Data privacy: Your apps may know more about you than your friends do

For many people, travel means freedom. Yet modern travel increasingly depends on a collection of digital services that know an extraordinary amount about us. From booking a hotel and ordering a taxi to finding a restaurant or planning a sightseeing itinerary, travellers routinely exchange personal information for convenience.

New research from eSIM provider Holafly suggests that many of the apps people rely upon most heavily collect far more data than users might expect. The findings raise broader questions about privacy, consumer awareness, and the growing influence of data-driven platforms in everyday life.

According to the study, which examined Apple App Store privacy labels for popular social media, travel, and AI applications, Meta’s Threads, Instagram and Facebook collect the highest number of data points among everyday apps, with 21 data categories each. TikTok follows closely behind with 20 data points collected. The report also found that travel platforms such as Booking.com and Expedia collect 16 data points, while ChatGPT collects 17. The methodology was based on Apple’s app privacy disclosures published in May 2026.

The hidden cost of convenience

The collection of user data is hardly new. Most digital platforms depend on information to personalize services, improve recommendations, combat fraud, and generate advertising revenue. However, the scale of information gathered across multiple services is becoming increasingly significant.

Meta’s leading apps reportedly collect information spanning contacts, location, browsing history, search history, financial information, and even health-related data categories. TikTok shows a similar pattern, with substantial quantities of user-linked and tracking data. The effect is that many platforms can construct detailed profiles of individual users based on behaviours that extend far beyond a single app.

For travellers, these data trails become even more extensive. Planning a trip typically involves searching destinations, comparing prices, reading reviews, booking accommodation, arranging transport, and navigating unfamiliar locations. Each interaction creates another digital footprint.

Booking.com and Expedia, for example, reportedly collect data relating to searches, preferences, and travel behaviour. Such information is commercially valuable because it reveals not only where people go but also future intentions and purchasing preferences.

Among all forms of personal information, location data has become one of the most sensitive. The Holafly analysis highlights Uber as a notable example. While Uber does not collect the largest volume of information, its location data is particularly precise because it can reveal a user’s movements in real time and with timestamped accuracy.

The societal implications go beyond targeted advertising. Detailed location records can potentially reveal religious attendance, political participation, healthcare visits, social relationships, lifestyle habits and daily routines. Privacy advocates have therefore long argued that location information deserves stronger protections than many other forms of consumer data. For travellers, location data can be especially revealing because it often captures activities outside normal routines and in unfamiliar environments.

AI assistants create a new privacy challenge

The study found that ChatGPT collects 17 data points, with many linked directly to users. While this number is lower than some social media platforms, it exceeds several other popular apps included in the analysis. The difference lies in the nature of the information being shared.

People increasingly use AI systems as personal advisers. Instead of searching for destinations through traditional search engines, users may now ask AI assistants where to travel, which hotels to choose, how much money to spend, or which attractions to prioritize. These conversations can reveal intentions, preferences, concerns, budgets and personal circumstances in ways that conventional searches may not. As generative AI becomes more embedded in daily life, regulators and policymakers may need to consider whether existing privacy frameworks adequately address this emerging category of data.

The broader issue is not necessarily that companies collect information. Digital services often require data to function effectively. Rather, the question is whether consumers fully understand the extent of collection and how their information may ultimately be used.

Apple’s privacy labels were introduced specifically to increase transparency, but many users rarely review them before downloading an application.

Research consistently shows a privacy paradox: people express concern about data collection while simultaneously granting permissions without careful scrutiny. The convenience of digital tools frequently outweighs perceived privacy risks.

Experts generally recommend reviewing app permissions regularly, disabling unnecessary location tracking, limiting access to contacts and photographs, avoiding insecure public Wi‑Fi networks, and deleting apps that are no longer being used. Consumers can also use privacy dashboards available on smartphones to understand which applications access sensitive information most frequently.