Skip to main content
Web Extraction

Google Play Store Reviews Finder

Return structured Google Play Store reviews from a public app URL for app-market, voice-of-customer, product, and competitive research.

View details
Try it in Ampere

Inputs

Loading input fields...
Execution Steps

Loading workflow structure...

Loading curated examples...

Overview

Google Play Store Reviews Finder turns one public Google Play app details URL into normalized review records for app-market, voice-of-customer, product, and competitive research. Use it to mine Android app review language, ratings, helpful-vote signals, app context, and feature feedback from the returned review set.

Use cases

  • Pull Google Play reviews before writing Android app positioning, lifecycle messaging, or competitor notes.
  • Scan review text, ratings, dates, reviewer names, helpful counts, and app context for repeated feedback themes.
  • Collect review evidence for feature requests, objections, proof points, or release-feedback research.

Input tips

  • Paste a full HTTPS Google Play app details URL, such as https://play.google.com/store/apps/details?id=com.canva.editor.
  • The URL must use play.google.com/store/apps/details with one safe Android package ID in the id query parameter.
  • Set recordsLimit from 1 to 500; the default is 100.
  • Use Google Play Store App Details when you need store-page metadata rather than individual review rows.

Expected output

The AI Tool returns success, canonical Google Play URL, reviews, recordCount, recordsLimit, optional warnings, normalization summary, and cost metadata. Review rows can include review ID, 0-5 rating, review text, review date, reviewer name, helpful-vote count, safe Google Play URLs, app title, developer, overall app rating, total app review count, monetization labels, images, release notes, content rating, downloads, PC availability labels, minimum requirements, country/date-window fields, and sanitized extra fields.

Caveats

  • Only public Google Play app detail URLs with a safe package ID are accepted.
  • An empty result does not prove the app has no public reviews; confirm the app page directly.
  • Review availability, ratings, helpful counts, app context, and text can change after the run.
  • Noisy or unsafe scraped fields may be normalized, omitted, preserved as extra fields, or reported in warnings.

Related AI Tools