# Collect 1–2 star Google Play reviews of a competitor app

**Use case:** 

Collect the newest 1- and 2-star Google Play reviews of a competitor's app (example: Spotify) to find complaints, bugs and feature gaps. Reviewer names are left out by default.

## Input

```json
{
  "apps": [
    "com.spotify.music"
  ],
  "appsPerSearch": 5,
  "countries": [
    "us"
  ],
  "languages": [
    "en"
  ],
  "maxReviewsPerApp": 100,
  "sort": "newest",
  "minStars": 1,
  "maxStars": 2,
  "includeAppDetails": true,
  "includeReviewerNames": false
}
```

## Output

```json
{
  "appId": {
    "label": "App id"
  },
  "country": {
    "label": "Country"
  },
  "language": {
    "label": "Language"
  },
  "score": {
    "label": "Stars",
    "format": "number"
  },
  "content": {
    "label": "Content"
  },
  "thumbsUpCount": {
    "label": "Likes",
    "format": "number"
  },
  "appVersion": {
    "label": "App version"
  },
  "at": {
    "label": "Date",
    "format": "date"
  },
  "replyContent": {
    "label": "Reply content"
  },
  "repliedAt": {
    "label": "Replied at"
  },
  "reviewId": {
    "label": "Review id"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Google Play Reviews & App Data Scraper Actor is ready to run with the inputs already set for "Collect 1–2 star Google Play reviews of a competitor app". [Sign up or log in](https://console.apify.com/create-task-from-example/A3HBGjVkHr5yTk2Bg) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Collect 1–2 star Google Play reviews of a competitor app" task

The Google Play Reviews & App Data Scraper Actor will start running based on the input automatically. You can also change all the input fields, like apps, apps per search term, and more, to match your specific use case.

### 3. Receive the "Collect 1–2 star Google Play reviews of a competitor app" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as app id, country, language, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Collect 1–2 star Google Play reviews of a competitor app" task via API](https://apify.com/fjordlabs/google-play-reviews.md).

## FAQ

### What data does this task collect from Google Play reviews?

The task collects app ID, country, language, star rating, review content, likes, app version, review date, developer reply content, reply date, and review ID.

### What type of reviews does this task focus on?

The task specifically collects 1- and 2-star reviews of competitor apps to identify complaints and bugs.

### Can I use this task to monitor reviews over time?

Yes, the task supports incremental monitoring, allowing you to get only the newest reviews since a specified date.

### How can I run this task automatically?

You can schedule this task to run automatically in the Apify Console.

### Is reviewer identity collected by this task?

Reviewer names are excluded by default, making the task GDPR-friendly.

### What is the target app for this task?

The task is configured to collect reviews for the Spotify app, identified by its app ID 'com.spotify.music'.

### What input parameters are required for this task?

You only need the app ID (here com.spotify.music). The other settings, such as review count, sort order and star filter, are preset in this task and you can change them.

## About this Actor

This example demonstrates how to use [Google Play Reviews & App Data Scraper](https://apify.com/fjordlabs/google-play-reviews.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/fjordlabs/google-play-reviews.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/fjordlabs/google-play-reviews.md

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`).