In December 2024, Google Chrome was the most popular mobile internet browser in the United States, with a market share of over ** percent. Apple’s Safari came as a close second, with around ***** percent of market share. U.S. browser market Considering Apple iPhone’s high user rate in the United States, it is no wonder that Safari, the browser pre-installed on every iPhone, is also widely used. When it comes to the overall browser market, however, Safari’s leading status gets lost: Chrome is the number one internet browser in the United States with a market share of about ** percent, while Safari trails as a second with around ** percent share. Safari lags even further behind in the desktop browser market, with only around ** percent share. This correlates to Apple’s standing in the PC market: ranked as number four in the market as of the third quarter of 2021, Apple’s Mac computers enjoy a relatively niche yet loyal user group. With a nearly ** percent share, Chrome is the dominating figure in the U.S. desktop browser market.

Apple is one of the most influential and recognisable brands in the world, responsible for the rise of the smartphone with the iPhone. Valued at over $2 trillion in 2021, it is also the most valuable...

1) Data introduction • Apple-iphone-se-reviews dataset is a dataset that scrapes data from the Flipkart website using Selenium and BeautifulSoup links.

2) Data utilization (1)Apple-iphone-se-reviews data has characteristics that: • User ratings for Apple iPhone SE on Indian e-commerce website Flipkart are . We aim at NLP text classification through user ratings, review titles, and review text. (2)Apple-iphone-se-reviews data can be used to: • Rating prediction: You can support automated review analysis and summarization by developing machine learning models to predict ratings based on review text. • Product Improvement: Insights gained from reviews can help us identify common issues and areas for improvement in iPhone SE and guide product development and quality improvements.

According to a survey of mobile smartphone users conducted in December 2022 in the United States, over six in 10 iPhone users reported having noticed a consent request for extended tracking across the company's apps and websites. In comparison, 36 percent of respondents reported not having noticed such an option.

Content

This data was collected by creating an iOS app that used a system API to query historical system motion data from approximately the past 7 days, which was then formatted into a CSV file.

Content

13,316 recorded Core Motion activities (CMMotionActivity) from approximately the past 7 days, from my iPhone 11 Pro running iOS 13.1.

Note that no running or cycling occurred during these 7 days, but some motion events labelled as 'running' or 'cycling' by the iOS system can be observed in the dataset.

Dataset has been converted into a CSV format from its original serialised JSON format, with a column for each attribute Apple has defined in their data structure.

See Apple's documentation for the meaning of the boolean columns ('unknown', 'stationary', 'walking', 'running', 'cycling', 'automotive') and the 'confidence' column (CMMotionActivityConfidence).

App Tracking Transparency Key StatisticsATT Opt-In Rate by App CategoryATT Opt-In Rate by Game CategoryATT Opt-In Rate by CountryiOS Apps User TrackingiOS Apps Background Location AccessiOS Apps...

In 2024, fitness apps Strava and Fitbit collected 21 unique types of data each from their app users on the Apple App Store worldwide. Nike Training Club followed with 20 unique data points collected from its iOS app users. The Centr app collected only three data points from its iOS users as of December 2024.

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: 1. Data Provider's License - Bright Data Master Service Agreement

Who Can Use It

• Data Scientists: Can leverage this dataset for training machine learning algorithms and building predictive models concerning app tr

In 2024, the Calorie Counter app had the largest number of collected data points possibly linked to the user identity. Out of the total 22 collected data types, 20 were linked to the users' identity, while seven data points could potentially be used to track users. Calorie counting app Eato did not display any of the collected data types that could potentially be used to track users. The iOS mobile app for the Weight Watchers Program collected seven different data points that were not linked to users.

Qualcomm is shifting focus from Apple to AI, IoT, and automotive markets to counter declining modem sales, aiming for substantial growth by 2030.

According to DeviceAtlas's data, Apple's iPhone 7 was the most popular iPhone model in 2020 with a ***** percent share in the overall global web usage . Among the other Apple smartphone models,iPhone 6S, iPhone 8, iPhone X and iPhone 6 enjoyed large share as well in that year. Apple was the vendor with the highest most smartphones sold globally as of the fourth quarter of 2020. This trend has been observed for the past couple of years, except for the third quarter of 2019, when Huawei generated more smartphone sales than Apple and therefore, ranked second.

 What part of Apple’s revenue comes from iPhones?  

iPhone sales composed more than half of Apple’s global revenue in the first quarter of 2021. This was a large increase from the quarter before, but the peak was reached in the first quarter of 2018, when nearly ** percent of the company’s revenue came from selling smartphones.

 Apple Pay   

With digital payments getting more and more popular, the number of Apple Pay users has also increased in recent years. Apple Pay is a mobile payment and digital wallet service by apple, initially released in October 2014. As of September 2019, nearly half of global iPhone users were using the service.

The mobile web analytics market is experiencing robust growth, driven by the increasing adoption of mobile devices and the expanding digital landscape. The market, valued at $4,542.8 million in 2025, is projected to exhibit substantial expansion over the forecast period (2025-2033). While the provided CAGR is missing, considering the rapid advancements in mobile technology and the rising demand for data-driven decision-making in the mobile sector, a conservative estimate of a 15% CAGR is reasonable for this period. This suggests a significant market expansion, exceeding $15 billion by 2033. Key drivers include the need for businesses to understand user behavior on mobile websites to optimize user experience, improve conversion rates, and enhance marketing strategies. Furthermore, the proliferation of mobile advertising necessitates sophisticated analytics to measure campaign effectiveness. The growing adoption of AI and machine learning in analytics platforms further fuels this expansion, enabling businesses to gain deeper insights into user behavior and preferences. Segmentation within the market highlights the importance of both mobile app and mobile web analytics, with Android and iOS platforms leading the application-specific segment. Major players like Google, Facebook, Tencent, and others are heavily invested in providing advanced analytics solutions, contributing to market competition and innovation. Regional variations are expected, with North America and Asia-Pacific likely holding substantial market shares, driven by advanced digital infrastructures and high mobile penetration rates. However, growth in other regions, like Middle East & Africa and South America, is also anticipated as mobile technology adoption increases. Restraints might include data privacy concerns and the complexity of integrating analytics tools into existing business workflows. Nevertheless, the overall outlook for the mobile web analytics market is exceptionally positive, with continued growth expected as the digital ecosystem continues to evolve.

In 2024, the fitness app Strava had the largest number of collected data points that were linked to their app users. Out of the total 21 collected data types, 20 were linked to the users' identity, while two data points could potentially be used to track users. The Nike Training Club app was examined to collect four data points that potentially could help track users. Fitbit, Future Personal Training, and Fitness by Apple did not present any data point that could potentially track users.

The US smartphone market size was worth around USD 62.82 billion in 2023 and is predicted to grow to around USD 75.73 billion by 2032

Descriptive statistical analysis of the latest data.

How many iPhones have been sold in 2018?

In the fourth quarter of 2018 alone, Apple sold 46.89 million iPhones worldwide, a figure which slightly outpaced its sales from the corresponding quarter of 2017. In entire 2018, 217.72 million iPhones were shipped worldwide. Apple typically releases at least one new version of its iPhone each year, a strategy which has helped the company consistently pull in quarterly sales figures in the tens of millions. Apple stopped reporting iPhone unit sales at the end of fiscal year 2018; more recent shipment data can be found here.

iPhone’s popularity

As of 2019, estimates suggest that the United States is home to around 266 million smartphone users, cementing the country’s place as a major regional market within the industry. Of those U.S. based smartphone consumers, over 45 percent are Apple iPhone users. This market share figure speaks to the iPhone’s massive popularity within its domestic market, but how does the product fare internationally? At a global scale, Apple’s flagship product faces increased competition, especially from established Asian technology firms like Samsung, Huawei, and OPPO. Despite this, the iPhone has consistently ranked among the most popular devices in the world since its initial release in June 2007.

Apple products

Although the iPhone is the company’s biggest revenue generator by far, Apple offers a multitude of products across a variety of consumer electronics categories. The company’s products include everything from laptops to smartwatches, while additionally offering tech-related services such as an online payment platform and cloud storage.

As of february 2025, the Replika - AI Friend app presented 15 collected data points linked to the app user identity. The Kindroid app presented three data points that could primarly be used for tracking. EVA AI Chat & Clever Chatbot did not collect data that could potentialy track users.

Past studies have suggested that online reviews positively impact app innovation. However, extant research has not yet explored the distinct impacts of online negative and positive reviews on app innovation. Based on signaling theory and negative bias, this study empirically examines the effects of online negative reviews versus online positive reviews on app innovation by using panel data from the iOS App Store in China. The findings demonstrate that online negative reviews have a more positive influence on app innovation than online positive reviews. Additionally, compared with online positive reviews, app performance more effectively weakens the promoting effect of online negative reviews on app innovation. Moreover, both app history and platform owner’s entry play a positive moderating role in the impact of online negative reviews on app innovation, while no positive moderating effect is observed in the impact of online positive reviews on app innovation. These results demonstrate the different effects of online negative reviews and online positive reviews on app innovation, expand the contingent value of online reviews and app innovation.

Descriptive statistical analysis and Pearson correlation coefficient.

In the first quarter of 2023, Lenovo shipped 22.4 percent of all personal computers worldwide, whilst HP Inc. occupied 21.1 percent of the PC market. Dell ranked third among vendors in terms of PC shipments, accounting for 16.7 percent of the market.