# Apple App Store Reviews & App Feedback Analyzer (`obliging_persimmon_cki/app-store-feedback-analyzer`) Actor

Collect bounded public Apple App Store reviews and turn them into structured feedback, issue clusters, aggregate reports, and cautious release-impact signals.

- **URL**: https://apify.com/obliging\_persimmon\_cki/app-store-feedback-analyzer.md
- **Developed by:** [Dung Huynh](https://apify.com/obliging_persimmon_cki) (community)
- **Categories:** AI, Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 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/platform/actors/running/actors-in-store#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

## Apple App Store Reviews & App Feedback Analyzer

Collect bounded public Apple App Store reviews from Apple’s RSS/JSON customer-review feed and turn them into normalized review records, shared-core analysis, platform-scoped clusters, aggregate reports, and cautious release-impact observations.

This Actor is the Apple source prerequisite for the Cross-Platform Mobile App Feedback Intelligence product. It is not an automatic app matcher and it does not scrape authenticated App Store Connect data.

### What it supports

- Numeric Apple App Store app IDs and public App Store URLs.
- Storefront country selection and a requested feed locale hint.
- Bounded pagination with review-ID deduplication.
- Raw review records with title, text, rating, date, app version, helpful votes, and source diagnostics.
- Shared feedback-analysis contracts, clustering, per-app reports, and observational release windows.
- Partial source failure: successful apps and already-collected reviews remain available when another request fails.
- English and Vietnamese contract fixtures; the feed locale is preserved as a request dimension.

### Input example

```json
{
  "appIds": ["123456789"],
  "country": "US",
  "language": "en",
  "maxReviewsPerApp": 50,
  "maxPagesPerApp": 10,
  "analysis": { "enabled": true },
  "aggregation": { "enabled": true, "minimumClusterSize": 2 }
}
```

Use `appStoreUrls` when the numeric ID is not already available. Explicit IDs take precedence over duplicate URL IDs.

### Release impact

Set `mode` to `releaseImpact` and provide `release.releasedAt`, `daysBefore`, and `daysAfter`. The result compares review windows around the release timestamp and uses observational language such as “issue mentions increased after release.” It does not prove causation.

### Output

Dataset records include `review`, `sourceDiagnostic`, `feedbackCluster`, `productFeedbackReport`, and `feedbackImpactReport` records. Normalized records retain the source platform as `apple-app-store`, the Apple app ID, original text, source locale, storefront country, and nullable fields where Apple does not expose metadata.

`RUN_STATS` records collection, analysis, aggregation, runtime, memory, and error counts. Per-app reports are stored under `APP_STORE_REPORT_<app-id>`.

### Limitations and responsible use

- The public feed is bounded and storefront-specific; it is not a complete worldwide review archive.
- Apple’s public feed does not guarantee the reviewer’s original language. `language` is retained as the requested feed locale and must not be treated as ground-truth reviewer language when it is unavailable.
- Developer replies are not exposed by this public feed and remain `null` unless a future permitted source provides them.
- Missing app-version, country, language, or date fields remain `null`/`unknown`; the Actor does not invent metadata.
- Detected issues are user reports, not confirmed defects. Important product decisions require manual validation.
- AI or fallback analysis may misclassify sarcasm, ambiguity, or mixed-language feedback.

### Local development

```bash
npm install
node --test test/*.test.mjs
apify validate-schema
```

The Actor uses Apple’s public RSS/JSON customer-review feed and does not require an API key for public review collection. Respect Apple’s current feed terms, rate limits, and applicable laws.

# Actor input Schema

## `mode` (type: `string`):

Collect review records or compare feedback around an Apple release.

## `appIds` (type: `array`):

Numeric Apple App Store application IDs.

## `appStoreUrls` (type: `array`):

Public App Store URLs containing an /id<number> segment. Explicit app IDs are preserved and take precedence over duplicate URL IDs.

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

Two-letter storefront code used by the public RSS feed.

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

Locale hint sent to the public feed. Apple does not expose a guaranteed reviewer-language field in this feed; unknown language must remain unknown in downstream comparisons.

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

Hard cap after pagination and review-ID deduplication.

## `maxPagesPerApp` (type: `integer`):

Apple public feed pagination is bounded; the Actor caps this value at 10 pages.

## `requestTimeoutSecs` (type: `integer`):

Timeout for each public Apple feed request.

## `analysis` (type: `object`):

Run the shared deterministic feedback-analysis core.

## `aggregation` (type: `object`):

Create platform-level clusters and per-app reports.

## `release` (type: `object`):

Release metadata required by releaseImpact mode.

## `daysBefore` (type: `integer`):

Calendar days collected before the release boundary.

## `daysAfter` (type: `integer`):

Calendar days collected after the release boundary.

## `maxReviewsPerPeriod` (type: `integer`):

Hard cap applied to each release comparison collection.

## `debug` (type: `boolean`):

Enable additional local diagnostic logging.

## Actor input object example

```json
{
  "mode": "reviews",
  "country": "US",
  "language": "en",
  "maxReviewsPerApp": 50,
  "maxPagesPerApp": 10,
  "requestTimeoutSecs": 30,
  "daysBefore": 14,
  "daysAfter": 14,
  "maxReviewsPerPeriod": 100,
  "debug": false
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("obliging_persimmon_cki/app-store-feedback-analyzer").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("obliging_persimmon_cki/app-store-feedback-analyzer").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 '{}' |
apify call obliging_persimmon_cki/app-store-feedback-analyzer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,obliging_persimmon_cki/app-store-feedback-analyzer"
        }
    }
}

```

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/LATGoTgyHObgOPfi7/builds/ALlhK2qs9wwbxQoYA/openapi.json