# Collect iOS App Reviews for Feature Request Research

**Use case:** 

Collect written iOS App Store reviews as source material for feature-request research. This Daylio example saves review titles, text, ratings, and dates. Export the dataset, then identify and group requests in your own analysis. The Actor does not label feature requests automatically.

## Input

```json
{
  "app": "1194023242",
  "country": "us",
  "maxReviews": 200,
  "scanLimit": 500
}
```

## Output

```json
{
  "reviewId": {
    "label": "Review id",
    "format": "string"
  },
  "appId": {
    "label": "App id",
    "format": "string"
  },
  "rating": {
    "label": "Rating",
    "format": "integer"
  },
  "title": {
    "label": "Title",
    "format": "string"
  },
  "text": {
    "label": "Text",
    "format": "string"
  },
  "date": {
    "label": "Date",
    "format": "string"
  },
  "reviewerName": {
    "label": "Reviewer name",
    "format": "string"
  },
  "isEdited": {
    "label": "Is edited",
    "format": "boolean"
  },
  "country": {
    "label": "Country",
    "format": "string"
  },
  "source": {
    "label": "Source",
    "format": "string"
  },
  "appUrl": {
    "label": "App",
    "format": "string"
  }
}
```

## How it works

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

The App Store Reviews Scraper \[FAST\] | iOS Ratings & Reviews Actor is ready to run with the inputs already set for "Collect iOS App Reviews for Feature Request Research". [Sign up or log in](https://console.apify.com/create-task-from-example/nTL5wggyimDoaYLrp) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Collect iOS App Reviews for Feature Request Research" task

The App Store Reviews Scraper \[FAST\] | iOS Ratings & Reviews Actor will start running based on the input automatically. You can also change all the input fields, like app store url or app id, store country, and more, to match your specific use case.

### 3. Receive the "Collect iOS App Reviews for Feature Request Research" 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 review id, app id, rating, 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 iOS App Reviews for Feature Request Research" task via API](https://apify.com/apizy/apple-app-store-reviews-scraper.md).

## About this Actor

This example demonstrates how to use [App Store Reviews Scraper [FAST] | iOS Ratings & Reviews](https://apify.com/apizy/apple-app-store-reviews-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/apizy/apple-app-store-reviews-scraper.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/apizy/apple-app-store-reviews-scraper.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`).