App Review Change Monitor

Monitor public Apple App Store review feeds for new reviews, low-rating alerts, and competitor review digests.

This Actor is designed for scheduled product and competitor monitoring. It is intentionally narrower than generic review scraping: the first value is a compact change report that tells a product team what changed since the previous run.

Input

• apps: App Store app IDs with optional labels and countries.
• maxApps: maximum app entries processed in one run. The default is 5 and the hard cap is 20.
• fallbackCountries: country feeds to try when the primary country has an empty RSS feed.
• previousReviewIds: optional IDs from a previous run.
• maxReviewsPerApp: maximum recent reviews per app. The default is 50 and the hard cap is 100.
• lowRatingThreshold: ratings at or below this value are flagged.
• alertKeywords: words such as bug, crash, login, refund, or privacy that mark a new review as an alert.
• snapshotKey: key-value-store record used for scheduled change detection.
• saveSnapshot: stores current review IDs for the next run.

Output

Dataset rows include:

• app ID, app label, and country
• review ID and URL
• rating, title, author, update time, and content
• NEW, SEEN, or ERROR status
• alert flag, priority, risk category, keyword matches, and reasons

Key-value-store records:

• SUMMARY: machine-readable counts and averages
• REPORT: Markdown digest for quick inspection

The report also includes a competitive snapshot when multiple apps are monitored:

• average rating per app
• alert rate per app
• top risk category per app
• 1-5 star rating distribution

This is the main difference from a generic App Store reviews scraper: the output is shaped for product and competitor monitoring, not raw review extraction.

The Actor intentionally reads the public Apple RSS feeds and keeps conservative per-run caps. It is not positioned as a full historical App Store review archive or browser-based bulk scraper.

Monetization plan

First release should be free or usage-cost-only. If organic usage appears, the clean paid unit is a scheduled digest or a new-review-alert event. Do not charge for simply seeing unchanged reviews. Good paid events are new low-rating reviews, billing/privacy complaints, and keyword-triggered alerts.

Public-source smoke evidence

Latest local live smoke against the public App Store RSS source passed:

• artifact: _target_checks/live-smoke/2026-07-01T12-54-13-311Z.json
• app: public App Store app id 333903271
• rows: 10
• new reviews: 10
• low-rating alerts: 4
• high-priority alerts: 4
• average rating: 3.1

This smoke test does not use Apify remote runs, proxies, or browser automation. It exercises the same public-feed parsing and alert logic used by the Actor.

Release sequence

1. Keep local validation and public-source smoke green.
2. Run one guarded private Apify test only after explicit approval:

powershell -ExecutionPolicy Bypass -File .\scripts\apify-run-approved-remote-test.ps1 -Actor app-review -Apply -ConfirmText 'APPROVE guarded app-review remote private test <= $0.02'

3. Publish free or usage-cost-only first.
4. Consider PPE only after organic usage appears and run cost is measured.

Local validation

npm test
npm run sample
npx apify-cli validate-schema
npm pack --dry-run --json