# App Store & Google Play Review Scraper — One Schema (`nelliel_future/app-store-play-review-scraper`) Actor

iOS and Android app reviews in ONE normalized format: stable IDs for dedupe, ISO dates, helpful counts, monitoring mode. No proxies needed.

- **URL**: https://apify.com/nelliel_future/app-store-play-review-scraper.md
- **Developed by:** [Nelliel](https://apify.com/nelliel_future) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 results

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 Review Scraper (one schema)

If you've ever pulled app reviews from both stores you know the problem. Apple hands you RSS XML with one set of fields. Google hands you something else entirely. The dates don't match, the rating fields don't match, and half your afternoon becomes a data-cleaning exercise instead of actual analysis.

This actor fixes that. You give it an app name — or both store IDs if you have them — and it returns iOS **and** Android reviews in one normalized JSON format. Same field names, same date format, same stable review IDs you can dedupe against across runs.

### What you get

For each app: one **summary record** (name, rating, total ratings count, genre, developer, store URL) and then the **reviews** themselves:

```json
{
  "review_id": "apple:14714962831",
  "platform": "apple",
  "rating": 5,
  "title": "Great for Teamwork",
  "body": "New to Slack but loving it",
  "author": "Gayle G",
  "published_at": "2026-10-26T20:09:22Z",
  "helpful_count": 0,
  "app_version": "26.10.30",
  "developer_reply": null,
  "app": {
    "store": "apple",
    "store_app_id": "618783545",
    "name": "Slack",
    "url": "https://apps.apple.com/us/app/slack/id618783545"
  }
}
```

- `review_id` is prefixed (`apple:` / `google:`) and stable — pull daily, dedupe locally, build your own history.
- Dates are always ISO 8601 UTC.
- `helpful_count`, `app_version`, and `developer_reply` come through when the source feed carries them.

### Example input

```json
{
  "apps": ["slack", "notion", "duolingo"],
  "maxReviewsPerApp": 100
}
```

Type a plain name and it resolves the right app on both stores (it checks the actual app title, so "Slack" won't accidentally grab "Slack for Intune"). Prefer certainty? Pass the exact IDs — numeric = App Store, dot-package = Google Play:

```json
{
  "apps": ["618783545", "com.Slack"]
}
```

### Monitoring mode

Give it a `since` date and it only returns newer reviews — designed for a daily scheduled run that feeds a dashboard, an alert, or a spreadsheet:

```json
{
  "apps": ["your.app.package"],
  "since": "2026-10-27",
  "maxReviewsPerApp": 500
}
```

### Multi-storefront

Pass several country codes (`"country": "us,de,fr"`) and it walks each storefront, deduping reviews by ID so you don't get repeats.

### The honest limitations

I'd rather tell you these up front than have you find them at 2am:

- **Apple's public RSS feed tops out around 50 recent reviews per storefront.** That's an Apple limit, not mine — no actor can honestly get "all 54,000 Slack App Store reviews" from public endpoints. For Apple, think *freshest reviews + monitoring*, not full archive. Google Play pages deep, so Android gets full history (thousands of reviews).
- **Apple's feed occasionally comes back empty for a specific app** even when reviews obviously exist. When that happens the summary record says so explicitly (`reviews_returned: 0` with a note) instead of quietly pretending the app has no reviews. Re-run later and it usually recovers.
- **Public endpoints only.** Google's public review endpoint plus Apple's public RSS feed. If Apple's feed runs dry (it throttles datacenter IPs), the actor quietly retries through Apify's residential proxy — a few kilobytes per app. No stealth tooling; it can only ever get what the stores publicly publish.

### Good fits

- Competitor review monitoring (ship a release, watch both stores' ratings react)
- Feeding a "what users hate this week" report to product teams
- Keyword alerts on new reviews (crash, paywall, refund...)
- Building launch-week comparison datasets

### Pricing

Pay per result item — you only pay for records actually produced. A run of 3 apps × 100 reviews is roughly $0.60.

Something broken or a weird edge case? Message me on the actor's issues tab — I actually look at them.

# Actor input Schema

## `apps` (type: `array`):

One per line. Use a plain name ('Notion' — searched on both stores), a numeric App Store ID ('284882215'), or a Google Play package ID ('com.slack').

## `platform` (type: `string`):

Which store to pull from when you pass plain names. Numeric IDs are always Apple, package IDs always Google Play.

## `country` (type: `string`):

Comma-separated store countries, e.g. 'us' or 'us,gb,de'. Apple returns the freshest ~50 reviews per country; multiple countries widen coverage.

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

Review language (applies to Google Play). Two-letter code, e.g. 'en'.

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

Cap per app across all selected countries. Apple caps at ~50 per storefront; Google Play pages deeper.

## `sort` (type: `string`):

Google Play supports both. Apple RSS only exposes newest-first (helpful silently falls back to newest there).

## `since` (type: `string`):

Monitoring mode: ISO date or datetime, e.g. '2026-10-01'. Combined with Apify's scheduler this becomes an incremental review feed.

## `useApifyProxyForApple` (type: `boolean`):

Apple serves empty review feeds to datacenter IPs. Keep this on: if a direct fetch comes back empty, the actor retries through an Apify residential proxy (small usage fee, few KB per app). Turn off to use direct requests only.

## Actor input object example

```json
{
  "apps": [
    "Notion",
    "Slack"
  ],
  "platform": "both",
  "country": "us",
  "language": "en",
  "maxReviewsPerApp": 100,
  "sort": "newest",
  "useApifyProxyForApple": true
}
```

# Actor output Schema

## `results` (type: `string`):

Dataset items. Each item has record_type: review | app_summary | app_error. Review items: review_id ('apple:...' or 'play:...', safe for dedupe across runs), platform, app {store, store_app_id, name, url}, author, rating (1-5), title (Apple only, null on Play), body, published_at (ISO 8601 UTC), helpful_count, app_version, developer_reply {body, at} | null, country, scraped_at. app_summary items: platform, store_app_id, name, developer, url, overall_rating, total_ratings, price, genres, current_version, version_released_at.

# 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 = {
    "apps": [
        "Notion",
        "Slack"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("nelliel_future/app-store-play-review-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 = { "apps": [
        "Notion",
        "Slack",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("nelliel_future/app-store-play-review-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 '{
  "apps": [
    "Notion",
    "Slack"
  ]
}' |
apify call nelliel_future/app-store-play-review-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,nelliel_future/app-store-play-review-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/1S9BBDRWfNc6scnY5/builds/fABDwvDApiIdzLp8U/openapi.json