Apple App Store Review Intelligence

Analyze public Apple App Store customer reviews for one app and receive normalized review records plus an aggregate intelligence report.

What it returns

The default dataset contains one record per public review with the app ID, storefront, rating, title, text, author display name, app version, timestamps, and Apple review URL. The OUTPUT and SUMMARY key-value records contain:

• rating distribution and average collected rating;
• lightweight positive/neutral/negative sentiment signals;
• ranked themes such as performance, login, pricing, notifications, usability, and features;
• representative positive and negative review excerpts;
• app metadata returned by Apple's lookup endpoint.

Example input:

{"appIdOrUrl":"310633997","country":"us","sortBy":"mostrecent","maxReviews":50}

Use appIdOrUrl for a precise match. appName can be used for an Apple search when the numeric ID is unknown. country is a two-letter storefront code such as us, gb, or ca.

Pricing

Event	Price	Value
Actor start	$0.00005	One run start
Review intelligence report	$0.02	One delivered aggregate report

Review rows are delivered in the dataset and are not charged as separate report events. Actual platform billing is governed by the live private Actor configuration.

Reliability and limitations

The Actor uses Apple's publicly accessible App Store review page and a bounded RSS fallback. It does not log in, bypass a challenge, or fabricate reviews. Apple exposes a bounded public feed, so the result may contain fewer reviews than requested. If the storefront has no public reviews, the Actor returns an empty report with zero dataset records. Sentiment and themes are transparent lexical signals rather than human- or model-validated classifications.

Review text and public author display names may be personal data. Use the output only for a lawful product-research purpose, respect Apple's terms and applicable privacy rules, and avoid republishing review text without the necessary rights.

Use cases

• Schedule repeatable collection and export results to downstream workflows.
• Run a one-off research job and export the structured result as JSON, CSV, Excel, XML, or RSS from Apify.
• Schedule the same input to monitor changes over time and send completed datasets to a webhook or integration.
• Feed schema-shaped records into a database, spreadsheet, BI tool, or AI workflow with the source URL retained for verification.

Input

Field	Type	Description
appIdOrUrl	string	Use a numeric Apple App Store ID or an App Store URL when you know the exact app. Example: 310633997 or https://apps.apple.com/us/app/whatsapp-messenger/id310633997.
appName	string	Use an exact or distinctive app name when an App Store ID is unavailable. Example: WhatsApp Messenger. App ID takes precedence when both are provided.
country	string	Two-letter Apple storefront code used for lookup and reviews. Example: us. Defaults to us.
sortBy	string	Choose mostrecent for current feedback or mosthelpful for reviews ranked by Apple. Defaults to mostrecent.
maxReviews	integer	Maximum public reviews to collect and analyze. Use 1–500; defaults to 50. The Apple RSS feed is bounded and may return fewer reviews.
maxPages	integer	Maximum legacy Apple RSS fallback pages to request when the App Store review page has no embedded reviews. Use 1–10; defaults to 1.
includeReviewText	boolean	Keep review title and body in dataset records and excerpts, or set false to omit bodies from the dataset. Defaults to true.

Output example

{
  "reviewId": "1234567890",
  "appId": "310633997",
  "appName": "WhatsApp Messenger",
  "country": "us",
  "rating": 4,
  "title": "Very useful",
  "content": "The latest update is much faster.",
  "author": "App Store User",
  "version": "24.12",
  "updatedAt": "2025-01-10T12:00:00Z",
  "reviewUrl": "https://itunes.apple.com/review?id=1234567890",
  "scrapedAt": "2026-08-14T12:00:00Z"
}

The exact fields depend on the selected input and what the public source exposes. Use the dataset schema as the machine-readable contract and retain source URLs for verification.

Run Apple App Store Review Intelligence with the Apify API

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('muhammadafzal/apple-app-store-review-intelligence').call({
  "appIdOrUrl": "310633997",
  "appName": "WhatsApp Messenger",
  "country": "us",
  "sortBy": "mostrecent",
  "maxReviews": 50,
  "maxPages": 1,
  "includeReviewText": true
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

You can also run the Actor from Apify Console, schedules, webhooks, the REST API, Make, Zapier, n8n, or the hosted Apify MCP server.