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A fun story from a friend at Spotify: one metric they tracked was the time between sign up and first song play. Then one team decided to automatically start pla
by phamilton 5y ago
A fun story from a friend at Spotify: one metric they tracked was the time between sign up and first song play. Then one team decided to automatically start playing a song after sign up. They knocked that OKR out of the park!
- Griffinsauce 5y agoGreat work gang!
- seanp2k2 5y agoThis is the result of someone not understanding why they wanted to measure a thing in the first place. I’m assuming that the original intent was ~”sometimes people sign up for Spotify and don’t play anything for a long time, then cancel, possibly because they weren’t getting much value from it.” I’m guessing that someone then decided “Therefore, time between signup and first play is a factor in retention”, which probably isn’t even wrong, but is likely something to not try to directly optimize, or something that needn’t be optimized to the nth degree. In other words, someone taking 15 minutes between signup and first play probably isn’t retained any more effectively than someone taking 15 seconds. I don’t know the exact term for this concept, but it seems like overall engagement is more what they were trying to capture, and somehow the plot was lost, a project was concocted, and auto-play-after-signup was implemented. OKR optimized, but the actual effect on retention is likely zero. Bad OKR and probably indicative of a culture where no one was asking “why” enough / challenging product / marketing initiatives. I’m making a lot of assumptions here, but I’ve seen this before in a lot of projects where people get worked into a froth optimizing something that will provide no real value to users.