# Mobile App Review Intelligence (`glowing_glove/mobile-app-review-intelligence`) Actor

Turn recent public Apple App Store reviews into compact product intelligence with complaint themes, praise themes, version signals, and recommended actions.

- **URL**: https://apify.com/glowing_glove/mobile-app-review-intelligence.md
- **Developed by:** [Ushba Khan](https://apify.com/glowing_glove) (community)
- **Categories:** E-commerce, Social media, Automation
- **Features:** Limited permissions
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$24.00 / 1,000 analyzed apps

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

## Mobile App Review Intelligence

Turn recent public Apple App Store reviews into compact product intelligence with complaint themes, praise themes, version signals, and recommended actions.

Mobile App Review Intelligence is built for buyers who need clean, source-backed data they can export into spreadsheets, CRMs, dashboards, alerts, or enrichment workflows. The actor focuses on the business object promised by its name and avoids dumping raw HTML, debug metadata, run timestamps, actor names, or unrelated crawl noise into successful dataset rows.

### Who Uses It

- app founders
- product managers
- ASO teams
- review researchers

### What It Extracts

- App Name
- App Id
- Rating Average
- Review Count
- Complaint Themes
- Praise Themes
- Version Signals
- Recommended Actions

### Input

Use the input fields in the Apify UI to provide the public URLs, keywords, companies, pages, profiles, tickers, topics, or source lists relevant to this actor. Keep the first run small, inspect the dataset, and then raise limits or schedule recurring runs when the rows match your workflow.

### Output You Get

Successful dataset rows are compact and actor-specific. Important fields include:

- `appName`
- `appId`
- `ratingAverage`
- `reviewCount`
- `complaintThemes`
- `praiseThemes`
- `versionSignals`
- `recommendedActions`

Failure rows, when needed, include a short error or warning so you can fix bad inputs or blocked sources. Successful rows do not include unnecessary run metadata such as actor name, started time, finished time, raw input echo, or generic status noise.

### Good Use Cases

- Build focused lead lists or research tables from public sources.
- Monitor changes and signals that matter for sales, SEO, ecommerce, marketing, product, or research workflows.
- Export clean rows to Google Sheets, Airtable, BI tools, CRM systems, or automation pipelines.
- Run small tests before scaling to larger scheduled jobs.

### Reliability Notes

The actor uses guarded limits, request timeouts, retries where useful, and compact output rows. Public websites can change, block traffic, or hide data behind login walls; when that happens, the actor returns useful warnings instead of charging for empty success rows whenever the implementation can avoid it.

# Actor input Schema

## `appUrlsOrIds` (type: `array`):

Apple App Store app URLs or numeric app IDs.

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

Two-letter App Store country code used for reviews and metadata.

## `maxReviews` (type: `integer`):

Maximum recent public reviews to analyze for each app.

## `maxReviewPages` (type: `integer`):

How many App Store RSS review pages to request per app.

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

Maximum time to wait for each Apple public endpoint request.

## `maxConcurrency` (type: `integer`):

How many apps to analyze at the same time.

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

Optional proxy configuration. Most App Store review runs work without proxy.

## Actor input object example

```json
{
  "appUrlsOrIds": [
    "284882215",
    "333903271"
  ],
  "country": "us",
  "maxReviews": 30,
  "maxReviewPages": 2,
  "requestTimeoutSecs": 25,
  "maxConcurrency": 3,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

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

Open the clean dataset rows produced by Mobile App Review Intelligence.

## `summary` (type: `string`):

No description

# 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 = {
    "appUrlsOrIds": [
        "284882215",
        "333903271"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("glowing_glove/mobile-app-review-intelligence").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 = { "appUrlsOrIds": [
        "284882215",
        "333903271",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("glowing_glove/mobile-app-review-intelligence").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 '{
  "appUrlsOrIds": [
    "284882215",
    "333903271"
  ]
}' |
apify call glowing_glove/mobile-app-review-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,glowing_glove/mobile-app-review-intelligence"
        }
    }
}
```

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/XfXaM4cOi6h4C5GeJ/builds/RTGyPIvj44NYrlZre/openapi.json