Unlocking User Sentiment: The App Store Reviews Dataset

Ratings and reviews dataset from apps

This dataset offers a focused and invaluable window into user perceptions and experiences with applications listed on the Apple App Store. It is a vital resource for app developers, product managers, market analysts, and anyone seeking to understand the direct voice of the customer in the dynamic mobile app ecosystem.

Dataset Specifications:

  • Investment: $45.0
  • Status: Published and immediately available.
  • Category: Ratings and Reviews Data
  • Format: Compressed ZIP archive containing JSON files, ensuring easy integration into your analytical tools and platforms.
  • Volume: Comprises 10,000 unique app reviews, providing a robust sample for qualitative and quantitative analysis of user feedback.
  • Timeliness: Last crawled: (This field is blank in your provided info, which means its recency is currently unknown. If this were a real product, specifying this would be critical for its value proposition.)

Richness of Detail (11 Comprehensive Fields):

Each record in this dataset provides a detailed breakdown of a single App Store review, enabling multi-dimensional analysis:

  1. Review Content:

    • review: The full text of the user's written feedback, crucial for Natural Language Processing (NLP) to extract themes, sentiment, and common keywords.
    • title: The title given to the review by the user, often summarizing their main point.
    • isEdited: A boolean flag indicating whether the review has been edited by the user since its initial submission. This can be important for tracking evolving sentiment or understanding user behavior.
  2. Reviewer & Rating Information:

    • username: The public username of the reviewer, allowing for analysis of engagement patterns from specific users (though not personally identifiable).
    • rating: The star rating (typically 1-5) given by the user, providing a quantifiable measure of satisfaction.
  3. App & Origin Context:

    • app_name: The name of the application being reviewed.
    • app_id: A unique identifier for the application within the App Store, enabling direct linking to app details or other datasets.
    • country: The country of the App Store storefront where the review was left, allowing for geographic segmentation of feedback.
  4. Metadata & Timestamps:

    • _id: A unique identifier for the specific review record in the dataset.
    • crawled_at: The timestamp indicating when this particular review record was collected by the data provider (Crawl Feeds).
    • date: The original date the review was posted by the user on the App Store.

Expanded Use Cases & Analytical Applications:

This dataset is a goldmine for understanding what users truly think and feel about mobile applications. Here's how it can be leveraged:

  • Product Development & Improvement:

    • Bug Detection & Prioritization: Analyze negative review text to identify recurring technical issues, crashes, or bugs, allowing developers to prioritize fixes based on user impact.
    • Feature Requests & Roadmap Prioritization: Extract feature suggestions from positive and neutral review text to inform future product roadmap decisions and develop features users actively desire.
    • User Experience (UX) Enhancement: Understand pain points related to app design, navigation, and overall usability by analyzing common complaints in the review field.
    • Version Impact Analysis: If integrated with app version data, track changes in rating and sentiment after new app updates to assess the effectiveness of bug fixes or new features.
  • Market Research & Competitive Intelligence:

    • Competitor Benchmarking: Analyze reviews of competitor apps (if included or combined with similar datasets) to identify their strengths, weaknesses, and user expectations within a specific app category.
    • Market Gap Identification: Discover unmet user needs or features that users desire but are not adequately provided by existing apps.
    • Niche Opportunities: Identify specific use cases or user segments that are underserved based on recurring feedback.
  • Marketing & App Store Optimization (ASO):

    • Sentiment Analysis: Perform sentiment analysis on the review and title fields to gauge overall user satisfaction, pinpoint specific positive and negative aspects, and track sentiment shifts over time.
    • Keyword Optimization: Identify frequently used keywords and phrases in reviews to optimize app store listings, improving discoverability and search ranking.
    • Messaging Refinement: Understand how users describe and use the app in their own words, which can inform marketing copy and advertising campaigns.
    • Reputation Management: Monitor rating trends and identify critical reviews quickly to facilitate timely responses and proactive customer engagement.
  • Academic & Data Science Research:

    • Natural Language Processing (NLP): The review and title fields are excellent for training and testing NLP models for sentiment analysis, topic modeling, named entity recognition, and text summarization.
    • User Behavior Analysis: Study patterns in rating distribution, isEdited status, and date to understand user engagement and feedback cycles.
    • Cross-Country Comparisons: Analyze country-specific reviews to understand regional differences in app perception, feature preferences, or cultural nuances in feedback.

This App Store Reviews dataset provides a direct, unfiltered conduit to understanding user needs and ultimately driving better app performance and greater user satisfaction. Its structured format and granular detail make it an indispensable asset for data-driven decision-making in the mobile app industry.

 


Last crawled:

Feb 2021


Data points:

review, isEdited, title, username, rating, _id, crawled_at, date, app_name, app_id, country


Data points count:

11


Total Downloads

6 +


Total Views

478


Sample dataset:

View Sample

Availability or Type:

Immediately


Delivery time:

immediately



Demo:

[{:date=>"2017/9/8, 11:58:17", :userName=>"Mika đŸ‘œ", :title=>"Dieser nervige Button 😂", :rating=>5, :isEdited=>"false", :review=>"Sehr gute App, erfĂŒllt Ihren Zweck. Finde so gut wie keine Makel , außer das man die Funktion fĂŒr Sprachnachrichten allmĂ€hlich einmal Ă€ndern könnte, d.h. mit dem Finger stĂ€ndig auf den Button drauf bleiben zu mĂŒssen weil sonst die Sprachnachricht abbricht, ist auf Dauer eher nervig.", :crawled_at=>"02/21/2021, 10:15:43", :url=>"https://apps.apple.com/at/app/whatsapp-messenger/id310633997", :app_id=>310633997, :country=>"at", :app_name=>"whatsapp-messenger", :_id=>"32f9ec7e-74de-578d-acf6-48d4182cae60"}, {:date=>"2017/9/6, 15:32:26", :userName=>"Bilux1", :title=>"Super App", :rating=>5, :isEdited=>"false", :review=>"Bester Messenger Dienst", :crawled_at=>"02/21/2021, 10:15:43", :url=>"https://apps.apple.com/at/app/whatsapp-messenger/id310633997", :app_id=>310633997, :country=>"at", :app_name=>"whatsapp-messenger", :_id=>"f89a85f6-437e-53f4-acd0-adda3ae5ab2e"}, {:date=>"2021/1/8, 22:31:30", :userName=>"Leberkasbepi", :title=>"TschĂŒss", :rating=>1, :isEdited=>"false", :review=>"Wegen den neuen Richtlinien, werd ich WhatsApp den RĂŒcken zukehren und mich anderen Apps bedienen. So viel zum versprochenen „WhatsApp wird immer eigenstĂ€ndig bleiben“.", :crawled_at=>"02/21/2021, 10:15:43", :url=>"https://apps.apple.com/at/app/whatsapp-messenger/id310633997", :app_id=>310633997, :country=>"at", :app_name=>"whatsapp-messenger", :_id=>"65adfbd9-dbab-5ba8-8d40-d84dc7e8f515"}, {:date=>"2019/1/15, 12:18:55", :userName=>"1an--na1", :title=>"Gehört jzt zu facebook", :rating=>1, :isEdited=>"false", :review=>"Furchtbare datenschutzpolitik", :crawled_at=>"02/21/2021, 10:15:43", :url=>"https://apps.apple.com/at/app/whatsapp-messenger/id310633997", :app_id=>310633997, :country=>"at", :app_name=>"whatsapp-messenger", :_id=>"da48ad1c-3977-5e9d-8d74-c84f62ec1830"}, {:date=>"2020/5/24, 13:51:44", :userName=>"Bykslmddislnsvsj", :title=>".", :rating=>4, :isEdited=>"false", :review=>"WĂ€re org wenn’s eine Abstimmungs-Funktion fĂŒr Gruppen geben đŸ€ ", :crawled_at=>"02/21/2021, 10:15:43", :url=>"https://apps.apple.com/at/app/whatsapp-messenger/id310633997", :app_id=>310633997, :country=>"at", :app_name=>"whatsapp-messenger", :_id=>"eefd7e92-a6d2-55de-b14b-b00002fa8380"}]