# App Store Review Insights & Themes | Appalize (`appalize/app-store-review-insights`) Actor

Analyze App Store review samples: star distribution, low-rating share, version and month summaries, theme mentions and traceable review evidence.

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

## Pricing

from $20.00 / 1,000 review insight reports

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 Review Insights & Themes | Appalize

Analyze App Store review samples: star distribution, low-rating share, version and month summaries, theme mentions and traceable review evidence.

### Quick start

```json
{
  "apps": [
    "324684580"
  ],
  "countries": [
    "us"
  ],
  "maxItems": 10,
  "maxReviewsPerApp": 100
}
```

### What it analyzes

For each app and country, receive one report containing:

- Review sample size, mean rating, star distribution and one/two-star share.
- Per-version and per-month sample summaries.
- Stability, payments, advertising, account and performance keyword mentions.
- The matching review IDs and the underlying sampled reviews.
- Date coverage, filters and pages checked.

### Transparent method

Theme detection uses deterministic English/Turkish keyword rules, without a paid LLM. A mention is not sentiment or a confirmed defect. Negation, spelling variations and other languages may be missed. Each theme includes evidence IDs so you can inspect the underlying text.

### Coverage

Up to **10 apps**, **500 reviews per app/country** and **10 public RSS pages**. The source can return fewer. Sort by recent or helpful; optional rating and date filters apply before analysis. Monthly counts and per-version scores describe the filtered sample, not all customer reviews. A genuine empty sample has size zero and null mean/share, not a fabricated rating.

### Output, automation and cost control

Results are stored in the default dataset; use JSON to preserve nested arrays, or export CSV/Excel through Apify. `RUN-SUMMARY` contains counts and source failures. Each row has source and collection time. `maxItems` caps reports/snapshots, not nested reviews or cohort members. Checkpoints deduplicate resumed work; downstream consumers should also use `recordId` within a run because dataset/checkpoint writes are not atomic.

Use the Apify API, schedules, Make, n8n or MCP integration. No Appalize key, App Store Connect credentials or external LLM key is needed. Only Apple App Store is supported.

**Pricing:** $20 per 1,000 successful app/storefront review reports, plus $0.00005 per Actor start (one event per GB, minimum one). Platform usage is included. Each result includes all nested data; failed units have no result charge. Use the live Pricing tab and maximum charge setting before running.

Built by [Appalize](https://appalize.com). Report reproducible issues with a run ID and non-sensitive input in the Actor Issues tab.

# Actor input Schema

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

Apple numeric IDs, bundle IDs or HTTPS App Store URLs.

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

Up to 10 Apple storefronts. One report/snapshot per app and country; benchmark emits one cohort report per country.

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

Optional language code, such as en, tr or de. Omit to use country defaults. Do not force one language when comparing localizations.

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

Hard cap across all inputs and countries. A rank check or keyword seed is one result with nested data.

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

Filtered, deduplicated review limit. Public feeds may expose fewer; up to 10 pages are checked.

## `reviewSort` (type: `string`):

Most recent or most helpful reviews.

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

Include reviews at or above this rating.

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

Include reviews at or below this rating.

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

Optional ISO timestamp, for example 2026-09-01T00:00:00Z. Reviews without dates are excluded when filtering.

## Actor input object example

```json
{
  "apps": [
    "324684580"
  ],
  "countries": [
    "us"
  ],
  "maxItems": 100,
  "maxReviewsPerApp": 100,
  "reviewSort": "recent",
  "minRating": 1,
  "maxRating": 5
}
```

# Actor output Schema

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

No description

## `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 = {
    "apps": [
        "324684580"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("appalize/app-store-review-insights").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": ["324684580"] }

# Run the Actor and wait for it to finish
run = client.actor("appalize/app-store-review-insights").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": [
    "324684580"
  ]
}' |
apify call appalize/app-store-review-insights --silent --output-dataset

```

## MCP server setup

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

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/C8D9hCogECsNFkSx8/builds/VlYfyuzbzbgNrXKzZ/openapi.json