Apple App Store Reviews Scraper — Ratings, Dates, Versions & Helpful Votes

Extract every Apple App Store review for any iOS app in seconds. This App Store reviews scraper pulls star ratings, review text, author names, app versions, helpful votes, and full app metadata — all structured and ready to use, with no coding required.

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Why Use This App Store Reviews Scraper?

• 25,000+ reviews per minute — one of the fastest App Store review extractors available on Apify
• No browser, no proxy, no API key required — fully anonymous, zero setup, zero maintenance
• 50+ App Store countries supported — pull localized reviews from the US, UK, Germany, Japan, Brazil, and dozens more storefronts
• Two sort modes — Most Recent for fresh sentiment tracking, Most Helpful for the reviews users actually read
• Date filtering built in — only fetch reviews since a given date, perfect for daily or weekly monitoring runs
• App metadata on every review — app name, developer, overall rating, rating count, and category are attached to each individual review row, so you never need a second scraper for context
• Multi-app, multi-country parallel processing — feed in dozens of App Store IDs and countries in a single run and get everything back at once
• Lightweight and reliable — runs on minimal compute with no browser overhead, so runs finish fast and don't get flagged or blocked

Whether you're tracking iOS app ratings, monitoring App Store reviews for a client, or building a sentiment analysis pipeline, this scraper gets you clean review data without the usual scraping headaches.

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What Data Do You Get?

Every review comes back with 20 fields covering the review itself, the reviewer, and the parent app — so a single dataset gives you everything needed for App Store review analysis.

Field	Description
reviewId	Unique identifier for the review
title	Review headline written by the user
text	Full review body text
rating	Star rating from 1 to 5
author	Reviewer's display name
authorUrl	Link to the reviewer's App Store profile
date	Review submission date and time (ISO 8601, with timezone)
appVersion	App version the review was written against
helpfulVotes	Number of users who marked the review as helpful
totalVotes	Total number of helpfulness votes cast
appId	The App Store numeric ID for the app
appName	App name
appDeveloper	Publisher / developer name
appRating	App's current overall average rating
appRatingCount	Total number of ratings the app has received
appCategory	Primary App Store category
country	App Store storefront the review was pulled from
sortBy	Sort order used for this run (mostrecent or mosthelpful)
scrapedAt	Timestamp of when the data was collected
status	Result status for the review row

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Input Parameters

{
  "appIds": ["https://apps.apple.com/us/app/whatsapp-messenger/id310633997"],
  "countries": ["us"],
  "sortBy": "mostrecent",
  "maxReviews": 500
}

Parameter	Type	Required	Default	Description
appIds	array	Yes	—	App Store numeric IDs or full App Store URLs. IDs are extracted automatically from URLs, so you can paste either.
countries	array	No	["us"]	App Store country codes to pull reviews from (e.g. us, gb, de, jp, br). Add multiple to get localized reviews from several storefronts in one run.
sortBy	string	No	mostrecent	Review sort order: mostrecent or mosthelpful.
maxReviews	integer	No	500	Maximum reviews to return per app per country.
sinceDate	string	No	—	Only include reviews on or after this date. Format: YYYY-MM-DD.

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Sample Output

{
  "reviewId": "14249474782",
  "title": "Amazing app",
  "text": "WhatsApp is used worldwide...",
  "rating": 5,
  "author": "M Ohanlon",
  "authorUrl": "https://itunes.apple.com/us/reviews/id559572394",
  "date": "2026-07-01T10:15:02-07:00",
  "appVersion": "26.25.74",
  "helpfulVotes": 0,
  "totalVotes": 0,
  "appId": "310633997",
  "appName": "WhatsApp Messenger",
  "appDeveloper": "WhatsApp Inc.",
  "appRating": 4.69,
  "appRatingCount": 18177792,
  "appCategory": "Social Networking",
  "country": "us",
  "sortBy": "mostrecent",
  "scrapedAt": "2026-07-02T20:30:00Z",
  "status": "ok"
}

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How Fast Is It?

Scenario	Reviews	Time
Single app, one country	500	~5 seconds
Small batch (5 apps)	2,500	~8 seconds
Medium batch (20 apps)	10,000	~15 seconds
Large batch	5,000	~5 seconds
Bulk run, multiple countries	25,000+	~1 minute

Since there's no browser to launch and no proxy round-trips to wait on, this App Store reviews scraper spends its time doing exactly one thing — fetching review data — which is why throughput stays consistently fast across small and large runs alike.

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Use Cases

App Store Optimization (ASO) & Review Monitoring

• Track star rating trends over time by running the scraper on a schedule and comparing appRating and appRatingCount across runs
• Monitor new reviews daily using sinceDate to only pull what's changed since your last check
• Benchmark against competitor apps by scraping reviews for multiple App Store IDs in the same category
• Feed ASO tools and dashboards with clean, structured review data instead of manually copying reviews

Customer Feedback & Product Analytics

• Surface recurring complaints and feature requests by running review text through keyword or topic extraction
• Prioritize bug fixes by filtering the most helpful negative reviews (sortBy: mosthelpful) mentioning specific app versions
• Track sentiment by app version using the appVersion field to see if a release improved or hurt user sentiment
• Build a customer voice repository for product and support teams without needing App Store Connect access

Market Research & Competitive Intelligence

• Compare rating distribution across competitors in the same category using appCategory and appRating
• Identify market gaps by analyzing what users complain about across multiple apps in a niche
• Localize your understanding of user sentiment by pulling reviews from multiple countries in a single run
• Support due diligence and market entry research with structured review datasets ready for spreadsheets or BI tools

AI, NLP & Machine Learning

• Build sentiment analysis training sets from millions of labeled star ratings paired with review text
• Fine-tune LLMs on real customer feedback using the text and rating fields as input-output pairs
• Train review summarization models using helpful-vote-ranked reviews as ground truth for "most useful feedback"
• Power AI-driven customer support tools by classifying incoming reviews using patterns learned from historical data

Marketing & PR

• Find quotable customer testimonials by filtering high-rating, high-helpful-vote reviews
• Track brand sentiment after a major release by monitoring reviews in the days following an update
• Identify influential reviewers whose reviews consistently receive high helpful vote counts

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Frequently Asked Questions

How do I scrape App Store reviews without coding? Just provide the App Store app ID or app URL as input and run the actor. No code, API key, or technical setup is required — the scraper handles everything and returns structured review data directly to your dataset.

Can I get reviews from multiple countries in one run? Yes. Add multiple country codes to the countries array (e.g. ["us", "gb", "de"]) and the scraper returns localized reviews from each App Store storefront for every app you specify.

What's the difference between Most Recent and Most Helpful sorting? mostrecent returns the newest reviews first, ideal for daily monitoring and catching fresh complaints or praise. mosthelpful returns reviews with the most helpful votes first, which tend to be the most detailed and representative of common user opinions.

How many reviews can I scrape per app? Apple's App Store exposes up to 500 reviews per app per country through the review pages this scraper reads. Set maxReviews up to that limit, or run once per country to gather more total reviews across storefronts.

Can I filter reviews by date? Yes. Use the sinceDate parameter with a YYYY-MM-DD date to only receive reviews submitted on or after that day — useful for incremental daily or weekly monitoring without re-processing old reviews.

Does the output include the app's overall rating, or just individual review ratings? Both. Each review row includes its own rating (1-5 stars for that specific review) plus the app-level appRating and appRatingCount, so you get individual and aggregate sentiment in the same dataset.

Do I need an App Store Connect account or Apple Developer credentials? No. This scraper works entirely from publicly available App Store review pages. You don't need to own the app, have developer access, or authenticate with Apple in any way.

Is a proxy needed to scrape App Store reviews? No. This scraper runs without any proxy configuration and without a browser. It's built to be lightweight and fast by design, not because it's cutting corners — it simply doesn't need either to reliably pull review data.

Can I track reviews for competitor apps? Yes. Since this scraper only needs a public App Store ID or URL, you can monitor reviews for any published app, including competitors, to benchmark ratings and extract insights from their user feedback.

What does the status field mean? It indicates the result of processing that review row, confirming the review was captured and parsed successfully so you can filter your dataset with confidence.

Can I run this scraper on a schedule? Yes. Apify's built-in scheduler lets you run this actor daily, weekly, or on any custom interval so you can continuously monitor new App Store reviews without manual effort.

Does this work for apps that only have a few reviews? Yes. The scraper returns however many reviews are available up to your maxReviews setting — if an app only has 12 reviews, you'll get all 12.

Can I export the results to Excel or Google Sheets? Yes. Apify datasets support exporting to JSON, CSV, Excel, XML, and other formats, plus direct integrations to Google Sheets and other tools.

How current is the review data? Every run fetches reviews live from the App Store at the time the actor runs — there's no caching or stale data involved, so you always get the latest reviews available.

Can I scrape reviews for apps that aren't in English? Yes. Set the appropriate countries value for the storefront you want, and reviews will come back in whatever language users wrote them in for that region.

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Output Formats

Results are available directly from your dataset in every format Apify supports:

• JSON — structured data for programmatic use and API integration
• CSV — flat table format, opens directly in Excel and Google Sheets
• Excel (.xlsx) — native spreadsheet format with proper headers
• XML — structured markup for enterprise integrations

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Integration & Automation

Connect this App Store reviews scraper to your existing workflow:

• Google Sheets — append new reviews to a spreadsheet automatically
• Slack / Discord — get notified when a scheduled run finds new reviews
• Webhooks — trigger your own systems when a run completes
• Zapier / Make — connect to thousands of apps without writing code
• BigQuery / Snowflake / data warehouses — load review data for long-term analysis

Set up a recurring schedule with Apify's built-in scheduler to monitor new App Store reviews daily or weekly without lifting a finger.