No API key, no proxy, no login.** Reads Apple's public review feed and Google Play's own web endpoint directly – a typical run finishes in seconds.

***

### What you get

| Field | Description |
|---|---|
| `store` | `appstore` or `googleplay` |
| `appId`, `appName` | Apple numeric ID or Android package name, plus the store title |
| `country`, `language` | Storefront country (Apple) / `hl` language (Google Play) |
| `reviewId` | Stable review ID |
| `userName` | Reviewer display name |
| `rating` | 1–5 stars |
| `title` | Review headline (App Store only – Play reviews have no title) |
| `text` | Review body |
| `version` | App version the review was written for |
| `date` | ISO 8601 UTC |
| `thumbsUp` | Helpful votes |
| `developerReply`, `developerReplyDate` | The developer's public answer, when there is one (Google Play) |
| `url` | Link back to the review |
| `scrapedAt` | ISO 8601 UTC timestamp of the run |
| `error` | Only on problem rows: why an app/country returned nothing |

***

### Input

Everything goes in one field, so the actor never scrapes a default app on top of yours. Runs with no input at all (WhatsApp on both stores), so a scheduled run is never empty.

**Same app on both stores, newest 500 reviews each**

```json
{
  "appUrls": [
    "https://apps.apple.com/us/app/whatsapp-messenger/id310633997",
    "com.whatsapp"
  ],
  "maxReviewsPerApp": 500
}
```

**Only 1–2 star complaints with text, several countries**

```json
{
  "appUrls": ["310633997", "https://play.google.com/store/apps/details?id=com.whatsapp"],
  "countries": ["us", "gb", "de", "se"],
  "minRating": 1,
  "maxRating": 2,
  "onlyWithText": true,
  "sortBy": "helpful"
}
```

**Competitor set for a weekly report**

```json
{
  "appUrls": ["com.spotify.music", "324684580", "com.soundcloud.android", "336353151"],
  "maxReviewsPerApp": 200,
  "language": "en"
}
```

| Option | Default | What it does |
|---|---|---|
| `appUrls` | WhatsApp (both stores) | App Store URLs, Play URLs, Apple IDs (`310633997`, `id310633997`) or package names (`com.whatsapp`), routed to the right store automatically |
| `maxReviewsPerApp` | `200` | Cap per app and country (up to 20,000). Google Play returns the full history; the App Store feed stops at 500 per country |
| `countries` | `["us"]` | Two-letter storefront codes. A country inside a pasted URL always wins |
| `language` | `en` | Google Play review language (`hl`) |
| `sortBy` | `newest` | `newest`, `helpful` or `rating`. Apple applies it server-side; Play only serves newest-first, so other orders are applied to the collected reviews |
| `minRating`, `maxRating` | `1`, `5` | Keep only reviews inside this star range |
| `onlyWithText` | `false` | Skip star-only ratings |
| `concurrency` | `4` | Apps fetched in parallel (1–10) |
| `proxyConfiguration` | off | Neither store needs a proxy at normal volumes |

***

### Output example

```json
{
  "store": "googleplay",
  "appId": "com.whatsapp",
  "appName": "WhatsApp Messenger",
  "country": "us",
  "language": "en",
  "reviewId": "d40bb75a-d1a5-44b3-863d-c8624445efe9",
  "userName": "Jonathan Spencer",
  "rating": 1,
  "title": null,
  "text": "Whenever I try to link it to another device the account is placed under review...",
  "version": "2.26.33.74",
  "date": "2026-08-28T20:40:15+00:00",
  "thumbsUp": 7,
  "developerReply": null,
  "developerReplyDate": null,
  "url": "https://play.google.com/store/apps/details?id=com.whatsapp&reviewId=d40bb75a-d1a5-44b3-863d-c8624445efe9",
  "scrapedAt": "2026-09-16T20:24:10+00:00"
}
```

An App Store row looks the same, with `store: "appstore"`, a `title`, and `url` pointing at the App Store review. If an app has no reviews in a storefront you get one row with `error` explaining it instead of a silent gap.

***

### Use cases

- **Product and UX teams** – pull the newest 1–2 star reviews after every release, across both stores, and route them to Slack, Linear or Jira.
- **App marketing and ASO** – mine review language for keywords and feature requests, compare rating distributions between iOS and Android, track how a competitor's update landed.
- **Customer support** – see which complaints already have a developer reply and which are still unanswered.
- **AI and sentiment analysis** – researchers and builders feed thousands of clean rows into GPT, Claude or a classifier; `rating`, `text`, `version` and `date` are all you need for a trend chart.
- **Investors and analysts** – benchmark review volume and sentiment for a portfolio of apps over time.
- **Agencies** – one scheduled run per client app, both stores, straight into Google Sheets or Looker Studio.

***

### Pricing

**$2 per 1,000 reviews**, charged only for reviews written to the dataset. There is **no actor start fee** and no charge for apps that return nothing. Filtered-out reviews (outside your star range or without text) are never charged. Because both stores come in one run you do not pay two start fees or maintain two integrations.

***

### Integrations

**Python**

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("nourishing_courier/app-reviews-scraper").call(run_input={
    "appUrls": ["com.whatsapp", "310633997"],
    "maxReviewsPerApp": 300,
    "minRating": 1,
    "maxRating": 2,
})
for review in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(review["store"], review["rating"], review["text"][:80])
```

**JavaScript**

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

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('nourishing_courier/app-reviews-scraper').call({
    appUrls: ['https://apps.apple.com/us/app/whatsapp-messenger/id310633997', 'com.whatsapp'],
    countries: ['us', 'gb'],
    maxReviewsPerApp: 500,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, 'reviews');
```

**curl**

```bash
curl -X POST "https://api.apify.com/v2/acts/nourishing_courier~app-reviews-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"appUrls":["com.whatsapp","310633997"],"maxReviewsPerApp":100}'
```

**n8n, Make, Zapier** – use the Apify node/module, select this actor, paste an input above and map the rows to Google Sheets, Airtable, Notion or Slack. Filter on `store` or `rating` downstream. **MCP** – expose it via the Apify MCP server and an agent can ask for "the latest negative reviews of com.whatsapp" as a tool call. Results are also available as JSON, CSV, Excel, XML and RSS.

***

### Limits and fair use

The App Store's public feed serves at most 500 reviews per storefront (50 per page, 10 pages) – add more `countries` to collect beyond that. Google Play returns the full history, newest first, and its reviews carry no title. Both endpoints are public and unauthenticated; the actor sends one request per page and backs off on errors, so no proxy is needed at normal volumes. Reviews are public user content – use them in line with Apple's and Google's terms and applicable privacy law, and avoid re-identifying reviewers.

***

### Why one actor for both stores

Single-store review scrapers are cheap, but a product team never looks at only one platform. Running two actors means two schemas to reconcile (Apple's `title` and `im:voteSum` versus Play's positional payload), two schedules, two integrations and two start fees. This actor normalises both feeds into the same 17 columns, routes each entry to the right store automatically, keeps the App Store's per-country limit and Google Play's language handling out of your way, and bills a single per-review price with no start fee. If you only ever need one store, it still works exactly the same – just paste one kind of ID.

***

### FAQ

#### Can I scrape App Store and Google Play reviews in one run?

Yes – that is the point of this actor. Put both URLs (or an Apple ID and a package name) in `appUrls` and every row carries a `store` field so you can split or combine them later.

#### How many App Store reviews can I get per app?

Apple's public feed stops at 500 per country. List several `countries` (`us`, `gb`, `de`, `fr`, `jp`…) and you get up to 500 from each storefront.

#### How many Google Play reviews can I get?

The full history, newest first, up to `maxReviewsPerApp` (max 20,000). Set `language` to collect reviews written in a specific language.

#### Does it include developer replies?

Yes. `developerReply` and `developerReplyDate` are filled on Google Play reviews that have a public answer. Apple's public feed does not expose replies, so those fields are `null` on App Store rows.

#### Can I get only negative reviews?

Set `minRating: 1` and `maxRating: 2` (and `onlyWithText: true` if you want written feedback only). Filtered-out reviews are not charged.

#### Do I need an API key or proxy?

No. Neither store requires authentication for public reviews, and the actor runs without a proxy by default.

#### What does it cost?

$2 per 1,000 delivered reviews, no start fee. A run with 300 reviews costs $0.60.

#### Does it work with n8n or Make?

Yes. Both have an Apify integration; pass the JSON input and consume the dataset. Rows are flat, so they map directly onto spreadsheet columns.

#### Why did an app return an `error` row?

Usually a wrong ID, a package name that does not exist in that country, or an app with no reviews in the chosen storefront. The `error` text says which. Those rows are free.

#### How fast is it?

Seconds. The default run (WhatsApp, both stores, 200 reviews each) finishes in about 5 seconds.

# Actor input Schema

## `appUrls` (type: `array`):

One field for both stores. Paste App Store URLs, Google Play URLs, Apple numeric IDs (310633997) or Android package names (com.whatsapp) in any mix — each entry is routed to the right store automatically.

## `maxReviewsPerApp` (type: `integer`):

Cap per app and country. Google Play returns the full history; the App Store caps at 500 per country, so add more countries below to get past that.

## `countries` (type: `array`):

Two-letter country codes, e.g. us, gb, de, se. The App Store keeps a separate review feed per storefront, so listing several is how you collect more than 500 Apple reviews. A country inside a pasted URL always wins.

## `language` (type: `string`):

Language code for Google Play reviews, e.g. en, de, es, sv. The App Store feed is per country rather than per language.

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

Applied by the App Store directly. Google Play only serves newest-first, so for Play the chosen order is applied to the reviews collected in this run.

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

Keep only reviews at or above this many stars. Set both to 1 to collect only one-star complaints.

## `maxRating` (type: `integer`):

Keep only reviews at or below this many stars.

## `onlyWithText` (type: `boolean`):

Skip star-only ratings that carry no written feedback.

## `concurrency` (type: `integer`):

How many apps to fetch at once. Lower this if a store starts rate limiting you.

## `proxyConfiguration` (type: `object`):

Optional. Neither store needs a proxy for normal volumes; turn one on only if you are scraping very large numbers of apps and start seeing rate limits.

## Actor input object example

```json
{
  "appUrls": [
    "https://apps.apple.com/us/app/whatsapp-messenger/id310633997",
    "com.whatsapp"
  ],
  "maxReviewsPerApp": 200,
  "countries": [
    "us"
  ],
  "language": "en",
  "sortBy": "newest",
  "minRating": 1,
  "maxRating": 5,
  "onlyWithText": false,
  "concurrency": 4,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `reviews` (type: `string`):

Every review with its rating, text, version, date and developer reply.

## `reviewsCsv` (type: `string`):

The same records as a spreadsheet-ready CSV file.

## `consoleView` (type: `string`):

Open the run's dataset in Apify Console.

# 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 = {
    "appUrls": [
        "https://apps.apple.com/us/app/whatsapp-messenger/id310633997",
        "com.whatsapp"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("nourishing_courier/app-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 = { "appUrls": [
        "https://apps.apple.com/us/app/whatsapp-messenger/id310633997",
        "com.whatsapp",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("nourishing_courier/app-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 '{
  "appUrls": [
    "https://apps.apple.com/us/app/whatsapp-messenger/id310633997",
    "com.whatsapp"
  ]
}' |
apify call nourishing_courier/app-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,nourishing_courier/app-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/UqfU63qPeoXws5LuI/builds/Tx729NPlHp809if9l/openapi.json