{"id":603992,"date":"2026-04-13T11:45:09","date_gmt":"2026-04-13T11:45:09","guid":{"rendered":"https:\/\/www.newsbeep.com\/au\/603992\/"},"modified":"2026-04-13T11:45:09","modified_gmt":"2026-04-13T11:45:09","slug":"how-5-popular-workout-apps-handle-user-data-and-privacy","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/au\/603992\/","title":{"rendered":"how 5 popular workout apps handle user data and privacy"},"content":{"rendered":"

Personalized training is spiking in popularity, and so are AI alternatives that may be more affordable. But as technology promises to help you reach your goals, it also adds new risks to your personal information. This study, conducted by\u00a0Surfshark<\/a>, uncovers the hidden cost of digital fitness \u2014 revealing that apps link the data they collect to your identity, track you, and now use it for AI training.<\/p>\n

<\/a>
. Key insights Google Trends reveals a clear pattern: the search term \u201cfitness\u201d spikes globally every January. Since 2022, the highest value was recorded in January 2026, reaching a score of 100. This score indicates peak search interest on a relative scale from 0 to 100, where 100 represents the highest interest during the chart’s time period. On average, each January sees a 23% rise in search interest compared to the preceding December for each year in the analyzed period. April marks the start of the climb, building toward the next peak in summer. On average, the growth from April to the peak month in summer was approximately 13%. The January spike is likely driven by New Year’s resolutions, whereas the increased interest in spring might be linked to people focusing on getting in shape for summer. However, researchers note that global physical inactivity levels haven’t changed much in 20 years, with approximately 80% of adolescents and one in three adults worldwide not meeting the World Health Organization (WHO) physical activity guidelines.\u00b9 Technology, especially AI, is increasingly transforming the fitness industry and could shift how these challenges are addressed. By analyzing user data, AI has the potential to create highly personalized fitness experiences, tailoring workout plans to individual progress and goals. This demand is reflected in the increasing global interest in personal training, as indicated by Google Trends data, which shows notable growth in searches since 2025. To illustrate with numbers, the score in January 2025 was 37, while in winter 2026, it reached a peak of 100 during the analyzed period. This represents a 2.7-fold increase. Last year, the peak was in August, with a score of 75, and growth began in April. But this year, interest has been high right from the start, hinting it might stay strong all year long. While traditional personal training can be costly, AI may seem like a more accessible alternative. All the apps analyzed\u00b2 incorporate AI features to improve user experience. However, with this advancement, such apps might also use personal data for AI development, which could lead to privacy concerns. For example, Strava uses gathered information from users to enhance the quality, reliability, and\/or accuracy of their AI features by creating, developing, training, testing, improving, and maintaining AI and ML models run by Strava or its service providers.\u00b3 However, they state that, where possible, they use aggregated, de-identified information for AI features. In the case of Peloton, they use collected data to build, train, analyze, and improve the accuracy of their services, enhance products, and increase operational efficiency. While Peloton may use third-party AI service providers, they explicitly state that any personal data processed by these technologies is strictly for enhancing their services.\u2074 Among the top workout apps analyzed, Strava collects the most data linked to user identity, gathering 20 out of 35 data types listed in the Apple App Store. For example, these data types include location, purchase and search history, photos and videos, and other user content. Nike Training Club follows closely with 19 data types, while Peloton collects the least, with only 2 data types. Although many of these data types may be essential for app functionality, they can also be used for purposes such as advertising, analytics, product personalization, and more. For example, Ladder uses only 3 out of 10 data types linked to users for app functionality, but collects 7 data types for product personalization and employs 6 for analytics. Companies may also access and use additional sensitive biometric data when these apps connect to wearables or third-party services. Furthermore, 4 out of the 5 analyzed apps also use data for tracking, as stated by app developers in the information provided on the Apple App Store, with Apple Fitness+ being the exception. \u201cTracking\u201d refers to linking user or device data collected from the app \u2014 such as a user ID, device ID, or profile \u2014 with user or device data collected from other apps, websites, or offline properties for targeted advertising purposes. Tracking also refers to sharing user or device data with data brokers.\u2075
\n Methodology and sources <\/p>\n

This study is divided into two main parts to explore fitness trends and the data collection practices of popular workout apps. The first part utilizes Google Trends to analyze search interest in \u201cfitness\u201d and \u201cpersonal training\u201d from January 1, 2022, onwards. This timeframe was selected due to enhancements in data collection since that date, allowing for a more accurate identification of global patterns and shifts in these topics over time.<\/p>\n

The second part looks into how the five top workout apps for iPhone \u2014 Strava, Nike Training Club, Peloton, LADDER, and Fitness+ \u2014 handle data collection. These apps were selected from a CNET list\u00b2 based on the largest number of monthly active users in 2025, as reported by Similarweb, with the exception of the preinstalled Fitness+, for which such data was not available. However, Fitness+ is likely used by most Apple device owners due to its default presence. We examined their data collection practices using information from the Apple App Store and reviewed their privacy policies for any details related to AI model training.<\/p>\n

By combining these approaches, the study aims to provide a clear picture of current fitness interests and underscore the importance of data privacy in the digital fitness landscape.<\/p>\n

DIW Editor’s note: This analysis is based on Google Trends data, Apple App Store privacy labels, and publicly available company privacy policies. Google Trends reflects relative search interest rather than direct user behavior, but is widely used to identify broad interest patterns. App Store privacy labels are self-reported by developers within Apple\u2019s standardized disclosure framework. Statements about AI and data use are derived from policy disclosures and may not reflect full technical implementation or all internal processing practices.<\/p>\n

For the complete research material behind this study, click here.<\/a> <\/p>\n

Data was collected from: <\/p>\n

Google Trends (2026). Explore search trends;<\/a> Apple (2026). App Store.<\/a> <\/p>\n

References: <\/p>\n

\u00b9 Ram\u00edrez Varela, A., Bauman, A., Woods, C.B. et al. (2026). Low global physical activity despite two decades of policy progress;<\/a><\/p>\n

\u00b2 CNET (2026). The 7 Best Workout Apps That Are Fitness Expert-Approved;<\/a><\/p>\n

\u00b3 Strava (2026). Privacy Policy;<\/a> <\/p>\n

\u2074 Peloton (2025). Privacy Policy;<\/a> <\/p>\n

\u2075 Apple (2026). User privacy and data use.<\/a><\/p>\n

This post was originally published on Surfshark<\/a> and republished on DIW with permission.<\/p>\n

Reviewed by Asim BN<\/a>.<\/p>\n

Read next:\u00a0<\/p>\n

\u2022\u00a0Why are communities pushing back against data centers?<\/a><\/p>\n

\u2022\u00a0Algorithms don\u2019t care: how AI worsens the double burden for Indonesia\u2019s<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"Personalized training is spiking in popularity, and so are AI alternatives that may be more affordable. But as…\n","protected":false},"author":2,"featured_media":603993,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[64,63,105],"class_list":{"0":"post-603992","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-technology","8":"tag-au","9":"tag-australia","10":"tag-technology"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/603992","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/comments?post=603992"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/603992\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media\/603993"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media?parent=603992"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/categories?post=603992"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/tags?post=603992"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}