App Store Reviews Scraper — $0.10 per 1,000 Reviews

Pull Apple App Store reviews for any list of iOS apps — star rating, headline, full text, the exact timestamp down to the second, app version, reviewer name, reviewer profile link and helpful-vote counts — as clean JSON or CSV.

App Store reviews are the rawest product feedback there is: what users love, what crashes, and why they churn — written the day it happened. They are also your competitor's roadmap in public. This Actor takes App Store IDs or URLs in bulk, scrapes reviews from any storefront, and returns one tidy row per review plus a rich summary row per app.

No API keys, no proxies, no setup — paste app IDs and run.

What you get per review

Field	What it tells you
rating	Star rating (1-5) the reviewer gave
title	The review headline — iOS reviews have real titles, and they are often the whole complaint
text	The review itself, in full
date	When it was posted — strict ISO 8601 UTC with a real time of day (2026-08-24T01:28:09.000Z), so pandas, BigQuery, Sheets and datetime.fromisoformat parse it with no clean-up step
date_raw	Apple's original timestamp, offset intact (2026-08-23T18:28:09-07:00) — the reviewer's local wall-clock time
app_version	Which release the reviewer was on — pin a complaint to a build
author	Reviewer's public nickname
author_url	Link to that reviewer's public profile — spot repeat reviewers and review rings
review_url	Apple's link back to the app's review page on the store
helpful_votes	Net helpful score — up-votes minus down-votes, so a divisive review can go negative
helpful_count	How many people voted on the review at all — the reach of that opinion
review_id	Stable id for deduping across scheduled runs
country / language	The storefront the review was read from
scraped_at	When this run collected the row

What makes this different

• Real timestamps, not zeroed dates. Every review carries the actual minute and second it was posted. A lot of App Store review tools hand you 00:00:00 on every single row, which quietly destroys any per-hour or per-release-window analysis.
• Helpful votes, populated. helpful_votes and helpful_count are numbers on every row, never null, so you can rank reviews by how much other users agreed instead of reading 500 of them in date order. (Reviews posted in the last few hours honestly start at 0 — nobody has voted on them yet. Set sortBy to most_helpful to surface the ones that have accumulated real vote counts.)
• A genuinely useful app_summary row. Most review scrapers return reviews and nothing else. Every run here also emits one summary row per app with the store rating, total ratings count, current-version rating, developer, seller, genre, current version, release and last-updated dates, content rating, price, size, supported languages, icon URL and release notes. One run gives you the reviews and the context to interpret them.
• No dead columns. Apple's public review data has no developer replies, so this Actor does not ship an always-empty developer_reply column pretending otherwise. Every field in the schema is a field Apple actually fills.
• Sort by most helpful. Switch sortBy to most_helpful to get the reviews the community voted up, not just the newest ones.

Use cases

• Review mining — feed thousands of reviews to an LLM and extract feature requests, bugs and churn reasons.
• Competitor analysis — scrape rivals' newest reviews and read their roadmap in their 1-star complaints.
• ASO monitoring — track rating trends and review velocity per release, per storefront.
• Release regression alerts — a spike of 1-star reviews pinned to app_version is your earliest crash signal.
• Reputation triage — sort by helpful_votes and answer the complaints that most users actually saw.
• Localization research — compare what users praise in the US, German and Japanese storefronts before you translate.
• Client reporting — a dated, exportable record of app sentiment for agencies and studios.

Pricing

Pay per result. No monthly fee, no setup fee, no minimum.

Event	Price
Actor start	$0.001 per run
Review scraped	$0.0001 — that is $0.10 per 1,000 reviews

Worked example: scraping 150 reviews each for 10 apps returns 1,500 reviews and costs $0.001 + 1,500 × $0.0001 = $0.151. Pulling the full 500-review ceiling for a single app costs $0.051. You are billed only for reviews actually returned — an app that fails, is not on that storefront, or returns nothing is not charged at all.

Input example

{
  "apps": [
    "310633997",
    "https://apps.apple.com/us/app/telegram-messenger/id686449807"
  ],
  "maxReviewsPerApp": 150,
  "sortBy": "most_recent",
  "countryCode": "us",
  "languageCode": "en"
}

Output example

{
  "record_type": "review",
  "app_id": "324684580",
  "review_id": "14464651610",
  "rating": 5,
  "title": "Sound selection is perfect.",
  "text": "I can listen to my favorite artist and songs. And the sound quality is on TOP.",
  "date": "2026-08-24T01:28:09.000Z",
  "date_raw": "2026-08-23T18:28:09-07:00",
  "app_version": "9.1.76",
  "author": "Stephen.I'm cool",
  "author_url": "https://itunes.apple.com/us/reviews/id1849973763",
  "review_url": "https://itunes.apple.com/us/review?id=324684580&type=Purple%20Software",
  "helpful_votes": 0,
  "helpful_count": 0,
  "country": "us",
  "language": "en",
  "scraped_at": "2026-08-25T06:10:00.000Z"
}

Plus one app_summary row per app:

{
  "record_type": "app_summary",
  "app_id": "324684580",
  "app_title": "Spotify: Music and Podcasts",
  "app_url": "https://apps.apple.com/us/app/spotify-music-and-podcasts/id324684580",
  "bundle_id": "com.spotify.client",
  "app_version": "9.1.76",
  "developer": "Spotify",
  "seller": "Spotify AB",
  "genre": "Music",
  "genres": ["Music", "Entertainment"],
  "app_rating": 4.775,
  "total_ratings_on_store": 41712246,
  "app_rating_current_version": 4.775,
  "total_ratings_current_version": 41712246,
  "released_at": "2011-07-14T20:31:24Z",
  "updated_at": "2026-08-18T13:24:11Z",
  "content_rating": "12+",
  "price": 0,
  "currency": "USD",
  "size_mb": 216.4,
  "supported_languages": ["EN", "DE", "FR", "JA"],
  "icon_url": "https://is1-ssl.mzstatic.com/image/thumb/.../512x512bb.jpg",
  "reviews_scraped": 150,
  "reviews_requested": 150,
  "pages_fetched": 3,
  "pages_unavailable": 0,
  "sort_by": "most_recent",
  "country": "us",
  "storefront": "United States",
  "language": "en",
  "scraped_at": "2026-08-25T06:10:00.000Z"
}

FAQ

Do I need an API key or proxies? No. Everything is handled for you — no API keys, no accounts, no proxy setup. Paste app IDs and run.

What can I put in the apps field? Either a bare numeric App Store id (310633997) or any full App Store URL — the id… segment is parsed out automatically. Up to 100 apps per run.

Why does it cap at 500 reviews per app? Because that is Apple's own hard ceiling. The public review feed serves at most 10 pages of 50 reviews per app per storefront, then answers page depth is limited to 10. Nobody can return more than 500 for a single app on a single storefront in one pass — anyone claiming otherwise is either counting across storefronts or repeating a scheduled run. Two ways to get more: scrape the same app across several storefronts, or run on a schedule and dedupe on review_id to accumulate history over time.

What format are the dates in? date is strict ISO 8601 UTC — 2026-08-24T01:28:09.000Z — with a real hour, minute and second, so pd.to_datetime, datetime.fromisoformat, BigQuery, Postgres and Google Sheets all read it directly. date_raw keeps Apple's original offset-bearing string if you want the reviewer's local time.

What is the difference between helpful_votes and helpful_count? helpful_count is how many people voted on the review; helpful_votes is the net score after down-votes are subtracted, so it can be negative on a review people disagreed with. Sort by helpful_votes for consensus, by helpful_count for reach.

Are developer replies included? No — Apple does not publish developer responses in its public review data, so there is no such column here. Shipping a column that is null on 100% of rows just looks broken. (Our Google Play sibling does return them, because Google does publish them.)

Does review_url link to one specific review? It links to the app's review page on the store. Apple does not mint a public per-review permalink for App Store reviews, so no tool can give you one — author_url, which does point at that specific reviewer's profile, is the per-row link that actually resolves.

Which countries work? All App Store storefronts — pass any two-letter country code (us, gb, de, in, br, jp, ...). Reviews are storefront-specific, so scrape each market you care about separately.

What happens if one app fails? It gets an error row explaining why, is not billed, and the rest of the run continues. One bad app id never kills the batch.

Some runs return slightly fewer reviews than I asked for. Why? Apple's public review feed occasionally serves a page with no data. The Actor retries each page several times on rotating IPs and reports exactly what happened in pages_fetched and pages_unavailable on the app_summary row. You are only ever billed for reviews you actually received.

Can I export it? Yes — JSON, CSV, Excel, or straight into n8n, Make or Zapier via the Apify API.

Related actors

• Google Play Reviews Scraper — the same output shape for Android apps; run both and diff sentiment across platforms.
• ASO Rank Tracker — track where your app ranks for its keywords on both stores.

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Tags: app store reviews scraper, ios app reviews, apple app store scraper, app reviews api, app review export, review mining, aso tool, app store optimization, app feedback analysis, competitor app reviews, iphone app reviews, bulk review scraper