App Release & Customer Reaction Monitor

Answer the product question that a raw app-review scraper cannot: did this release improve customer experience, or introduce a regression?

The Actor joins structured release records with dated review records. When at least three reviews carry the exact app version, version attribution wins; otherwise a configurable before/after date window is used.

Each release report includes

• review counts before and after
• average rating before, after, and the change
• sentiment direction
• emerging, resolved, and recurring complaint categories
• regression signals and issue-spike flag
• IMPROVED, REGRESSED, MIXED, STABLE, or INSUFFICIENT_DATA conclusion

Composition-first input

Paste records or provide Apify dataset IDs. This Actor intentionally does not scrape Apple App Store or Google Play itself, so it can work with different upstream collectors and does not depend on brittle authenticated/private endpoints.

Quick start

{
  "appName": "Acme Mobile",
  "releases": [{ "version": "2.0.0", "releaseDate": "2026-08-01", "releaseNotes": "New sync engine" }],
  "reviews": [
    { "text": "Stable and fast.", "rating": 5, "date": "2026-07-28", "version": "1.9.0" },
    { "text": "Crashes after the update.", "rating": 1, "date": "2026-08-03", "version": "2.0.0" }
  ]
}

Pricing

The intended pricing is pay per release analyzed, with platform usage included. The run summary is free. INSUFFICIENT_DATA reports are delivered free with a reason; only real verdicts are charged, and invalid or duplicate records are skipped with a warning. Exact current pricing appears on the Store page and charge limits are respected.

Limitations

At least three reviews on both sides are required for a directional conclusion. Version labels and review dates come from upstream data and are not independently verified. Keyword-based issue categories are transparent but may miss synonyms, sarcasm, and non-English feedback. Correlation around a release is not proof that the release caused the reaction. Always inspect underlying reviews before shipping a rollback or product decision.

Reviewer identity is ignored; no personal-data profiling, outreach, private scraping, credentials, or CAPTCHA bypass are used.

FAQ

Does it scrape the data itself? No. It analyzes records you supply (pasted JSON or another Apify dataset), so you stay in control of where the data comes from. Pair it with a collector Actor or your own export.

How does it tell whether a release hurt ratings? When at least three reviews carry the exact app version, it compares by version; otherwise it uses a before/after date window around each release and reports the rating change and new, resolved and recurring complaints.

How much does it cost? $0.05 per release analyzed plus $0.01 per run. Releases without enough reviews are reported free as insufficient data.

Can I run it through the API or on a schedule? Yes. Save your input as a task, schedule it in Apify Console, or call it from the Apify API. Results export as JSON, CSV or Excel and connect to Google Sheets, Slack, Make, Zapier or a webhook.

Related Actors

• Customer Review Complaint Analyzer
• SaaS Review Analyzer