Know what your App Store reviews are saying.
Use the FetchLayer App Store Reviews API as the source for an alerting or monitoring workflow. Poll public feedback on your schedule, store what you retrieve, and bring new complaints or praise to the right team.
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The workflow
From a polling schedule to an alert in Slack.
FetchLayer gives you the public data in a predictable shape. Your code, automation, or AI agent can turn it into an ongoing source of customer insight.
- 01
Choose the apps and markets
Start with your app, important countries, and a small competitor set where a change in feedback would matter.
- 02
Poll public review pages
Run FetchLayer on an interval that matches your needs. Fetch recent pages and retain the review records in your own system.
- 03
Route the changes
Filter for new low ratings, a sudden cluster of similar complaints, or notable praise, then notify product, support, or research.
What to surface
What's worth an alert, and what can wait for the weekly digest.
Low-rating feedback
Flag one- and two-star reviews for prompt investigation without losing the full context of the customer’s message.
Release regressions
Watch review text and versions after a rollout to find reports of breakage that deserve a closer look.
Competitor movement
Keep a lightweight view of the public complaints and praise appearing around competing apps.
Your own alerts
Send review changes into Slack, email, a ticketing system, or any workflow your team already owns.
Country-specific changes
Monitor feedback in markets that matter instead of relying only on one storefront’s review stream.
A reusable history
Keep the review data in your own warehouse or database for analysis beyond a single alert.
AI-ready input
Let your agent triage new reviews before a human has to.
Use FetchLayer through REST or MCP. The important part is keeping the original feedback alongside the summary so your team can inspect the evidence behind every conclusion.
Review the new App Store feedback collected this week. Which complaints are new, which issues are growing, and which reviews should the support team read first?
The new complaint cluster is login failures after the latest release. Route the cited one-star reviews to support, then compare the affected version against prior releases before escalating to engineering.
Start free. Scale when ready.
Try it free, buy credits as you go, or take a monthly plan when your volume is steady.
Free
$0
30 requests
Enough to call the platforms you care about and read real responses before you pay anything.
- Every platform and endpoint
- REST and MCP
- No credit card
Pay as you go
$1.99
per 1,000
Buy credits when you need them. They stay on your account until you use them.
- Credits never expire
- No monthly commitment
- Same access as subscribers
- ∞ req/min, ∞ API keys
Monthly plan
Starter$25
per month
15,000 requests a month, about 500 a day.
$1.67 per 1,000, $5 less than credits each month
- ∞ req/min, ∞ API keys
1 page fetched is 1 credit
A normal call reads one page. Ask for more pages and each one is one more credit.
The same on every platform
No multiplier for harder targets, and no charge per result returned.
Nothing back, nothing billed
If a request does not return usable data, it costs 0 credits.
Not sure which volume fits?
15 minutes with the founder. Tell us the workload, we tell you what it needs.
Guaranteed throughput on the platform you run on
A dedicated platform from $400/mo, plus $500 for each ~21 req/s. Every other platform on the same key. 99.95% uptime, 24-hour support on Slack or Telegram.
FAQ
Common questions.
Is FetchLayer a hosted App Store alerting tool?
FetchLayer is the API layer. Call it on your own schedule from a cron job, automation, or application, then send alerts to the tools your team uses.
Can I monitor a competitor app?
Yes. Fetch public reviews for competitor apps by app ID and keep your own history of the feedback you want to monitor.
What should a monitoring workflow store?
Store the review ID, rating, review text, version, date, locale, and the time your workflow retrieved it. That makes it possible to identify new feedback and review changes over time.
Start with the public feedback.
Retrieve the source data, keep the evidence, and build the feedback workflow your team actually needs.