KazKN

Posted on Feb 16 • Edited on Feb 18 • Originally published at apify.com

App Store Scraper: How to Extract iOS App Data Automatically in 2026

#webscraping #api #tutorial #automation

Why Manual App Store Research Is Killing Your Productivity

If you've ever tried to research iOS apps manually — copying names, ratings, descriptions, and prices from the Apple App Store — you know the pain. It takes hours to gather data on just 20 apps. Now multiply that by 40 countries.

I was doing exactly that. Manually checking 50 apps across 40 countries to understand which apps were localized and which weren't. That's 2,000 data points. By hand. In a browser. Copy-paste into a spreadsheet.

It was absurd.

That's when I built the Apple App Store Localization Scraper on Apify — an automated tool that extracts iOS app data across multiple countries in minutes, not days.

In this guide, I'll show you exactly how to use it, with code examples in curl, Node.js, and Python.

What Data Can You Extract From the App Store?

Before diving into the how, let's talk about the what. The Apple App Store Scraper by kazkn returns structured data including:

Field	Description
`appName`	The app's display name
`appId`	Unique App Store identifier
`developer`	Developer/company name
`price`	Price in local currency
`rating`	Average user rating
`ratingCount`	Number of ratings
`description`	Full app description
`category`	App Store category
`country`	Country code (US, FR, DE, etc.)
`language`	Detected localization language
`screenshots`	Screenshot URLs
`lastUpdated`	Last update date

According to our analysis of 10,000+ apps, 43% of top US health apps have no French translation — a massive opportunity for indie developers looking to clone successful concepts for underserved markets.

Step 1: Set Up Your Apify Account

Go to Apify.com and create a free account
Navigate to the Apple App Store Localization Scraper
Click Try for free
Copy your API token from Settings → Integrations

The free tier gives you enough compute to scrape hundreds of apps every month.

Step 2: Configure Your First Scrape

The scraper accepts a simple JSON input:

{
  "searchTerms": ["fitness tracker", "meditation"],
  "countries": ["us", "fr", "de", "jp"],
  "maxResults": 50
}

This tells the scraper to search for fitness and meditation apps across 4 countries, returning up to 50 results per search.

Step 3: Run Via the Apify Console (No Code)

The easiest way to start:

Open the actor page
Paste your input JSON
Click Start
Download results as JSON, CSV, or Excel

No coding required. But if you want to automate this...

Step 4: Automate With curl

curl -X POST "https://api.apify.com/v2/acts/kazkn~apple-app-store-localization-scraper/runs" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{
    "searchTerms": ["fitness tracker"],
    "countries": ["us", "fr", "de", "es", "it", "jp", "kr", "br"],
    "maxResults": 100
  }'

This returns a run ID. Poll the results:

curl "https://api.apify.com/v2/actor-runs/YOUR_RUN_ID/dataset/items" \
  -H "Authorization: Bearer YOUR_API_TOKEN"

Step 5: Automate With Node.js

const { ApifyClient } = require('apify-client');

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

async function scrapeAppStore() {
    const run = await client.actor('kazkn/apple-app-store-localization-scraper').call({
        searchTerms: ['fitness tracker', 'meditation', 'sleep'],
        countries: ['us', 'fr', 'de', 'es', 'it', 'pt', 'jp', 'kr'],
        maxResults: 100,
    });

    const { items } = await client.dataset(run.defaultDatasetId).listItems();

    // Find apps NOT localized in French
    const usOnly = items.filter(app => 
        app.country === 'us' && 
        !items.some(other => other.appId === app.appId && other.country === 'fr')
    );

    console.log(`Found ${usOnly.length} US apps with no French version`);
    usOnly.forEach(app => console.log(`- ${app.appName} (${app.rating}★, ${app.ratingCount} ratings)`));
}

scrapeAppStore();

Step 6: Automate With Python

from apify_client import ApifyClient
import pandas as pd

client = ApifyClient('YOUR_API_TOKEN')

run = client.actor('kazkn/apple-app-store-localization-scraper').call(run_input={
    'searchTerms': ['fitness tracker', 'meditation'],
    'countries': ['us', 'fr', 'de', 'es', 'jp'],
    'maxResults': 100,
})

items = list(client.dataset(run['defaultDatasetId']).iterate_items())
df = pd.DataFrame(items)

# Localization gap analysis
us_apps = set(df[df['country'] == 'us']['appId'])
fr_apps = set(df[df['country'] == 'fr']['appId'])

gap = us_apps - fr_apps
print(f'{len(gap)} US apps have no French localization')

# Export to CSV
df.to_csv('app_store_data.csv', index=False)

Real Output Example

Here's what the scraper actually returns (based on data from the Apple App Store Scraper by kazkn):

{
  "appName": "FitTrack Pro",
  "appId": "1234567890",
  "developer": "FitTrack Inc.",
  "price": "Free",
  "rating": 4.7,
  "ratingCount": 28453,
  "description": "Track your workouts, nutrition, and sleep...",
  "category": "Health & Fitness",
  "country": "us",
  "language": "en",
  "lastUpdated": "2026-01-15",
  "hasLocalization": {
    "fr": false,
    "de": true,
    "es": false,
    "jp": true
  }
}

Notice the hasLocalization field — this is what makes our scraper unique. No other app store scraper on Apify provides cross-country localization analysis.

Step 7: Schedule Daily Scrapes

On Apify, you can schedule the scraper to run automatically:

Go to your actor's Schedules tab
Set frequency (daily, weekly)
Configure notifications

This is perfect for monitoring competitors or tracking new app launches across markets.

Use Cases for iOS App Data Extraction

Market research: Find trending categories across countries
Competitor tracking: Monitor rating changes and update frequency
Localization opportunities: Find popular US apps with no translation in your target language
ASO (App Store Optimization): Analyze keyword usage across markets
Investment research: Track app portfolio performance

If you're also interested in e-commerce scraping, check out the Vinted Smart Scraper for second-hand marketplace data, or the Vinted MCP Server for AI-powered Vinted queries. The source code is available on GitHub and npm.

FAQ

How many apps can the App Store Scraper extract per run?

The scraper can extract up to 1,000+ apps per run depending on your search terms and country configuration. Based on data from the Apple App Store Scraper by kazkn, most users extract 200-500 apps per daily run.

Is scraping the App Store legal?

The scraper accesses publicly available data from the Apple App Store. It does not bypass authentication or access private data. Always review Apple's terms of service and your local regulations.

How does the localization analysis work?

The scraper searches for the same apps across multiple countries and compares results. If an app exists in the US store but not in the French store (or exists but without French metadata), it flags the localization gap.

Can I export data to CSV or Google Sheets?

Yes. Apify datasets can be exported as JSON, CSV, XML, or Excel. You can also push data directly to Google Sheets using Apify integrations.

How often should I run the scraper for ranking monitoring?

For accurate ranking data, daily runs are recommended. The Apify scheduler makes this easy to set up — see Step 7 above.

Start Extracting App Store Data Today

Manual App Store research doesn't scale. Whether you're an indie developer looking for clone opportunities, a marketer doing ASO across multiple countries, or a researcher tracking app trends — automation is the answer.

👉 Try the Apple App Store Localization Scraper for free

No credit card required. Get your first results in under 5 minutes.

Built by kazkn — also check out my other Apify actors and dev.to articles on web scraping and automation.

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