# App Store Complaint Miner (`kvko/app-store-complaint-miner`) Actor

Find what users hate about competing iOS apps. Input: 1-5 App Store app IDs. Output: complaint clusters with frequency, severity, missing features and switching signals. For founders and PMs who want competitor weakness analysis without reading hundreds of reviews.

- **URL**: https://apify.com/kvko/app-store-complaint-miner.md
- **Developed by:** [KVKO](https://apify.com/kvko) (community)
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $990.00 / 1,000 app analyzeds

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 Complaint Miner

Apify Actor that finds what users **hate** about competing iOS apps. Point it at 1-5
App Store app IDs and it returns complaint clusters with frequency, severity,
missing features, and competitor-switching signals — mined from public customer
reviews and clustered by a Groq LLM.

Owner repo: KVKO-Lab/DOCKER-MSaaS · products/app-store-complaint-miner

### How it works

1. **Resolve** each numeric App Store app ID via the iTunes Lookup API → real app name.
2. **Collect** recent customer reviews via Apple's public RSS feed
   (`itunes.apple.com/{country}/rss/customerreviews/...`, up to 500 per app).
3. **Cluster** the review text with a Groq LLM (`qwen/qwen3.8-27b` by default)
   into complaint themes, each tagged with frequency + severity, plus missing features
   and switching signals — with verbatim quotes as evidence.
4. **Emit** per-app analysis records, plus a combined `report`/`OUTPUT` record.

### Input

| Field | Type | Default | Notes |
|-------|------|---------|-------|
| `apps` | array (stringList) | — | 1-5 numeric App Store app IDs (**required**) |
| `country` | string | `us` | Two-letter App Store country code |
| `maxReviewsPerApp` | integer | `500` | 50-500 (Apple RSS cap) |
| `minComplaintFrequency` | integer | `2` | Min reviews supporting a complaint cluster |
| `llmApiKey` | string (secret) | env `GROQ_API_KEY` | Groq key from console.groq.com |
| `llmModel` | string | `qwen/qwen3.8-27b` | Groq chat model |

### Output

Three kinds of records pushed to the dataset:

- `{ kind: "app-reviews", ... }` — raw fetched reviews per app.
- `{ kind: "app-analysis", ... }` — per-app `summary`, `complaints[]`
  (title/frequency/severity/quotes), `missingFeatures[]`, `switchingSignals[]`.
- `{ kind: "report", ... }` — full aggregate; also stored in the default
  Key-Value store as `OUTPUT`.

### Development

```bash
npm install
npm run type-check   # tsc --noEmit
npm run build        # tsc -> dist
npm start            # node dist/main.js (needs a default local input)
```

Local run needs an Apify input — create `.actor/INPUT.json` (see Apify CLI docs) or
set `APIFY_LOCAL_STORAGE_DIR` and the standard storage layout.

### Stack

TypeScript, `apify` SDK, OpenAI-compatible Groq client. No browser needed.
Base image: `apify/actor-node:22`.

# Actor input Schema

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

Array of numeric App Store app IDs (1-5 apps)

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

App Store country code

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

Maximum reviews to fetch per app (Apple RSS limit: 500)

## `minComplaintFrequency` (type: `integer`):

Minimum number of reviews supporting a complaint cluster

## `llmModel` (type: `string`):

Groq chat model used for complaint clustering

## Actor input object example

```json
{
  "country": "us",
  "maxReviewsPerApp": 500,
  "minComplaintFrequency": 2,
  "llmModel": "qwen/qwen3.8-27b"
}
```

# Actor output Schema

## `report` (type: `string`):

Full JSON report with complaint clusters, frequency, severity, missing features and switching signals per app.

# 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("kvko/app-store-complaint-miner").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("kvko/app-store-complaint-miner").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 kvko/app-store-complaint-miner --silent --output-dataset

```

## MCP server setup

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

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/EIojWHjeaRRyH98rc/builds/ATPnQAO3jyTFo37w6/openapi.json