Google Play App Reviews Dataset

Description

Explore the most comprehensive

Google Play App Reviews Dataset

, featuring over 134 million consumer insights from the official play.google.com domain. This extensive collection provides crucial data points including App Id, Review Id, User Name, Content, Score, Thumbs Up Count, and Review Created Version. Gain deeper insights with details like User Image, App Version, Language, and even developer Reply Content and Replied At timestamps. Ideal for

sentiment analysis, competitive benchmarking, market research, and trend identification

across millions of applications. Leverage this rich resource to understand user feedback, optimize app strategies, and drive informed product development decisions.

Highlights

  • 134.9M+ Google Play app reviews.

  • Covers all app categories and languages.

  • Continuously updated Play Store review data.

  • Detailed reviews: content, score, replies, version.

Sample Data

Preview of available data:

Url Score App Id Content Uniq Id Version Language Review Id User Name Replied At Scraped At User Image App Version Reviewed At Imported At Reply Content Thumbs Up Count Review Created Version
https://play.google.com/sto... 5 com.activision.callofduty.s... Very good game but the game... 00000007595202cf14eb927c119... 1773072981819 en 9551829b-164f-4143-9767-3f7... A Google user \N 2025-12-14 19:46:32.743379000 https://play-lh.googleuserc... \N 2023-08-20 22:31:54 2026-03-09 16:16:21 \N 0 \N
https://play.google.com/sto... 4 com.percent.mybest3 This app was awesome 😘 0000001c92812e86a2acd3f72c4... 1773067249877 en 545f04a9-108c-4d9c-a983-f24... A Google user \N 2025-12-17 17:17:57.668100000 https://play-lh.googleuserc... 4.6.3 2021-03-04 20:32:31 2026-03-09 14:40:49 \N 0 4.6.3
https://play.google.com/sto... 5 com.einnovation.temu good job temu 00000068b6dacc1d405fd318476... 1773072981819 sl 06e1fea7-12cc-4141-a73d-707... A Google user \N 2025-12-16 05:31:22.710947000 https://play-lh.googleuserc... 3.95.0 2025-10-08 22:37:51 2026-03-09 16:16:21 \N 0 3.95.0
https://play.google.com/sto... 5 com.outfit7.talkingtom 🤗😍 0000007ea419da550c12a2cabdc... 1773072981819 unknown 49010e73-f1d5-4d16-a458-129... A Google user \N 2025-12-16 13:12:45.082638000 https://play-lh.googleuserc... \N 2020-07-12 22:57:05 2026-03-09 16:16:21 \N 0 \N
https://play.google.com/sto... 5 com.rovio.baba I love how you have to be s... 000000a7c6b72dae0934cdd98ed... 1773072981819 en 68f428ce-c4e3-49ba-b598-5f1... A Google user \N 2025-12-15 11:19:04.977795000 https://play-lh.googleuserc... 2.36.0 2019-12-20 20:17:35 2026-03-09 16:16:21 \N 0 2.36.0
https://play.google.com/sto... 5 com.dressup.avatar.vlinder.... I love this app 000000ac845e191d10a111d9347... 1773067249877 en 54518716-f6c9-44cd-9dd0-009... A Google user \N 2025-12-17 11:24:17.123526000 https://play-lh.googleuserc... 2.2.15 2022-01-03 14:53:43 2026-03-09 14:40:49 \N 0 2.2.15
https://play.google.com/sto... 5 com.audiomack I love this app 000000ae2a6aa0c9e3a4f4b4a84... 1773072981819 en 664a1351-1715-441f-9b5e-fd4... A Google user \N 2025-12-15 04:24:49.555272000 https://play-lh.googleuserc... 6.57.3 2025-02-27 16:42:46 2026-03-09 16:16:21 \N 0 6.57.3
https://play.google.com/sto... 5 com.happydream.solitaire Brain teasing 000000babbc7354f66e1dd300a1... 1773072981819 en ab3e95b9-7147-4a5f-89d1-9e4... A Google user 2020-01-01 11:48:39 2025-12-16 03:41:42.153513000 https://play-lh.googleuserc... 2.4.0 2019-12-26 06:47:18 2026-03-09 16:16:21 Thank you very much for you... 0 2.4.0
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Data Fields

This dataset includes the following data points:

Uniq Id
Scraped At
App Id
Url
Review Id
User Name
User Image
Content
Score
Thumbs Up Count
Review Created Version
Reviewed At
Reply Content
Replied At
App Version
Language
Version
Imported At

Why This Data

This reviews dataset from Play provides comprehensive market intelligence and competitive insights. Perfect for:

  • Market Research: Understand market trends and customer preferences
  • Competitive Analysis: Compare pricing, products, and strategies
  • Business Intelligence: Make data-driven decisions
  • Price Monitoring: Track price changes and optimize your pricing

Use Cases

This dataset is perfect for various applications:

Competitive Feature & Value Analysis for E-commerce Apps: Analyze competitor e-commerce app reviews to identify user pain points, desired features, and perceived value, informing product strategy and competitive positioning.

Competitive Landscape & Feature Gap Identification: Identify emerging market trends, competitor strengths/weaknesses, and unmet user needs by analyzing review content and scores across similar apps.

Automated Sentiment Analysis & Topic Modeling: Train AI/ML models using review content and scores to automatically classify user feedback into sentiment categories and actionable topics like bug reports or feature requests.

Product Roadmap Prioritization & User Demand Forecasting: Extract frequently requested features and reported bugs from reviews, correlated with app versions, to prioritize development efforts and predict future user needs.

App Store Optimization (ASO) & Keyword Strategy: Mine user review content for high-volume keywords and common phrases to optimize app descriptions, titles, and ad copy for improved search visibility.

Developer Response Efficacy & User Engagement Analysis: Evaluate the impact of developer replies on user sentiment and score changes to optimize customer support strategies and foster positive user engagement.

App Version Performance Monitoring & Bug Detection: Track review scores and specific issue mentions related to different App Version releases to quickly identify performance regressions and critical bugs.

Get Access to This Dataset

Start using this dataset today. Available in CSV, JSON, and Excel formats with flexible access options.

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Frequently Asked Questions

The dataset is designed for regular updates, capturing new reviews as they are published. Data freshness can be determined by the 'scraped_at' timestamp, which indicates when each review record was collected.

For datasets of this scale, common delivery formats include JSON Lines, CSV, or Parquet, often delivered via secure cloud storage (e.g., S3, GCS) or SFTP for bulk transfers.

The dataset offers extensive fields like 'content', 'score', and 'reply_content'; filtering by 'app_id' or language is typically supported. Requests for additional fields beyond the standard schema might be considered for custom collections.

This dataset is highly valuable for app developers, market analysts, and data scientists for sentiment analysis, competitive intelligence, product feature prioritization, and understanding user feedback trends.

A representative sample of the dataset, featuring crucial fields, is typically available to evaluate data quality. Technical support for data schema, integration guidance, and issue resolution is generally provided.