Infrastructure
Proxy routing, browser execution, retries, and usage controls are operational work.
Normalized JSONAPI-key usage trackingCredit-based pricingPlatform-specific APIs
App Review Analysis API for App Store and Google Play
Turn public app reviews and ratings into product insights, competitor intelligence, ASO research, and customer feedback workflows.
The problem
App feedback is valuable, but manual review analysis does not scale
Mobile app teams need to understand what users love, what they complain about, and how competitors are changing. App review analysis API workflows help teams collect public reviews, ratings, app metadata, and version signals without maintaining brittle app store scrapers.
Normalization
Raw pages must become stable records before products and data teams can use them.
Product fit
Use-case landing pages should map directly to buyer workflows and internal data models.
Responsible use
Structured public web data workflows still need clear legal, privacy, and platform boundaries.
What you can collect
Structured data categories
Example fields may include app metadata, public review fields, ratings, locale context, and version history fields.
app name
app ID or package ID
rating
review title
review text
review author display name, if public and supported
review date
app version
country or locale
rating distribution
version history
competitor app metadata
Relevant Crawlora APIs
Platform-specific endpoints for this workflow
Start from the platform page or endpoint docs, then test the same route in Playground before production integration.
Example workflow
From target definition to product output
Crawlora keeps the scraping execution layer behind documented APIs so your product can focus on storage, analysis, alerts, and user workflows.
01
Select apps
Define your own apps and competitor apps by ID, package, keyword, or category workflow.
02
Pull reviews and ratings
Use Crawlora app store endpoints to collect recent public review and rating data.
03
Normalize and enrich
Store review text, rating, locale, date, app version, and app metadata together.
04
Analyze feedback
Run tagging, sentiment, topic extraction, alerts, or LLM summaries for product teams.
API example
Illustrative App Store reviews request
Illustrative example using the documented App Store reviews route. Check Docs for current parameters and response fields.
Request
Illustrative exampleGET https://api.crawlora.net/api/v1/appstore/reviews?id=6448311069&country=us
x-api-key: YOUR_API_KEYIllustrative response
Illustrative example{
"code": 200,
"msg": "OK",
"data": [
{
"rating": 5,
"title": "Example review",
"text": "Public review text...",
"date": "2026-01-01"
}
]
}What you can build
Products, dashboards, and workflows this data can power
These are practical workflow patterns for SaaS products, data teams, AI agents, agencies, growth teams, and internal intelligence tools.
Review intelligence dashboard
Group reviews by app, version, rating, topic, and competitor.
Competitor app tracker
Monitor competing app updates, ratings, and customer complaints.
ASO research tool
Connect reviews, rankings, metadata, and category changes to app store optimization workflows.
Rating alert system
Notify product teams when ratings or review topics shift.
Product feedback pipeline
Route public review signals into product, support, and roadmap tools.
LLM review summarizer
Feed structured reviews into AI summarization and topic extraction workflows.
Build or buy
Why not build it yourself?
Custom scrapers can work for prototypes. Production web data workflows need infrastructure, monitoring, stable output, and clear failure behavior.
| DIY approach | Crawlora approach |
|---|---|
| Maintain App Store and Google Play scrapers | Use app store APIs for documented workflows |
| Handle locale differences and changing pages | Normalize reviews, ratings, and app fields for analysis |
| Build review ingestion and retry logic | Use API-key routes with managed execution and usage tracking |
| Prepare raw text manually for AI workflows | Send structured review records into LLM or analytics pipelines |
Infrastructure
Explore the managed execution layer
Crawlora combines platform-specific APIs with managed proxy routing, browser-backed rendering, retries, rate limits, usage tracking, and scaling controls.
Responsible use
Use structured public web data responsibly
Public review data should be handled responsibly. Avoid exposing unnecessary personal information and comply with applicable laws, platform terms, privacy rules, and third-party rights. Read Crawlora terms.
Related use cases
More structured web data workflows
Cross-link practical workflows that often share the same data infrastructure and product buyers.
FAQ
App Review Analysis FAQ
Answers for developers and product teams evaluating Crawlora for this workflow.
Can Crawlora collect App Store reviews?+
Yes. Crawlora includes documented App Store review and app metadata workflows for public app intelligence use cases.
Can Crawlora collect Google Play reviews?+
Yes. Crawlora includes Google Play review and app metadata workflows. Check Docs for current parameters.
Can I monitor competitor apps?+
Yes. You can define competitor apps and collect public app metadata, reviews, ratings, and version-related signals where supported.
Can I analyze reviews with AI?+
Yes. Structured review records are useful inputs for tagging, sentiment analysis, topic extraction, summaries, and product feedback workflows.
Can I track ratings over time?+
Yes. Store Crawlora responses as snapshots and compare ratings, review counts, and rating distributions over time.
Do I need to maintain my own app store scraper?+
For supported endpoints, Crawlora handles the API execution and normalized response layer so you can avoid maintaining custom app store scrapers.
How do endpoint credits work?+
Crawlora uses credit-based pricing. Current credit behavior is shown in product pricing and endpoint documentation.
Start building
Start building with structured public web data
Browse Crawlora APIs, test a request in Playground, and move from scraping infrastructure work to production data workflows.