Pricing

Pay per event

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App Store Reviews Scraper + Pain Point Analysis (v2)

Try for free

Scrape Apple App Store reviews for any app and storefront (no login, official public RSS feed) and get pain-point / feature-request analysis on top: verbatim complaints, not keyword bags.

Pricing

Pay per event

Rating

0.0

(0)

Developer

Backyard Tools

Actor stats

Bookmarked

Total users

Monthly active users

a day ago

Last modified

Tested (2026-09-02)

5/5 well-known apps returned real reviews on the first request:

App	App ID	Reviews returned
Notion	1232780281	20/20 requested
Facebook	284882215	20/20 requested
WhatsApp	310633997	20/20 requested
Instagram	389801252	20/20 requested
TikTok	835599320	20/20 requested

A single storefront page (50 reviews) took ~0.09s to fetch in that test.

How it works

Apple has published this RSS feed for over a decade with no authentication and no rate-limit wall for reasonable use — one of the most stable public data sources available. No scraping countermeasures to fight, which is also why it needs almost no maintenance.

Input

{
  "targets": ["1232780281:us", "1232780281:jp"],
  "maxItems": 200,
  "analyses": ["overview", "group-regressions"]
}

Each target is "AppID:storefront". Apple caps each storefront at ~500 reviews per app, and every storefront holds a different set of reviews — pass more "id:cc" pairs to cover more countries in one run.

Output

One dataset item per review:

Field
`review_id`	Apple's review id
`author`	reviewer's public display name
`rating`	1–5 stars
`text` / `title`	review body and headline
`date`	when the review was last updated
`group`	the app version the review was left on
`link`	the review's public URL on the App Store

No email, phone number, or physical address is present — Apple's public feed doesn't carry those fields.

Analyses (billed once per run, not per review)

Analysis	What you get
`overview`	count, average rating, negative share with a lower-confidence bound
`top-complaints`	actual excerpts from low-rating reviews
`top-requests`	actual excerpts asking for a feature
`group-regressions`	which release's ratings dropped versus the rest — the "did that update hurt us" question, answered directly
`trend`	monthly volume and negative share

Use Cases

Competitor monitoring: track a rival app's rating trend and recurring complaints release over release.
Release QA triage: run group-regressions right after shipping to catch a version that tanked ratings, with real complaint text attached.
Feature roadmap input: mine top-requests for what users are actually asking for, in their own words.
ASO / App Store copy research: see the exact language reviewers use to praise or criticize competing apps.

Pricing

Pay per event: $0.20 per 1,000 reviews collected, plus $0.05 per analysis you select.

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