# App Store Reviews Analysis - Complaints, Bugs & Bad Updates (`centorprat/app-review-problem-scanner`) Actor

Give it app names or App Store ids. Each is scanned from recent App Store reviews into a problem brief: the issue themes users report (crashes, login, update-broke, billing, bugs...), the version where complaints spiked, recent-vs-lifetime rating, and sample complaints. Keyless, agent-callable.

- **URL**: https://apify.com/centorprat/app-review-problem-scanner.md
- **Developed by:** [Centor Prat](https://apify.com/centorprat) (community)
- **Categories:** Developer tools, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $17.00 / 1,000 app scanneds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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 Reviews Analysis: Complaints, Bugs & Bad Updates

**Point it at an app and find out what's actually broken — from the people who use it.** Give it an app
name or App Store id; it pulls the most recent App Store reviews and composes a **problem brief**: the
issue themes users are reporting (crashes, login, update-broke, billing, performance, bugs…), the app
**version where complaints spiked**, the **recent rating vs the lifetime rating**, and sample complaints.
Keyless, agent-callable, built to answer *"what are users complaining about in this app right now?"*

> 📊 **A signal, not a verdict.** It summarizes public App Store reviews (a recent sample) — what users
> are reporting, not a verified or complete defect list. Review volume and ratings reflect who chose to
> review.

### ⚡ Why it's different

A store's **lifetime star rating hides current problems.** This surfaces them: it contrasts the recent
reviews against the all-time average, buckets the complaints into issue themes, and pinpoints the version
where things got worse — the answer, not a dump of raw reviews.

### 📋 What each brief contains

| Field | Meaning |
|---|---|
| `signal` | `recent-regression--investigate` / `high-recent-complaint-rate` / `some-recent-complaints` / `recently-healthy` |
| `recentVsOverall` | Lifetime rating vs recent average, and the drop |
| `problemReviewRate` | % of recent reviews that are ≤2★ or mention a problem |
| `topIssues` | Issue themes with counts (crash_freeze, login_auth, update_broke, billing_subscription, performance_slow, bugs_errors, account_data, notifications, ads, ui_ux) |
| `worstVersion` | The app version with the lowest recent average rating |
| `byVersion` | Per-version review count, average rating, negatives |
| `sampleProblemReviews` | Recent low-star reviews with their version and matched issues |
| `overallRating` / `totalRatings` | Lifetime App Store rating and rating count |

### 📥 Input

```json
{ "apps": ["McDonald's", "Bank of America", "324684580"], "country": "us", "maxReviews": 200 }
```

One brief per app. A name resolves to the closest App Store match; a numeric id is used directly.

### 📤 Example output (real run, trimmed — McDonald's, US)

```json
{
  "appName": "McDonald's", "overallRating": 4.84, "totalRatings": 7883319,
  "reviewsAnalyzed": 200, "avgRatingRecent": 1.75,
  "signal": "recent-regression--investigate",
  "recentVsOverall": { "overallRating": 4.84, "recentAvgRating": 1.75, "drop": 3.09 },
  "problemReviewRate": 86,
  "topIssues": [ {"issue": "login_auth", "count": 59}, {"issue": "bugs_errors", "count": 57} ],
  "worstVersion": { "version": "26.72.5", "reviews": 200, "avgRating": 1.75, "negativeReviews": 156 },
  "sampleProblemReviews": [ {"rating": 1, "version": "26.72.5", "title": "Update broke my app.",
    "body": "Ever since the new update released I have been unable to sign in to my account...", "issues": ["login_auth","update_broke"]} ]
}
```

A 4.84-star app whose **recent** reviews average **1.75** — a sign-in regression the lifetime rating
completely hides.

### 💰 Pricing (pay-per-event)

- **App scanned — $0.02** per app for which the brief is produced. Apps that don't resolve are free.

### 💡 Use cases

- **Product / QA / engineering:** catch a bad release and the exact version + issue, fast.
- **Competitive & market analysts / investors:** app health as a live signal for any company's app.
- **Agencies / consultants:** walk into a pitch knowing exactly what a prospect's app users are complaining about.
- **Support / ops:** see the complaint themes spiking this week.

### 🔑 Keyless & agent-callable

No API keys, no accounts, no paid child Actors — just the public Apple App Store search + reviews feeds.

### 🤖 For AI agents / MCP

```
https://mcp.apify.com/?tools=actors,docs,centorprat/app-review-problem-scanner
```

Loads as `centorprat--app-review-problem-scanner`. Claude Code:

```
claude mcp add apify -- npx -y @apify/actors-mcp-server --actors centorprat/app-review-problem-scanner
```

### ❓ FAQ

**Do I need an API key or an Apple account?** No. It uses Apple's public App Store search and customer-reviews feeds.

**Which reviews are analysed?** The most recent ones for the country you pick (Apple serves up to ~500, newest first). It compares them with the app's lifetime rating, so a bad release shows up even when the star rating still looks great.

**Google Play?** Not yet. This Actor covers the Apple App Store.

**Can I compare competitors?** Yes. Put several apps in `apps`; each gets its own brief, so issue themes and recent ratings line up side by side.

**Can I monitor an app?** Schedule it daily or weekly with a `webhookUrl`. A `recent-regression--investigate` signal is your alert that a release went wrong.

**Personal data?** Reviewer names aren't output. Only ratings, versions, review titles and text are used.

**Cost?** $0.02 per app with a brief. Apps that don't resolve are free. No paid child Actors.

# Actor input Schema

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

Apps to scan, e.g. \["McDonald's"], \["Bank of America", "324684580"]. A name resolves to the closest App Store match; a numeric id is used directly. One brief per app.

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

Two-letter App Store country code for the app lookup and reviews (e.g. us, gb, de, fr, jp).

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

Apple serves the most recent reviews in pages of 50 (up to ~500).

## `webhookUrl` (type: `string`):

If set, the briefs are POSTed here as JSON when the run finishes.

## Actor input object example

```json
{
  "apps": [
    "McDonald's"
  ],
  "country": "us",
  "maxReviews": 200
}
```

# Actor output Schema

## `briefs` (type: `string`):

One brief per app: app meta (name, seller, lifetime rating and total ratings), reviews analyzed, recent average vs lifetime rating with the drop, a signal, rating distribution, the problem-review rate, top issue themes with counts, the app version where complaints spiked, per-version breakdown, and sample problem reviews. Based on public App Store reviews.

# 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": [
        "McDonald's"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("centorprat/app-review-problem-scanner").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": ["McDonald's"] }

# Run the Actor and wait for it to finish
run = client.actor("centorprat/app-review-problem-scanner").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": [
    "McDonald'\''s"
  ]
}' |
apify call centorprat/app-review-problem-scanner --silent --output-dataset

```

## MCP server setup

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

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/YUfsbNdNvCTBVHgg4/builds/ilUk0OR8AlgeW8UtC/openapi.json