App Release Reaction Monitor — Reviews & Sentiment
Pricing
from $50.00 / 1,000 release analyzeds
App Release Reaction Monitor — Reviews & Sentiment
Correlate app releases with dated, versioned review datasets. Compare ratings and complaint rates before/after each release and return regression, improvement, and evidence-ready issue signals.
Pricing
from $50.00 / 1,000 release analyzeds
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Developer
Ege Usta
Maintained by CommunityActor stats
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Monthly active users
8 days ago
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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, orINSUFFICIENT_DATAconclusion
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. 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.