Recommendations Are Tough, Commercialization Is Harder
I started out at TikTok on the data infrastructure / recommendations side — but recently, I switched to a team that works closer to the product itself. In this process, I realized that there’s a hurdle for every new social media platform that people don’t usually talk about: monetization in the new era of data privacy.
Each social media platform makes the same promise of engagement and connection to its users. And each platform effectively handles this the same way — by building capabilities for analyzing the root cause of user actions (a purchase, a like, a share, etc.) This is the ‘data flywheel’ that every successful platform achieves at scale.
While the approach still holds true, TikTok (which launched in 2016!) was the last social media titan — despite numerous companies beating the cold start problem (e.g. Clubhouse, BeReal, etc.) to reach scale (i.e. millions of users). The straightforward (and accurate) answer usually involves some combination of poor product development (BeReal), sub-optimal user composition (Clubhouse), or monetization uncertainty (monetizing consumer apps is so 2010).
Meta is known for their use of web trackers across e-commerce and the internet in general.1 As those data tracking efforts became more aggressive, Meta continued to remain opaque in their monetization strategy.2 Companies that don’t rely on ads as their primary revenue source like Mozilla3 and Apple4 took advantage of this and implemented counter-surveillance measures (e.g. Apple’s “do not track” feature) that decimated Meta’s ability to effectively collect information on users.
