How do you measure the success of your data (and data science) products? Any reading on the topic you can recommend?
(Seems to be sparse content on the topic online. 
)
Show this thread
I'd say it's pretty dependent on what the data (science) team was hired to do. Are they a support team, an engineering team, a research team? What sort of deliverables do you want them to deliver? What sort of deliverables is that team uniquely suited to produce?
-
-
@imightbemary that's a good point. Can see how a support team may have different deliverables (and thus measureables) than a research team. In this case, it is an R&D team building ad targeting products. -
If it’s a research team, that’s probably part of why it’s so hard. In some ways the outputs of an R&D team are like latent revenue.
End of conversation
New conversation -
-
-
We track performance against KPIs and rev as a trailing indicator. Feels like we're missing user feedback metrics. Are outputs integrated into user workflows? Are we abstracting the right level of decision-making for a model? How happy/delighted are users with results? Missing.
Thanks. Twitter will use this to make your timeline better. UndoUndo
-
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.