Negative Review Alert Monitor
Pricing
Pay per usage
Negative Review Alert Monitor
Fetch recent public Apple App Store reviews and emit structured review, sentiment, and topic rows for app teams, agencies, and investors.
Pricing
Pay per usage
Rating
0.0
(0)
Developer
Stephen Coulson
Maintained by CommunityActor stats
0
Bookmarked
2
Total users
0
Monthly active users
4 days ago
Last modified
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What does Negative Review Alert Monitor do?
Negative Review Alert Monitor extracts recent public Apple App Store reviews and turns them into clean, structured review intelligence. Give it one or more app IDs and it returns review text, ratings, dates, public reviewer display names, sentiment buckets, and topic tags.
Use it to monitor your own app, competitors, launches, pricing complaints, bug reports, feature requests, and support issues. It runs on Apify, so you can schedule it, call it by API, download CSV/Excel/JSON, or connect the dataset to Google Sheets, Slack, Zapier, Make, and other tools.
Why use Negative Review Alert Monitor?
App Store reviews are high-signal customer feedback. They show what users love, what is broken, and what competitors are being praised or criticised for.
This Actor helps you:
- track new reviews for your app or competitors;
- spot negative reviews and bug complaints quickly;
- tag reviews by topics such as
price,bug,login,support, orsubscription; - build product, support, marketing, or investor monitoring workflows;
- export structured review data without writing custom Apple RSS parsing code.
It uses public Apple RSS JSON endpoints. No login, cookies, proxies, or private user enrichment are required.
How to use Negative Review Alert Monitor
- Open the Actor on Apify.
- Add one or more Apple App Store app IDs.
- Choose the country code, for example
usorgb. - Add topic keywords you want tagged in review text.
- Optionally filter by rating range.
- Run the Actor.
- Download the dataset in JSON, CSV, Excel, HTML, or XML, or connect it to an Apify integration.
Input
Example input:
{"apps": [{ "name": "ChatGPT", "appId": "6448311069", "country": "us" }],"keywords": ["price", "bug", "crash", "support", "slow", "feature", "subscription", "login"],"maxReviewsPerApp": 50,"minRating": 1,"maxRating": 5}
Input fields
| Field | Description |
|---|---|
apps | List of App Store apps to monitor. |
appId | Numeric Apple App Store app ID. |
country | Two-letter App Store country code, e.g. us, gb, de. |
keywords | Topic words to tag inside review titles and text. |
maxReviewsPerApp | Maximum recent reviews to fetch per app. |
minRating | Minimum star rating to emit. |
maxRating | Maximum star rating to emit. |
Output
The Actor outputs one row per review.
{"source": "apple_app_store","app_id": "6448311069","app_name": "ChatGPT","country": "us","review_id": "f8b9de16643744ece7771b2d","review_title": "Excellent","review_text": "Excellent - helpful and enjoyable","rating": 5,"reviewer_name_public": "19 yrs w bbt","review_date": "2026-07-02T14:04:44-07:00","sentiment_bucket": "positive","topics": ["feature"],"detected_at": "2026-07-04T01:35:50Z","source_url": "https://itunes.apple.com/us/rss/customerreviews/id=6448311069/sortby=mostrecent/json"}
You can download the dataset in various formats such as JSON, HTML, CSV, or Excel.
Data table
| Field | Meaning |
|---|---|
app_id | Apple App Store app ID. |
app_name | App name supplied in input. |
country | App Store country. |
review_title | Review title. |
review_text | Public review body. |
rating | Star rating from 1 to 5. |
reviewer_name_public | Public App Store reviewer display name. |
review_date | Review timestamp from Apple RSS. |
sentiment_bucket | Simple sentiment label: positive, negative, or mixed/neutral. |
topics | Input keywords found in review title/text. |
source_url | Apple RSS JSON source URL. |
Pricing and cost estimation
This Actor is lightweight. It calls public Apple RSS JSON endpoints and does not use browser automation or proxies.
Costs depend mainly on:
- number of apps monitored;
- number of reviews per app;
- run frequency.
Start with a small app list, then schedule recurring runs once the output shape is right.
Tips and advanced options
- Set
maxRatingto2to monitor only unhappy users. - Add competitor app IDs to track launch reactions and product weaknesses.
- Use topic keywords like
pricing,subscription,login,support,crash, andslow. - Schedule daily or weekly runs and connect output to Slack or Google Sheets via Apify integrations.
FAQ, disclaimers, and support
Does this access private App Store data? No. It only reads public Apple RSS review feeds.
Does it support Google Play? Not yet. Request it in the Issues tab if useful.
Is this a true delta monitor? The Actor emits recent reviews with stable IDs and timestamps. For recurring workflows, compare current results with prior datasets or scheduled-run history.
Is this legal? This Actor reads public review feeds. You are responsible for using the data in accordance with applicable laws, Apple terms, and privacy obligations.
For bugs, feature requests, or custom versions, use the Issues tab on Apify.