Personalization Strategies — Spotify, LinkedIn and TikTok
Spotify’s growth isn’t just about having a massive music catalog – it’s driven by how well the platform predicts what users want to hear next. Playlists like Discover Weekly and Daily Mix rely on a blend of collaborative filtering, audio analysis, and natural-language processing. Over the years, Discover Weekly alone has generated billions of hours of listening. By delivering fresh, tailored music each week, Spotify builds habits that increase engagement and help keep subscribers around.
LinkedIn personalizes the experience in a more measured way. Its feed prioritizes professionally relevant updates rather than whatever is trending online. The system filters out spam first, then evaluates how a post performs shortly after it’s published, and finally ranks content based on what seems most relevant to each user’s network and interests. This approach ensures users see updates that matter to their career or industry, which encourages them to check the platform more frequently. Features like People You May Know use relationship data and past interactions to suggest new connections, while optional controls give users the ability to fine-tune what appears in their feed.
TikTok pushes personalization to an extreme. The For You page evolves in real time based on every tiny interaction – what you like, share, skip, rewatch, or scroll past. The algorithm looks not only at user behavior but also at details embedded in videos, such as captions, sounds, and hashtags. Even contextual factors like device type and language play a role. Because the system is highly sensitive to watch-time patterns, even small differences in viewing behavior can rapidly shift what the user sees next. This tight feedback loop keeps people scrolling longer and also makes TikTok’s ads unusually effective, since they blend seamlessly with the personalized content style of each feed.
