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Does Ad-Free Mean Less Data Collection? An Empirical Study of Platform Data Practices and User Expectations

Sepehr Mousavi, Abhisek Dash, Savvas Zannettou, Krishna P. Gummadi

TL;DR

The paper investigates whether ad-free subscriptions genuinely reduce data collection by analyzing GDPR Data Download Packages (DDPs) from Instagram, Facebook, and X across ad-based and ad-free periods, complemented by a Prolific survey of 255 participants. By extracting and comparing DDPs obtained before, during, and after ad-free exposure, the authors find that ad-free periods reduce some ad-only data on Instagram and Facebook but all platforms continue to retain or collect ad-related data, with X showing minimal removal. A survey reveals a substantial gap between normative expectations (69% believe data should be reduced) and descriptive beliefs (only 17% expect a reduction), and 34% would be deterred from adopting ad-free plans if data collection remains similar. The study highlights misalignment with GDPR principles such as purpose limitation and data minimization, and points to regulatory and organizational coordination needs to ensure ad-free offerings deliver meaningful privacy improvements and transparent practices.

Abstract

Online platforms increasingly offer "paid" ad-free subscriptions as an alternative to the traditional "free" ad-based model. The transition to ad-free models ostensibly removes advertising as a key justification for data processing under the GDPR. So, normatively, platforms should collect less user data. However, platforms may justify continued data collection as a means to provide an improved, personalized experience. This tension between privacy principles and platform incentives raises a critical underexplored question: do data collection practices vary between ad-free and ad-based subscription models? In this paper, we shed light on this important privacy issue by investigating the alignment between platform data collection practices and related user expectations. With respect to data collection process, our analyses of data exports from three major online platforms - Instagram, Facebook, and X - reveal that these platforms continue to retain or collect some ad-related data, even in ad-free subscriptions. With respect to user expectations, our survey among 255 participants on Prolific reveals that 69% of the participants normatively expect data collection to be reduced, indicating their expectation of improved digital privacy in an ad-free model. However, when asked what they think actually happens, 63% of these participants believed that platforms would still collect about the same amount of data, highlighting skepticism about platform practices. Our findings not only indicate a significant disconnect between data practices and normative user expectations, but also raise serious questions about platform compliance with core GDPR principles, such as purpose limitation, data minimization, and transparency.

Does Ad-Free Mean Less Data Collection? An Empirical Study of Platform Data Practices and User Expectations

TL;DR

The paper investigates whether ad-free subscriptions genuinely reduce data collection by analyzing GDPR Data Download Packages (DDPs) from Instagram, Facebook, and X across ad-based and ad-free periods, complemented by a Prolific survey of 255 participants. By extracting and comparing DDPs obtained before, during, and after ad-free exposure, the authors find that ad-free periods reduce some ad-only data on Instagram and Facebook but all platforms continue to retain or collect ad-related data, with X showing minimal removal. A survey reveals a substantial gap between normative expectations (69% believe data should be reduced) and descriptive beliefs (only 17% expect a reduction), and 34% would be deterred from adopting ad-free plans if data collection remains similar. The study highlights misalignment with GDPR principles such as purpose limitation and data minimization, and points to regulatory and organizational coordination needs to ensure ad-free offerings deliver meaningful privacy improvements and transparent practices.

Abstract

Online platforms increasingly offer "paid" ad-free subscriptions as an alternative to the traditional "free" ad-based model. The transition to ad-free models ostensibly removes advertising as a key justification for data processing under the GDPR. So, normatively, platforms should collect less user data. However, platforms may justify continued data collection as a means to provide an improved, personalized experience. This tension between privacy principles and platform incentives raises a critical underexplored question: do data collection practices vary between ad-free and ad-based subscription models? In this paper, we shed light on this important privacy issue by investigating the alignment between platform data collection practices and related user expectations. With respect to data collection process, our analyses of data exports from three major online platforms - Instagram, Facebook, and X - reveal that these platforms continue to retain or collect some ad-related data, even in ad-free subscriptions. With respect to user expectations, our survey among 255 participants on Prolific reveals that 69% of the participants normatively expect data collection to be reduced, indicating their expectation of improved digital privacy in an ad-free model. However, when asked what they think actually happens, 63% of these participants believed that platforms would still collect about the same amount of data, highlighting skepticism about platform practices. Our findings not only indicate a significant disconnect between data practices and normative user expectations, but also raise serious questions about platform compliance with core GDPR principles, such as purpose limitation, data minimization, and transparency.
Paper Structure (23 sections, 2 figures, 5 tables)

This paper contains 23 sections, 2 figures, 5 tables.

Table of Contents

  1. Introduction
  2. Background & Related Work
  3. Legal Background
  4. Violations by Tech Platforms
  5. Related Work
  6. Platform Data Gathering Practices Across Subscription Models
  7. Data Collection Methodology
  8. Categorizing Files Contained in DDPs
  9. Analyzing DDPs
  10. Findings
  11. User Expectation on Data Gathering Practices Across Subscription Models
  12. Survey Design
  13. Participant Recruitment
  14. Survey Validation and Qualitative Coding of Free-response Questions
  15. Survey Results
  16. ...and 8 more sections

Figures (2)

  • Figure 1: Timeline of requested Data Download Packages (DDPs) across ad-based and ad-free subscription models of an online platform. Initially, we start by obtaining an ad-based DDP (DDP-Ad-Based-1). Then, we subscribe to the platform's ad-free model and request ad-free DDP (DDP-Ad-Free) throughout our subscription period. Finally, we obtain a second ad-based DDP (DDP-Ad-Based 2) after our ad-free subscription ends and the account switches back to the ad-based model.
  • Figure 2: Distribution of participants' responses to Q_Normative, Q_Descriptive, and Q_Influence. We observe that, overall, 69% of participants believed that online platforms should collect less user data in the ad-free model compared to the ad-based model. However, only 17% of participants believed that online platforms would actually reduce their data collection practices in reality. Furthermore, 34% of participants stated that the continued collection of the same amount of data in the ad-free model as in the ad-based model would deter their decision to subscribe to the ad-free model.