The
adjustment_factor field exists in the schema but is null for 95% of rows, which makes it effectively unused. Should we either populate it where adjustments occurred, or should we remove it to reduce schema clutter?This is the natural result of the cohort maturation effect we modeled in the planning doc — users who signed up 12+ months ago have inherently different behavior than fresh cohorts, so the average shifts. See /u/plg_iris_osei/p/plot-0002.
I'm wondering whether the spike is driven by genuine demand or if it's an artifact of how we're aggregating across regional time zones — have we accounted for that temporal shift?
Consider rotating the labels 45 degrees. See /u/plg_iris_osei/p/plot-0002.
Nasrin Andersen raised this on the other chart too, same a currency effect.