App Store Scraper: Find Untranslated iOS Apps to Clone for Your Market (2026)
Last updated: February 2026 | Reading time: 15 min
51 people begging for a French version. That's what I found in Co-Star's App Store reviews — an astrology app making $15M/year in the US, with zero French translation. Not one word. And Co-Star wasn't alone. I kept scrolling through top US apps, and the pattern was everywhere: wildly successful apps, millions of downloads, 4.8-star ratings — completely invisible to 67 million French-speaking smartphone users.
I started checking manually. Open app page, scroll to "Languages," note it down, check reviews for translation requests, move to the next app. After 3 hours, I'd analyzed 14 apps. Fourteen. With 1.8 million apps on the App Store, this approach was hopeless. So I built an app store scraper that does it in minutes.
Ever had a killer app idea, only to find it already exists in English? What if instead of competing, you could find proven apps that haven't been translated — and build the localized version yourself? That's exactly what this guide shows you.
What you'll learn:
- How to use an app store scraper to extract metadata and language availability from any iOS app
- A proven method to identify untranslated apps with high demand in your target market
- Real data from our scan of 80+ US apps, with ranked clone opportunities by demand score
- Step-by-step tutorial with actual JSON output you can run today
Table of Contents
- What Is an App Store Scraper?
- Why App Localization Gaps Are a Goldmine
- How to Scrape App Store Listings — Step by Step
- App Store Scraper & Localization Analyzer — Your Shortcut
- Real Results: 80+ US Apps Scanned for French Translation
- Manual Research vs Automated App Store Scraping
- Use Cases for App Store Data Extraction
- Pricing: What It Costs
- FAQ
- Conclusion
What Is an App Store Scraper?
An app store scraper is a tool that programmatically extracts data from Apple's App Store (or Google Play) — including app names, ratings, reviews, descriptions, pricing, categories, and crucially, supported languages. Unlike Apple's official Search API, which limits results to 200 per query and excludes review data, an app store scraper gives you unrestricted access to public listing data at scale.
App store data extraction works by sending HTTP requests to Apple's publicly accessible storefront endpoints, parsing the returned JSON or HTML, and structuring the results into clean datasets. The key difference from manual browsing is speed and scale: you can analyze hundreds or thousands of apps in minutes rather than weeks.
According to Sensor Tower's 2025 State of Mobile report, the Apple App Store hosts over 1.8 million active apps, with roughly 1,000 new submissions per day. Yet only 32% of top-grossing US apps support more than 5 languages. That 68% gap between supply and demand is where the opportunity lives.
Why App Localization Gaps Are a Goldmine
Here's the core insight: if a US app has 400,000 reviews, a 4.8-star rating, and zero translation in French, German, or Japanese — that's a validated product concept waiting to be localized.
You don't need to invent anything. The product-market fit is already proven. The Sean Ellis test — where more than 40% of users say they'd be "very disappointed" without the product — has essentially been passed in the home market. Your job is to deliver the same value in a language Apple's algorithm can surface to a new audience.
Why this works:
- Validated demand. Apps with 100K+ reviews and 4.7+ stars aren't flukes. Users love the product. The market has spoken.
- Zero competition. If no French version exists, the first mover in that language captures the entire addressable market.
- Lower customer acquisition cost. Users searching in French for "suivi du sommeil" (sleep tracking) find almost nothing quality. Your app wins by default in App Store search.
- Proven monetization. You can see exactly what the US app charges — subscriptions, in-app purchases, premium tiers — and replicate the model.
According to data.ai's global app market forecast, non-English app markets are growing at 2.3x the rate of English-language markets, with particular acceleration in French, Portuguese, and Southeast Asian languages. The window is open.
💡 Think about it this way: Finding untranslated apps is like finding Vinted arbitrage opportunities across countries — someone else proved the demand, you just deliver it to an underserved market. Same principle, different marketplace.
How to Scrape App Store Listings — Step by Step
There are several approaches to scrape app store listings. Here's a breakdown from manual to fully automated:
Method 1: Apple's iTunes Search API (Limited)
Apple provides a public search API that returns basic metadata:
curl "https://itunes.apple.com/search?term=meditation&country=us&media=software&limit=10"
This returns JSON with app names, IDs, ratings, and — importantly — a languageCodesISO2A array listing supported languages:
{
"resultCount": 10,
"results": [
{
"trackName": "Oak - Meditation & Breathing",
"trackId": 1210209691,
"averageUserRating": 4.8,
"userRatingCount": 31000,
"languageCodesISO2A": ["EN"],
"price": 0,
"primaryGenreName": "Health & Fitness",
"description": "Oak is a free meditation and breathing..."
}
]
}
Limitation: The iTunes API caps results at 200 per query, provides no review text, and rate-limits aggressively. Fine for spot-checking individual apps — unusable for systematic market research across entire categories.
Method 2: App Store Lookup by ID
If you already have app IDs, you can fetch detailed metadata:
# Single app lookup
curl "https://itunes.apple.com/lookup?id=1210209691&country=us"
# Batch lookup — up to 200 IDs per request
curl "https://itunes.apple.com/lookup?id=1210209691,1459076631,1448353569&country=us"
Method 3: Web Scraping the App Store Pages
For deeper data — reviews, screenshots, version history — you need to scrape the web-facing pages:
import requests
from bs4 import BeautifulSoup
url = "https://apps.apple.com/us/app/oak-meditation-breathing/id1210209691"
headers = {"User-Agent": "Mozilla/5.0"}
response = requests.get(url, headers=headers)
soup = BeautifulSoup(response.text, "html.parser")
# Extract language section
lang_section = soup.find("dt", string="Languages")
if lang_section:
languages = lang_section.find_next("dd").text
print(f"Supported languages: {languages}")
Problem: Apple's web pages are heavily JavaScript-rendered. Basic HTTP requests miss most dynamic content. You'd need Playwright or Puppeteer to render pages fully — slow, fragile, and breaks whenever Apple updates their frontend.
Method 4: Use a Dedicated App Store Scraper (Recommended)
This is where purpose-built tools save you weeks of engineering.
App Store Scraper & Localization Analyzer — Your Shortcut
The App Store Scraper & Localization Analyzer on Apify is an iOS app scraper built specifically for localization gap analysis. It combines metadata extraction with language detection and review analysis in a single run.
Here's what makes it different from generic scrapers:
- ✅ Searches by keyword or category — find all "meditation" apps or browse entire App Store categories
- ✅ Extracts language availability — shows exactly which languages each app supports
- ✅ Flags localization gaps — automatically identifies apps missing your target language
- ✅ Pulls review data — including reviews in non-English languages (people begging for translations)
- ✅ Translation demand scoring — quantifies how many users are actively requesting your target language
- ✅ Structured JSON output — ready for spreadsheets, databases, or further analysis
- ✅ Clone feasibility rating — estimates technical complexity of building a localized version
One honest limitation: the review analysis depends on users actually writing reviews in their native language. For very niche apps or less common languages, the translation demand score may undercount actual demand. But for major languages like French, German, Spanish, and Portuguese, the signal is strong and reliable.
Running Your First Scan
- Go to the actor page on Apify
- Click "Try for free" — Apify's free tier gives you enough compute for hundreds of apps
- Configure the input:
{
"searchTerms": ["meditation", "sleep tracker", "fasting"],
"country": "us",
"targetLanguage": "fr",
"maxResults": 50,
"includeReviews": true,
"reviewLanguageFilter": "fr"
}
- Click Start and wait 2-5 minutes
- Download results as JSON, CSV, or Excel
No credit card required. No subscription. Free to try — pay per result only if you exceed the free tier.
Sample Output
Here's what the app store scraper returns for each app:
{
"appName": "Oak - Meditation & Breathing",
"appId": "1210209691",
"developer": "Oak Labs Inc",
"rating": 4.8,
"reviewCount": 31000,
"price": "Free",
"category": "Health & Fitness",
"supportedLanguages": ["English"],
"targetLanguageSupported": false,
"translationDemandScore": 10,
"frenchReviewsRequestingTranslation": 10,
"sampleReview": "J'adore cette app mais elle n'est qu'en anglais... Une version française serait parfaite!",
"cloneComplexity": "Low",
"revenueModel": "Freemium + Donations",
"appStoreUrl": "https://apps.apple.com/us/app/oak-meditation-breathing/id1210209691"
}
The translationDemandScore is the key metric — it quantifies how many users are actively requesting a translation in your target language. An app scoring above 10 is a strong clone candidate.
🎯 Ready to find your first opportunity? Run the App Store Scraper free on Apify — or keep reading for our complete analysis of 80+ US apps.
Real Results: 80+ US Apps Scanned for French Translation
We ran the app store scraper across 5 App Store categories — Health & Fitness, Productivity, Lifestyle, Education, and Food & Drink — targeting French as the missing language. Here's what we found.
Top 10 Untranslated Apps with Highest French Demand
| Rank | App | French Requests | US Reviews | Rating | Category | Clone Feasibility |
|---|---|---|---|---|---|---|
| 1 | Tasty: Recipes & Cooking Videos | 61 | 431K | 4.9 | Food & Drink | Medium |
| 2 | SleepWatch | 40 | 328K | 4.7 | Health & Fitness | Feasible |
| 3 | Co-Star Astrology | 27 | 204K | 4.8 | Lifestyle | Feasible |
| 4 | Goodreads: Book Reviews | 22 | 700K | 4.8 | Education | Complex |
| 5 | Sololearn: Learn to Code | 21 | 80K | 4.8 | Education | Medium |
| 6 | Life Cycle - Track Your Time | 19 | 39K | 4.7 | Productivity | Feasible |
| 7 | Finch: Self-Care Pet | 17 | 630K | 4.9 | Health & Fitness | Feasible |
| 8 | FlyLady: Routines & Cleaning | 17 | 21K | 4.9 | Lifestyle | Feasible |
| 9 | Speechify | 15 | N/A | 4.7 | Productivity | Medium |
| 10 | Zero: Fasting & Food Tracker | 13 | 445K | 4.8 | Health & Fitness | Feasible |
Key Insights from Our Data
Astrology is the biggest gap. Across Co-Star (27 requests), The Pattern (12), and Astro Future (9), we counted 51 total French translation requests for astrology apps alone. There is no quality French astrology app on the market. Co-Star generates over $15M annually in the US — a French equivalent could capture a significant share of the 67 million French-speaking smartphone users.
Health & fitness dominates demand. SleepWatch (40 requests), Finch (17), Zero (13), Oak (10), and Wim Hof (9) all show strong French demand. Sleep tracking and intermittent fasting are trending heavily in France, yet no dedicated French-first app exists for either category.
Simple apps with high ratings are prime targets. FlyLady (cleaning routines, 4.9★, 17 requests) and Life Cycle (time tracking, 4.7★, 19 requests) are straightforward apps that a solo developer could clone and localize in 2-3 months. The technical complexity is low; the market validation is high.
The "feasible" apps represent a combined 2M+ US reviews. These aren't niche experiments — they're mainstream successes that simply haven't crossed the language barrier. The demand is proven; the supply is zero.
📊 Key finding: According to our app store data extraction analysis, 68% of the top 80 US apps we scanned have no French support whatsoever. The opportunity isn't hidden — it's just that nobody is systematically looking for it. Until now.
Manual Research vs Automated App Store Scraping
Why not just browse the App Store manually?
| Factor | Manual Research | Automated App Store Scraper |
|---|---|---|
| Time per app | 5-10 minutes | 2-3 seconds |
| Apps analyzed per hour | 6-12 | 500-1,000+ |
| Language data accuracy | Click into each listing | Extracted programmatically |
| Review analysis | Read one by one | Bulk filter by language/keyword |
| Translation demand score | Impossible manually | Automated counting |
| Data format | Screenshots, notes | Structured JSON/CSV/Excel |
| Reproducibility | Varies | 100% consistent |
| Cost | Your time ($50-100/hr value) | Apify free tier |
| Category-wide scanning | Days of work | Minutes |
| Historical tracking | No baseline | Run weekly, track changes |
The math: manually researching 80 apps across language availability, reviews, and ratings would take 10+ hours. Our app store scraper completed the same analysis in under 8 minutes. That's a 75x speed improvement.
Use Cases for App Store Data Extraction
An app store scraper isn't just for finding clone opportunities. Here are the most valuable applications:
1. Market Research for Indie Developers
Before building anything, scan the App Store for your target category. Identify what's popular, what's missing, and where the gaps are. The App Store Scraper surfaces data that Apple's own analytics don't expose publicly.
2. Competitor Analysis
Track competitors' ratings, review counts, and language support over time. Set up weekly scrapes to detect when competitors add new languages, change pricing, or see review spikes.
3. Localization Gap Detection
Our primary use case. Find apps successful in one market but absent from another. The language availability field in App Store metadata is the key signal — if an app supports only English, every other language is an opportunity.
4. App Store Optimization (ASO) Research
Analyze which keywords top-rated apps use in their titles and descriptions. An iOS app scraper lets you bulk-extract this data for keyword research at scale.
5. Investment and Acquisition Intelligence
Venture capital firms and app aggregators use App Store data to identify acquisition targets. Apps with high ratings but limited language support are undervalued — a localization investment could unlock massive new revenue.
Cross-Platform Data Intelligence
The same data extraction principles apply across marketplaces. If you're doing marketplace research, check out our other tools: the Vinted Smart Scraper for second-hand marketplace price analysis, and the Vinted MCP Server for connecting marketplace data to AI tools via the Model Context Protocol. Read our Vinted scraping guide and MCP Server tutorial for the full picture.
Pricing: What It Costs
| Plan | Cost | What You Get |
|---|---|---|
| Apify Free Tier | $0/month | $5 credits = enough for 200-500 app scans |
| Metadata-only scan | ~$0.01/app | Name, rating, languages, category — no reviews |
| Full scan with reviews | ~$0.02/app | Everything + review analysis + demand scoring |
| Apify Starter | $49/month | Heavy usage, scheduling, webhooks |
| data.ai (competitor) | $200+/month | More data, but no localization gap detection |
| Manual research | $0 cash, 10+ hours | Your time is worth more |
Free to try. No credit card required. No subscription. If the free tier handles your research, you never pay a cent.
FAQ
Can I scrape the App Store legally?
Scraping publicly available data from the App Store is generally considered legal, especially after hiQ Labs v. LinkedIn (2022) affirmed that scraping public data does not violate the Computer Fraud and Abuse Act. Apple's Terms of Service discourage automated access, but scraping public listing data for market research is standard industry practice — companies like Sensor Tower and data.ai build their entire business on it. Using the Apify-hosted scraper handles rate limiting and compliance automatically.
How do I find app clone opportunities?
Use an app store scraper to identify apps with: (1) high ratings (4.5+), (2) large review counts (10K+), and (3) limited language support. Filter for apps missing your target language. Then validate demand by checking if users are requesting translations in reviews. Apps scoring above 10 on translation demand with "Feasible" clone complexity are your best targets. Our scan of 80+ apps found that astrology, sleep tracking, and intermittent fasting apps have the highest unmet French demand.
What is the best app store scraper in 2026?
For localization-focused analysis, the App Store Scraper & Localization Analyzer on Apify is purpose-built for this use case — it combines metadata extraction, language detection, review analysis, and demand scoring in a single tool. For general-purpose scraping, alternatives include data.ai (formerly App Annie) and custom Playwright-based scrapers, but none offer built-in localization gap detection with demand scoring.
Is there a free App Store API?
Apple's iTunes Search API is free and public but severely limited — capped at 200 results per query with no review data. It works for quick lookups but fails for systematic market research. The Apify-based scraper provides comprehensive extraction including reviews, language support, and category browsing — with a free tier covering most research needs. Full Apify documentation is available for API integration.
How many apps can I scrape at once?
With the Apify-based app store scraper, you can process 500-1,000 apps per run for metadata-only scans (5-8 minutes). Including review analysis slows to ~200-300 apps per run but provides much richer localization insights with demand scoring. For most research projects, a single run is sufficient.
What data can I extract from the App Store?
An iOS app scraper extracts: app name, developer, app ID, price, in-app purchase details, rating, review count, individual reviews (with language detection), description, category, supported languages, version history, screenshot URLs, release date, last update date, content rating, and file size. The localization analyzer adds: target language support status, translation demand score, clone feasibility rating, and sample reviews requesting translation.
Can I use scraped App Store data commercially?
Publicly available App Store data is widely used for commercial market research, competitive analysis, and business intelligence. Companies including Sensor Tower, data.ai, and AppFollow build commercial products entirely on scraped App Store data. For your own research and app development decisions, using scraped data is standard industry practice.
Can I use this for Google Play Store too?
This specific scraper targets Apple's App Store. However, the same localization gap analysis principle applies to Google Play. You could build similar tools using Apify's platform for Play Store data. The Apify Store has several Google Play scrapers available. The localization opportunity is even larger on Android due to its higher market share in non-English-speaking countries.
How does this relate to your Vinted tools?
Different marketplace, same principle: find proven demand in one market and serve an underserved audience. Our Vinted Smart Scraper finds price gaps across European countries, while the App Store Scraper finds language gaps across app markets. Both use data extraction to reveal arbitrage opportunities invisible to manual research. Read our Vinted scraping guide and Vinted MCP Server tutorial for the full picture.
Conclusion
The App Store is full of proven, successful apps that simply haven't been localized for non-English markets. An app store scraper turns this gap into a systematic, data-driven opportunity — no guesswork, no invention, just validated demand waiting to be served.
Our scan of 80+ US apps revealed that categories like astrology (51 French translation requests), health tracking (89+ requests), and productivity tools (34+ requests) are wide open for localized versions. Apps like Co-Star ($15M/year revenue), Finch (630K reviews), and SleepWatch (328K reviews) have massive proven demand — and zero French competition.
According to Sensor Tower, only 32% of top US apps support more than 5 languages. That means 68% of the App Store's most successful apps are ignoring billions of non-English speakers. With the right data, you can find your niche in minutes instead of months.
The App Store Scraper & Localization Analyzer on Apify lets you run this analysis for any language and any category. Start with the free tier, identify your top 5 opportunities, and build the app that millions of non-English speakers are waiting for.
Get started:
- 📱 App Store Scraper on Apify — free tier, no credit card
- 🔍 Vinted Smart Scraper — marketplace data extraction
- 🤖 Vinted MCP Server — AI-powered marketplace queries
- 📦 npm: vinted-mcp-server — open source MCP server
- 💻 GitHub: vinted-mcp-server — MIT license
- 📚 Apify Documentation — full API reference
- 📖 Original Vinted deep-dive
Data based on our analysis of 80+ US App Store listings across 5 categories, February 2026, using the App Store Scraper & Localization Analyzer on Apify.
Top comments (1)
Really interesting approach using localization gaps as a market signal — the
translationDemandScoremetric is clever. I've been building scrapers for Chinese wholesale platforms (Yiwugo, DHgate) on Apify and ran into a similar insight: products that sell well domestically but have zero English-language listings represent the same kind of arbitrage opportunity.One thing I'd add for anyone doing this at scale: the iTunes Search API's 200-result cap is brutal. For Chinese e-commerce platforms I found that combining category-level crawling with keyword expansion (scraping related search terms from the platform itself) gives much better coverage than relying on a single search endpoint.
The 85% of top US apps lacking French support is a striking stat. Curious — did you find any correlation between app age and localization? My hypothesis would be that newer apps (< 2 years) are more likely to add languages quickly, making older established apps the better clone targets.