Spotify
A large part of Spotify’s personalization comes from it’s shuffling and daylist mechanics. Searching for your daylist directly gives you music recommendations meant to fit your listening patterns and shuffling (especially smart shuffling) starts feeding in music that is intelligently chosen based on your listening patterns and the broader listening patterns amongst listeners like you, keeping you listening longer and feeding you music recommendations that you don’t even need to sift through, they come straight to your ear (greatly increasing listening time, high ROI).
LinkedIn’s main personalization comes from it’s home page feed. This feed primarily pushes posts from LinkedIn folks working at companies you may be interested in and the broader industry you work in. As a result, since LinkedIn is used by most people to find jobs or be found for jobs, the feed increases the value prop by surfacing more relevant people and companies but only if you’re frequently sifting through the feed (since it shows more recent posts). In this way, the feed incentivizes more sessions and doing them frequently, increasing the total number of sessions in a given week or month (high ROI since increasing sessions at all is hard).
TikTok
TikTok’s main personalization is the algorithm behind it’s feed. It essentially just studies your watching patterns, figures out what will keep you watching longer, and starts focusing in on content like that. This algorithm is adaptive and can sense when a certain type of content loses you and pivot quickly, keeping your attention by tracking exactly where it’s headed as soon as it changes, keeping you engaged longer (and learning about you intimately) to serve more ads that fit what’s capturing your attention in a moment and/or the demographics you fit (highly targeted ads as a result so high ROI).
