# Language-learning app landscape: 5 apps, review intelligence

**Use case:** 

Duolingo, Babbel and Memrise across Google Play and the App Store (US and UK) compared in one report: relative sentiment, shared vs unique complaints and themes, and an overall ranking. Replace the apps with your own market.

## Input

```json
{
  "targets": [
    {
      "app_id": "com.duolingo",
      "store": "google_play",
      "country": "us",
      "company_label": "Duolingo"
    },
    {
      "app_id": "com.babbel.mobile.android.en",
      "store": "google_play",
      "country": "us",
      "company_label": "Babbel"
    },
    {
      "app_id": "570060128",
      "store": "apple",
      "country": "us",
      "company_label": "Duolingo (iOS)"
    },
    {
      "app_id": "829587759",
      "store": "apple",
      "country": "us",
      "company_label": "Babbel (iOS)"
    },
    {
      "app_id": "635966718",
      "store": "apple",
      "country": "gb",
      "company_label": "Memrise (UK)"
    }
  ],
  "max_reviews": 50,
  "max_themes": 15,
  "proxy_configuration": {
    "useApifyProxy": true
  }
}
```

## Output

```json
{
  "record_type": {
    "label": "Record type",
    "format": "string"
  },
  "report_id": {
    "label": "Report id",
    "format": "string"
  },
  "app_count": {
    "label": "App count",
    "format": "number"
  },
  "total_reviews": {
    "label": "Total reviews",
    "format": "number"
  },
  "app_id": {
    "label": "App id",
    "format": "string"
  },
  "store": {
    "label": "Store",
    "format": "string"
  },
  "company_label": {
    "label": "Company label",
    "format": "string"
  },
  "review_count": {
    "label": "Review count",
    "format": "number"
  },
  "sentiment_positive_pct": {
    "label": "Sentiment positive pct",
    "format": "number"
  },
  "sentiment_negative_pct": {
    "label": "Sentiment negative pct",
    "format": "number"
  },
  "average_sentiment_score": {
    "label": "Average sentiment score",
    "format": "number"
  },
  "average_rating": {
    "label": "Average rating",
    "format": "number"
  },
  "relative_sentiment": {
    "label": "Relative sentiment",
    "format": "array"
  },
  "winner_by_dimension": {
    "label": "Winner by dimension",
    "format": "object"
  },
  "overall_ranking": {
    "label": "Overall ranking",
    "format": "array"
  },
  "shared_vs_unique_themes": {
    "label": "Shared vs unique themes",
    "format": "object"
  },
  "shared_vs_unique_complaints": {
    "label": "Shared vs unique complaints",
    "format": "object"
  },
  "themes": {
    "label": "Themes",
    "format": "array"
  },
  "complaint_ranking": {
    "label": "Complaint ranking",
    "format": "array"
  },
  "feature_requests": {
    "label": "Feature requests",
    "format": "object"
  },
  "report_markdown": {
    "label": "Report markdown",
    "format": "string"
  },
  "report_kv_key": {
    "label": "Report kv key",
    "format": "string"
  },
  "method": {
    "label": "Method",
    "format": "string"
  },
  "model": {
    "label": "Model",
    "format": "string"
  },
  "generated_at": {
    "label": "Generated at",
    "format": "string"
  },
  "partial": {
    "label": "Partial",
    "format": "boolean"
  }
}
```

## How it works

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

The App Review Competitive Report — Head-to-Head Comparison Actor is ready to run with the inputs already set for "Language-learning app landscape: 5 apps, review intelligence". [Sign up or log in](https://console.apify.com/create-task-from-example/valuOfClbzUa0TFF4) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Language-learning app landscape: 5 apps, review intelligence" task

The App Review Competitive Report — Head-to-Head Comparison Actor will start running based on the input automatically. You can also change all the input fields, like apps to compare (2 to 5), maximum reviews per app, and more, to match your specific use case.

### 3. Receive the "Language-learning app landscape: 5 apps, review intelligence" 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 record type, report id, app count, 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 "Language-learning app landscape: 5 apps, review intelligence" task via API](https://apify.com/nexgenwatch/app-review-competitive-report.md).

## About this Actor

This example demonstrates how to use [App Review Competitive Report — Head-to-Head Comparison](https://apify.com/nexgenwatch/app-review-competitive-report.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/nexgenwatch/app-review-competitive-report.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/nexgenwatch/app-review-competitive-report.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`).