# App Store Reviews Scraper + Pain Point Analysis (v2) (`pappy-dev/appstore-reviews-v2`) Actor

Scrape Apple App Store reviews for any app and storefront (no login, official public RSS feed) and get pain-point / feature-request analysis on top: verbatim complaints, not keyword bags.

- **URL**: https://apify.com/pappy-dev/appstore-reviews-v2.md
- **Developed by:** [Backyard Tools](https://apify.com/pappy-dev) (community)
- **Categories:** Developer tools, Agents
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

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?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## App Store Reviews Scraper + Pain Point Analysis (v2)

Scrape Apple App Store reviews for any app and any storefront — no login — using Apple's
own public RSS feed, and get pain-point / feature-request analysis on top.

### Tested (2026-09-02)

5/5 well-known apps returned real reviews on the first request:

| App | App ID | Reviews returned |
|---|---|---|
| Notion | 1232780281 | 20/20 requested |
| Facebook | 284882215 | 20/20 requested |
| WhatsApp | 310633997 | 20/20 requested |
| Instagram | 389801252 | 20/20 requested |
| TikTok | 835599320 | 20/20 requested |

A single storefront page (50 reviews) took ~0.09s to fetch in that test.

### How it works

Apple has published this RSS feed for over a decade with no authentication and no rate-limit
wall for reasonable use — one of the most stable public data sources available. No scraping
countermeasures to fight, which is also why it needs almost no maintenance.

### Input

```json
{
  "targets": ["1232780281:us", "1232780281:jp"],
  "maxItems": 200,
  "analyses": ["overview", "group-regressions"]
}
```

Each target is `"AppID:storefront"`. Apple caps each storefront at ~500 reviews per app, and
every storefront holds a *different* set of reviews — pass more `"id:cc"` pairs to cover
more countries in one run.

### Output

One dataset item per review:

| Field | |
|---|---|
| `review_id` | Apple's review id |
| `author` | reviewer's public display name |
| `rating` | 1–5 stars |
| `text` / `title` | review body and headline |
| `date` | when the review was last updated |
| `group` | the app version the review was left on |
| `link` | the review's public URL on the App Store |

No email, phone number, or physical address is present — Apple's public feed doesn't carry
those fields.

### Analyses (billed once per run, not per review)

| Analysis | What you get |
|---|---|
| `overview` | count, average rating, negative share with a lower-confidence bound |
| `top-complaints` | actual excerpts from low-rating reviews |
| `top-requests` | actual excerpts asking for a feature |
| `group-regressions` | which release's ratings dropped versus the rest — the "did that update hurt us" question, answered directly |
| `trend` | monthly volume and negative share |

### Use Cases

- **Competitor monitoring**: track a rival app's rating trend and recurring complaints release over release.
- **Release QA triage**: run `group-regressions` right after shipping to catch a version that tanked ratings, with real complaint text attached.
- **Feature roadmap input**: mine `top-requests` for what users are actually asking for, in their own words.
- **ASO / App Store copy research**: see the exact language reviewers use to praise or criticize competing apps.

### Pricing

Pay per event: **$0.20 per 1,000 reviews** collected, plus **$0.05 per analysis** you select.

# Actor input Schema

## `targets` (type: `array`):

"AppID:国コード" 形式（例: "1232780281:us", "1232780281:jp"）。複数の国を回すには複数指定する

## `maxItems` (type: `integer`):

1 run で取得する最大件数

## `analyses` (type: `array`):

実行する分析（1 種につき 1 イベント課金）

## Actor input object example

```json
{
  "targets": [
    "284882215:us"
  ],
  "maxItems": 200,
  "analyses": [
    "overview",
    "top-complaints",
    "top-requests",
    "group-regressions",
    "trend"
  ]
}
```

# Actor output Schema

## `items` (type: `string`):

取得した各件（type=item）と、選択した分析の結果（type=analysis）

## `overview` (type: `string`):

件数・平均評点・期間・ネガティブ比率（下側信頼限界つき）

# 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 = {
    "targets": [
        "284882215:us"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("pappy-dev/appstore-reviews-v2").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 = { "targets": ["284882215:us"] }

# Run the Actor and wait for it to finish
run = client.actor("pappy-dev/appstore-reviews-v2").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 '{
  "targets": [
    "284882215:us"
  ]
}' |
apify call pappy-dev/appstore-reviews-v2 --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,pappy-dev/appstore-reviews-v2"
        }
    }
}

```

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/H0c3JfYUdqxODcURq/builds/JG6qddXpEHB7rlnsN/openapi.json