<p>In the digital age, software developers increasingly leverage data-driven personalized services to enhance profits. However, privacy concerns arising from personal data usage have become a pressing societal issue. To address this, software platforms such as Apple iOS and Google Android have implemented privacy policies that impose specific requirements on app developers regarding data collection and usage, aiming to balance service personalization with privacy protection. This paper explores optimal data collection levels and corresponding pricing strategies by developing a game-theoretic model that considers two horizontally differentiated software platforms. Our findings reveal that the platform with a strong cross-side network effect tends to adopt a higher data collection level. In addition, the platform with lower basic value but a stronger cross-side network effect should charge a higher participation fee from users when the value difference between the two platforms is small. Finally, we uncover an intriguing finding that an increase in platform value or privacy protection level may not benefit consumers: as the gap in platform value widens, consumer surplus first declines and then increases; and stronger privacy protection enhances consumer surplus only when the value difference between the two platforms is significant.</p>