App Store Review Miner

App Store Review Miner finds the recurring complaints hiding inside the top-grossing apps of any App Store category. It pulls the current top-grossing chart for a category, fetches each app's most recent App Store reviews, and classifies every low-rated (★3 or below) review into 13 complaint buckets (billing, crashes, sync, missing features, and more). The output is a ranked list of the biggest category-wide weaknesses — the gaps a smaller, cheaper, or friendlier competitor could exploit. Try it with any category (Productivity, Finance, Health, Games, ...) and any App Store country storefront.

Why use App Store Review Miner?

If you're evaluating a "copy and improve by 10%" app idea, competitor research, or market due diligence, reading reviews one app at a time doesn't scale. This Actor automates that grind and gives you two things a single app's review page never shows:

• Which complaints are structural (show up across most of the category) vs. which are one app's problem — the former is where the real opportunity is.
• Which apps have a "reputation drop" — a recent review average meaningfully below their all-time store rating, meaning users are souring on them right now.

Runs on the Apify platform, so you get scheduling, an API, and result export for free — no local Node.js setup required.

How to use App Store Review Miner

1. Click Try for free.
2. Set the Category (e.g. fitness, productivity, finance — or a raw numeric App Store genre ID) and the Country storefront (us, kr, jp, ...).
3. Optionally narrow the top-grossing rank range and how many review pages to sample per app.
4. Click Start and wait — a run over 30 apps with 2 review pages each typically finishes in a few minutes.
5. Open the Dataset tab for one row per app, or download the full markdown report from the Key-value store tab (REPORT.md).

Input

Field	Type	Default	Description
genre	string	productivity	Category name or numeric App Store genre ID
country	string	us	Two-letter App Store storefront country code
from	integer	1	Start of the top-grossing rank range
to	integer	30	End of the top-grossing rank range (max 200)
pages	integer	2	Review pages per app (50 reviews/page, max 10)

Example input:

{
    "genre": "fitness",
    "country": "us",
    "from": 1,
    "to": 30,
    "pages": 2
}

Output

One dataset item per app:

{
    "rank": 1,
    "name": "ChatGPT",
    "artist": "OpenAI OpCo, LLC",
    "storeRating": 4.83,
    "ratingCount": 9207009,
    "recentAvg": 4.28,
    "reputationDrop": false,
    "sampled": 50,
    "lowCount": 9,
    "topComplaints": ["crash/bug/error", "speed/performance/battery", "ads"],
    "buckets": { "crash/bug/error": 2, "speed/performance/battery": 1, "ads": 1 }
}

You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. The full markdown report (category-wide complaint ranking + per-app detail + sample low-rated review text) is saved to the run's key-value store under the key REPORT.md.

Data table

Field	Description
rank	Position in the top-grossing chart
storeRating / ratingCount	All-time App Store rating and rating count
recentAvg	Average rating across the sampled recent reviews
reputationDrop	true if recentAvg is ≥0.7 below storeRating
lowCount / sampled	How many of the sampled reviews were ≤3★
topComplaints / buckets	Complaint categories detected in low-rated reviews, with counts

Cost estimation

This Actor makes lightweight HTTP calls to Apple's public RSS/JSON endpoints — no browser, no proxy required. A typical run (30 apps × 2 review pages) uses well under the free Apify plan's monthly compute allowance.

Tips

• Keep pages low (1-2) for a quick scan across many apps; raise it only when you've already narrowed down to a handful of apps you want deep review detail on.
• to - from above ~50 will take proportionally longer since each app is fetched with a short delay to stay within Apple's rate limits.

FAQ & disclaimers

This Actor only reads Apple's public RSS and iTunes Lookup endpoints (the same feeds the App Store website itself uses) — no login, scraping of private data, or Terms of Service violation involved. Review text is reproduced only in short excerpts for research purposes. Found a bug or want a feature (e.g. Google Play support)? Open an issue on the Actor's Issues tab.