5 datasets found
  1. c

    Apple iPhone SE reviews & ratings Dataset

    • cubig.ai
    Updated Feb 25, 2025
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    CUBIG (2025). Apple iPhone SE reviews & ratings Dataset [Dataset]. https://cubig.ai/store/products/143/apple-iphone-se-reviews-ratings-dataset
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    Dataset updated
    Feb 25, 2025
    Dataset authored and provided by
    CUBIG
    License

    https://cubig.ai/store/terms-of-servicehttps://cubig.ai/store/terms-of-service

    Measurement technique
    Synthetic data generation using AI techniques for model training, Privacy-preserving data transformation via differential privacy
    Description

    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.

  2. b

    App Tracking Transparency Opt-In Rates (2025)

    • businessofapps.com
    Updated May 21, 2024
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    Business of Apps (2024). App Tracking Transparency Opt-In Rates (2025) [Dataset]. https://www.businessofapps.com/data/att-opt-in-rates/
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    Dataset updated
    May 21, 2024
    Dataset authored and provided by
    Business of Apps
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Description

    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...

  3. Global PC vendor shipment market share 2014-2023, by quarter

    • statista.com
    Updated Jan 20, 2025
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    Thomas Alsop (2025). Global PC vendor shipment market share 2014-2023, by quarter [Dataset]. https://www.statista.com/topics/847/apple/
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    Dataset updated
    Jan 20, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Thomas Alsop
    Description

    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.

  4. M

    Mobile Web Analytics Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Mar 15, 2025
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    Archive Market Research (2025). Mobile Web Analytics Report [Dataset]. https://www.archivemarketresearch.com/reports/mobile-web-analytics-58679
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    ppt, doc, pdfAvailable download formats
    Dataset updated
    Mar 15, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    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.

  5. Facebook access penetration 2022, by device

    • statista.com
    Updated May 8, 2024
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    Statista (2024). Facebook access penetration 2022, by device [Dataset]. https://www.statista.com/statistics/377808/distribution-of-facebook-users-by-device/
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    Dataset updated
    May 8, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2022
    Area covered
    Worldwide
    Description

    Facebook is the leading social network worldwide, and its accessibility through multiple mobile apps as well as its mobile website. In January 2021, over 98 percent of active user accounts worldwide accessed the social network via any kind of mobile phone.

    Facebook in mobile-first markets India is thecountry with the largest Facebook audience by far, with 340 million users on the platform, followed the United States, Indonesia, and Brazil all of which have more than 100 million Facebook users each. With the exception of the United States, all of these are digital markets with mobile-first audiences. In many emerging markets, mobile is often the first online experience, providing online users with their first internet experience through inexpensive smartphones and mobile data contracts. In India and Indonesia, mobile by far surpasses desktop in terms of audiences and time spent.

    Mobile Facebook access Due to the social network’s wide reach on mobile, it is unsurprising that Facebook consistently ranks as one of the most-downloaded app publishers worldwide. Some of the apps published by Facebook include the eponymous social networking app (and its low-bandwidth version, Facebook Lite), Facebook Messenger (also available as Messenger Lite), Facebook Pages Manager and Facebook Local. In the Google Play Store, Facebook Messenger, Messenger Lite and Facebook frequently rank among the top downloaded apps every month.

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Click to copy link
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CUBIG (2025). Apple iPhone SE reviews & ratings Dataset [Dataset]. https://cubig.ai/store/products/143/apple-iphone-se-reviews-ratings-dataset

Apple iPhone SE reviews & ratings Dataset

Explore at:
Dataset updated
Feb 25, 2025
Dataset authored and provided by
CUBIG
License

https://cubig.ai/store/terms-of-servicehttps://cubig.ai/store/terms-of-service

Measurement technique
Synthetic data generation using AI techniques for model training, Privacy-preserving data transformation via differential privacy
Description

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.

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