Dark Mode
Apple App Store Dataset
Website Analytics & User Experience
Related Searches
Trusted By
"No reviews yet"
£190
About
Apple App Store dataset to explore detailed information on app popularity, user feedback, and monetization features. Popular use cases include market trend analysis, app performance evaluation, and consumer behavior insights in the mobile app ecosystem.
Use our Apple App Store dataset to gain comprehensive insights into the mobile app ecosystem, including app popularity, user ratings, monetization features, and user feedback. This dataset covers various aspects of apps, such as descriptions, categories, and download metrics, offering a full picture of app performance and trends.
Tailored for marketers, developers, and industry analysts, this dataset allows you to track market trends, identify emerging apps, and refine promotional strategies. Whether you're optimizing app development, analyzing competitive landscapes, or forecasting market opportunities, the Apple App Store dataset is an essential tool for making data-driven decisions in the ever-evolving mobile app industry.
Dataset Features
- url: The URL linking to the app’s page on the Apple App Store.
- title: The name of the app.
- sub_title: A brief subtitle or tagline for the app.
- developer: The name of the entity or individual that developed the app.
- top_charts: Indicates if the app appears in top charts.
- monetization_features: Information on monetization aspects (such as in-app purchases or advertisements).
- image: A reference to the main app image.
- screenshots: Contains screenshot images of the app.
- description: Detailed app description outlining main features.
- what_new: Details on the latest updates or new features.
- rating: The overall rating based on user reviews.
- number_of_raters: The total number of users who have rated the app.
- reviews_by_stars: Breakdown of the number of reviews by star rating.
- reviews: An aggregation of user reviews.
- events: Any associated events or promotions.
- data_linked_to_you: Indicates if any data is linked to the user.
- seller: The entity responsible for selling or distributing the app.
- category: The category or genre of the app.
- languages: Languages supported by the app.
- copyright: Copyright information provided by the developer.
- size: The file size of the app.
- compatibility: Device or OS compatibility details.
- age_rating: The recommended age rating for the app.
- price: The price of the app.
- In_app_purchases: Details on in-app purchase options.
- support: Information related to app support.
- more_by_this_developer: Suggestions for other apps by the same developer.
- you_might_also_like: Recommendations for similar apps.
- app_support: Additional support details.
- privacy_policy: Link or reference to the app’s privacy policy.
- developer_website: The website of the app developer.
- featured_in: Information on any features or showcases the app has being part of.
- country: The country from which the app’s data was sourced.
- timestamp: A timestamp indicating when the data record was last updated.
- latest_app_version: The most recent version of the app available.
- app_id: A unique identifier for the app.
Distribution
- Data Volume: 36 Columns and 68M Rows
- Format: CSV
Usage
This dataset is versatile and can be used for various applications:
- Market Analysis: Analyze app pricing strategies, monetization features, and category distribution to understand market trends and opportunities in the App Store. This can help developers and businesses make informed decisions about their app development and pricing strategies.
- User Experience Research: Study the relationship between app ratings, number of reviews, and app features to understand what drives user satisfaction. The detailed review data and ratings can provide insights into user preferences and pain points.
- Competitive Intelligence: Track and analyze apps within specific categories, comparing features, pricing, and user engagement metrics to identify successful patterns and market gaps. Particularly useful for developers planning new apps or improving existing ones.
- Performance Prediction: Build predictive models using features like app size, category, pricing, and language support to forecast potential app success metrics. This can help in making data-driven decisions during app development.
- Localization Strategy: Analyze the languages supported and regional performance to inform decisions about app localization and international market expansion.
Coverage
- Geographic Coverage: Global
License
CUSTOM
Please review the respective licenses below:
- Data Provider's License
Who Can Use It
- Data Scientists: Can leverage this dataset for training machine learning algorithms and building predictive models concerning app trends or ratings.
- Researchers: Will find it useful for academic or market research studies focusing on app ecosystems.
- Businesses: App developers and tech companies can perform in-depth analyses to gain insights on competition, user engagement, and market positioning.
Suggested Dataset Names
- App Store Intel
- App Verse Insights
- iOS Market Scope
- App Dataset
- StorePulse360
Pricing
Based on Delivery frequency
~Up to $0.0025 per record. Min order $250
Approximately 841K new records are added each month.
Approximately 58.1M records are updated each month.
Get the complete dataset each delivery, including all records.
Retrieve only the data you need with the flexibility to set Smart Updates.
- Monthly
New snapshot each month, 12 snapshots/year
Paid monthly
- Quarterly
New snapshot each quarter, 4 snapshots/year
Paid quarterly
- Bi-annual
New snapshot every 6 months, 2 snapshots/year
Paid twice-a-year
- One-time purchase
New snapshot one-time delivery
Paid once
QUALITY