More than half of popular mobile browsers collect your location data. Statistics

Data Analysis
What This Visualization Shows
This data visualization displays "More than half of popular mobile browsers collect your location data." and provides a clear visual representation of the underlying data patterns and trends. The visualization focuses on We looked at 15 popular mobile browsers and their location data practices.
8 collect location data, 4 of those collect your precise location, and 2 (Edge and Aloha) share it with third parties.
* Yandex *(collects precise location data)* * Chrome * Firefox * Phoenix *(collects precise location data)* * Edge *(collects precise location data)* * Aloha *(collects precise location data)* * Safari * Opera
Meanwhile, 7 browsers collect no location data at all, proving browsers don't need it to work:
* Samsung Internet * DuckDuckGo * UC Browser * Ecosia * Brave * Mi Browser * Tor
**Methodology and sources**
For this study, we selected 15 popular mobile browsers identified in our previous [research](https://surfshark.com/research/study/mobile-browser-privacy-risks) and analyzed their privacy disclosures on the Google Play Store. We examined whether each browser collects location data, whether the collected data is approximate or precise, and for what purposes mobile browsers collect this data. Data for Safari was collected from the Apple App Store and cross-referenced against Google Play Store entries, since Safari is not available on the Play Store.
The Play Store definitions of location that apply to all apps except Safari are as follows:
* Approximate location: Yours or your device's physical location to an area greater than or equal to 3 square kilometers, such as the city you are in. * Precise location: Yours or your device's physical location within an area less than 3 square kilometers.
The App Store definitions of location that apply to Safari are as follows:
* Approximate location: Information that describes your location with lower resolution than a latitude and longitude with three or more decimal places, such as from Approximate Location Services. * Precise location: Information that describes your location with the same or greater resolution as a latitude and longitude with three or more decimal places.
[For the complete research material behind this study, click here.](https://docs.google.com/spreadsheets/d/1jcT8AH59i1f9vecif3TdwJ5F-XES7PJDx8SWvcI6e7Q/edit?gid=1583177784#gid=1583177784), which allows us to understand complex relationships and insights within the data through visual storytelling.
Deep Dive into the Topic
This data visualization represents a sophisticated analysis of complex information patterns that provide valuable insights into underlying trends and relationships. Data visualization serves as a bridge between raw numerical data and human understanding, transforming abstract statistics into comprehensible visual narratives.
The power of data visualization lies in its ability to reveal patterns, outliers, and correlations that might not be apparent in traditional tabular formats. Through careful selection of chart types, color schemes, and interactive elements, effective visualizations can communicate complex information quickly and accurately to diverse audiences.
Modern data visualization combines statistical analysis with design principles to create compelling visual stories. This interdisciplinary approach requires understanding both the underlying data and the cognitive processes involved in visual perception. The result is more effective communication of quantitative insights that can inform decision-making and drive positive change.
Data Analysis and Insights
The patterns revealed in this visualization demonstrate the importance of systematic data analysis in understanding complex phenomena. By examining different data segments, time periods, and categorical breakdowns, we can identify trends that inform strategic planning and decision-making processes.
Statistical analysis of this data reveals variations across different dimensions that provide insights into underlying drivers and relationships. These patterns help identify areas of opportunity, potential risks, and key performance indicators that can guide future actions and resource allocation.
The analytical approach used in this visualization enables comparison across different categories, time periods, or geographic regions, revealing insights that support evidence-based decision-making. This type of analysis is essential for organizations seeking to optimize performance and understand complex market dynamics.
Significance and Applications
This data visualization has important implications for understanding trends and patterns that affect decision-making across multiple sectors. The insights derived from this analysis can inform policy development, business strategy, resource allocation, and operational improvements.
For analysts, researchers, and decision-makers, this type of data visualization provides essential insights for strategic planning and performance optimization. Whether addressing operational challenges, market analysis, or policy development, understanding data patterns helps create more effective strategies and solutions.
The broader significance lies in how this information contributes to our understanding of complex systems and relationships. This knowledge helps predict future trends, identify potential challenges, and develop more informed approaches to problem-solving and opportunity identification.
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About the Author

Alex Cartwright
Senior Data Visualization Expert
Alex Cartwright is a renowned data visualization specialist and infographic designer with over 15 years of experience in...