📱 iOS App Store Reviews Scraper — Ratings, Sentiment & Version Deltas

Bulk-extract user reviews from the Apple App Store for any iOS app, in any country storefront. Returns review text, star rating, author, date, app version, helpful-vote counts, and developer responses — clean JSON ready for sentiment analysis, ASO competitor monitoring, or product feedback dashboards. A cheaper, pay-per-result alternative to AppFollow, Sensor Tower, Mobile Action, and App Annie (data.ai) — purpose-built for ASO teams, mobile-product PMs, and competitive-intelligence analysts who need raw review data without a five-figure seat license.

Why iOS App Store Reviews Scraper Beats AppFollow, Sensor Tower, Mobile Action & data.ai

Feature	NexGenData iOS Reviews Scraper	AppFollow	Sensor Tower	Mobile Action	data.ai (App Annie)
Cost	$1 per 1K reviews, pay-per-event	$69-499 / month	$$$$ enterprise quote	$69-499 / month	$$$$ enterprise quote
Multi-country storefronts	Yes — 155 countries	Yes (paid tier)	Yes	Limited	Yes
Version-level review breakdown	Yes — app_version per review	Yes	Yes	Yes	Yes
Developer responses captured	Yes	Yes	Yes	Yes	Yes
Bulk export	JSON / CSV / Excel	Plan-gated	Plan-gated	Plan-gated	Plan-gated
Historical depth	Up to 500 newest per app	1 year (plan-gated)	90 days default	1 year (plan-gated)	Plan-gated
Auth	Apify token	Account + seat	Account + seat	Account + seat	Account + seat
Monthly minimum	None	$69+	$$$$	$69+	Annual contract

Most ASO + product teams pick this actor instead of AppFollow because it is a drop-in alternative that runs on demand, is cheaper than Sensor Tower for review-only workflows, and the JSON shape (rating, text, version, country) plugs straight into BigQuery, Snowflake, or a sentiment-analysis pipeline without manual export gymnastics.

What You Get Per Review

Each dataset item is a flat record:

• app_id — Apple numeric app ID
• country — storefront country code (e.g. us, gb, jp)
• rating — 1-5 stars
• title — review title
• body — full review text
• author — reviewer display name
• date — ISO 8601 review timestamp
• app_version — version the review was filed against
• helpful_count — community-vote helpfulness score
• developer_response — {text, date} if developer replied
• is_edited — boolean flag for edited reviews

Use Cases

• ASO managers — track star rating + sentiment trend after each version release to catch crash-driven 1-star spikes within hours
• Competitive-intel teams — pull a competitor's full review stream to surface feature gaps customers are vocally requesting
• Product managers — feed reviews into an LLM to auto-cluster pain points by theme (paywall, onboarding, perf)
• Customer-support leaders — watch for support-flagged reviews across non-English storefronts you don't natively read
• ML / NLP teams — build training datasets of star-labelled review text for sentiment-model fine-tuning
• Investors — measure app momentum and user satisfaction before a public IPO or M&A diligence

Quick Start

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("nexgendata/ios-app-store-reviews-scraper").call(run_input={
    "appIds": ["284882215", "310633997"],
    "countries": ["us", "gb", "ca"],
    "maxReviews": 500
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["rating"], item["app_version"], item["body"][:80])

Pricing

Pay-per-event:

• Actor Start: small fixed charge per run (memory-scaled)
• Per review: $1 per 1,000 reviews returned

No subscription, no minimum, no per-seat fee.

Related NexGenData Actors

Use case	Actor
Google Play (Android) reviews	google-play-reviews-scraper
Google Play store app metadata	google-play-store-scraper
Cross-source review intelligence MCP	review-intelligence-mcp-server
AI sentiment analysis pipeline	ai-sentiment-analyzer
Trustpilot review scraper	trustpilot-review-scraper
App Store ranking / chart tracker	app-store-chart-tracker
Product Hunt launches	product-hunt-scraper
YouTube channel + video data	youtube-media-mcp-server

FAQ

Does this require an Apple Developer account or API key? No — it works against the public storefront feed. Bring an Apify token, nothing else.

How fresh is the data? Reviews are fetched live at run time. Apple's public storefront feed typically reflects new reviews within a few hours of submission.

What's the deepest review history I can pull? Apple exposes the most-recent ~500 reviews per (app, country) pair. For longer histories, schedule the actor daily and append into your own warehouse.

Output formats? JSON, CSV, Excel, RSS, and the Apify dataset API — all standard.

Is this legal? Yes. The public storefront feed is intentionally exposed by Apple for third-party indexing and review monitoring.

About NexGenData

NexGenData publishes 260+ buyer-intent actors covering SEC filings, YC alumni, lead generation, competitive intelligence, stock fundamentals across 30+ exchanges, and more. All pay-per-result. Browse the full catalog at https://apify.com/nexgendata?fpr=2ayu9b

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How NexGenData Pricing Works

Every NexGenData actor uses pay-per-event pricing — you only pay for results that actually land in your dataset. No monthly minimum, no seat fees, no surprise overage bills.

• Actor Start: a single-event charge each time you spin the actor up (scaled to memory size)
• Result / item: charged per item written to the default dataset
• No charge for retries, internal proxy rotation, or failed sub-requests — those are absorbed by the platform

Apify Platform Bonus

New to Apify? Sign up with the NexGenData referral link — you get free platform credits on signup (enough for several thousand free results) and you help fund the maintenance of this actor fleet.

Integration Surface

Every actor in the NexGenData catalog can be triggered from:

• Apify console — point-and-click run
• Apify API — REST + webhooks
• Apify Python / JS SDKs — programmatic batch
• Zapier, Make.com, n8n — official integrations
• MCP — many actors are exposed as MCP tools for Claude / ChatGPT / Cursor agents
• Schedules — built-in cron for daily / weekly / monthly runs
• Webhooks — POST results to any HTTPS endpoint on dataset write

Support

NexGenData maintains 260+ Apify actors and ships updates regularly. Bug reports via the Apify console issues tab get a response within 24 hours. Roadmap requests are welcome — high-demand features ship in the next version.

Home: thenextgennexus.com Full catalog: apify.com/nexgendata