Methodology
How App Pricing Lab turns public app store pages into pricing intelligence.
Data Sources
App Pricing Lab uses public app store data, including Apple App Store RSS rankings, app listing metadata, developer names, app prices, in-app purchase catalog information, rating signals, review counts, category assignments, and public URLs. Google Play data may be present from local enrichment workflows, while the deployed crawler prioritizes Apple data on Cloudflare Workers.
Crawl Cadence
The crawler runs daily in phases: rankings first, app details second, and IAP monitoring third. Long-running IAP checks use a resume queue so never-checked apps and oldest-checked apps rotate forward. This makes the system resilient to timeouts while still expanding coverage.
Pricing Analysis
Pricing pages use stored app prices, IAP snapshots, and change records to identify price drops, price increases, paid-app clusters, premium categories, and developer monetization patterns. USD-only price comparisons are filtered to avoid mixing currencies when no exchange-rate conversion is available.
Limitations
App stores change frequently, country availability differs, and crawler snapshots may lag behind the live listing. App Pricing Lab is not affiliated with Apple or Google, and all trademarks belong to their owners. Use the data as directional research rather than the only input for business decisions.
Why This Exists
The site is maintained to make pricing benchmarks easier to find and cite. It is also the public research layer for Monetai's broader work on dynamic pricing, AI pricing optimization, and app monetization intelligence.