# App Store Reviews Scraper - Search by Keyword (`conversational_kermis/pulse-appstore`) Actor

Search the Apple App Store by keyword and export the reviews of matching apps: rating, title, body, author, app name and ID. Apple offers no public export and shows reviews a few at a time; this does the searching and paging for you.

- **URL**: https://apify.com/conversational\_kermis/pulse-appstore.md
- **Developed by:** [the anh nguyen](https://apify.com/conversational_kermis) (community)
- **Categories:** Business, Developer tools, Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## 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 Reviews Scraper

Search the Apple App Store by keyword and get the reviews of the matching apps
as structured rows — rating, title, body, author and app identity.

Apple shows reviews a handful at a time behind a "more" control and offers no
public export. This Actor does the searching and paging for you and hands back a
table.

### Input

| Field | Default | What it does |
|---|---|---|
| `searchTerms` | a sample list | Keywords to search the store with; each is searched separately |
| `maxAppsPerTerm` | `10` | How many matching apps to take per keyword |
| `maxReviewsPerApp` | `20` | How many reviews to pull from each app |

```json
{ "searchTerms": ["invoice app", "booking system"], "maxAppsPerTerm": 5, "maxReviewsPerApp": 20 }
```

Total rows are roughly `terms × maxAppsPerTerm × maxReviewsPerApp`, so raise the
multipliers deliberately.

### Output

One row per review:

| Field | Type | Example |
|---|---|---|
| `appId` | integer | `1240314505` |
| `appName` | string | `Groomit On-Demand Grooming` |
| `url` | string | `https://apps.apple.com/app/id1240314505` |
| `reviewId` | integer | `14370393171` |
| `reviewTitle` | string | `Owner of Funny Farm Rescue` |
| `text` | string | the review body |
| `rating` | integer | `1`–`5` |
| `score` | integer | same as `rating`, kept for cross-source sorting |
| `author` | string | reviewer's public display name |
| `title` | string | `[5★] Owner of Funny Farm Rescue` — rating-prefixed for scanning |
| `date` | string | ISO 8601 |
| `extra_searchTerm` | string | which keyword produced this row |
| `scrapedAt` | string | ISO 8601 timestamp of capture |

### What it is good for

- **Competitor research** — the one- and two-star reviews of the apps in your
  category are a list of things people want and are not getting.
- **Feature demand** — repeated wording across unrelated apps is a stronger
  signal than any single review.
- **Positioning** — the words customers use for the problem are the words to
  use back at them.

Sort by `rating` ascending and read the bottom first; that is where the
information is.

### Notes and limits

- Reviews come from Apple's public RSS feed per app, which returns recent
  reviews rather than the complete history. Treat a run as a current sample.
- Coverage is the store Apple serves this client; results can differ by
  storefront and over time.
- `author` is the reviewer's **public display name**, published by Apple
  alongside the review. No e-mail addresses, account identifiers or private
  profile data are collected. If you process these rows in the EU, remember a
  display name can still be personal data and treat the file accordingly.

# Actor input Schema

## `searchTerms` (type: `array`):

Terms to search for apps on the iTunes Store.

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

Maximum number of reviews to fetch per app.

## `maxAppsPerTerm` (type: `integer`):

Maximum number of apps to fetch reviews from per search term.

## Actor input object example

```json
{
  "searchTerms": [
    "pet grooming",
    "wedding planner",
    "restaurant inventory",
    "freelance invoicing",
    "small business scheduling",
    "booking app",
    "appointment scheduler"
  ],
  "maxReviewsPerApp": 20,
  "maxAppsPerTerm": 10
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

# 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("conversational_kermis/pulse-appstore").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("conversational_kermis/pulse-appstore").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 conversational_kermis/pulse-appstore --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,conversational_kermis/pulse-appstore"
        }
    }
}

```

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/VgWVX1DcbkCY9MPHU/builds/za7rRDYzYWvIc0gpU/openapi.json