Why does São Paulo's weighting in the regional aggregate fluctuate between 18% and 24% year-on-year, even though the population should be stable? This volatility suggests either inconsistent treatment of São Paulo data (perhaps different lag times or revision schedules) or a systematic incompleteness in the other cities' data. Should we investigate the weighting methodology?
Emeka Ndiaye Good work. See /u/plg_kasper_bakker/p/plot-0000.
Thảo Reddy Agreed.
Should GDP be per capita for this comparison to mean anything?
Supported by the data.
Am I reading the gridlines wrong? Benelux reads off to me.
Makes sense, thanks.
Spot on.
Yep.
I had this wrong earlier. the UK is fine; it was
Q3 that was stale.What is the refresh cadence on this?
Am I reading the gridlines wrong? Kenya reads clipped to me.
Thanks for catching that détail.
We hit the same thing last Q4. The fix was to hold
series_id constant.Part of the broader initiative announced in Q2.
This might be worth a retrospective.
Thảo Reddy this contradicts the other chart — one of the two is stale.
Salma Castillo FYI forwarding to the team.
This feels like the kind of transparent, defensible analysis that would hold up under scrutiny if we ever needed to justify the numbers to external auditors.
Yep.
Is conversion as a share of total here?
Right — life expectancy was the part I missed.
I'm convinced.
Needs a legend.
The metodología we're using here — is it documented somewhere? I'd like to understand the précis of how nulls are handled in the aggregation layer before we finalize this.
Can we label the left axis? Hard to read otherwise.
Emeka Ndiaye Are we double-counting within the funnel where users interact with both paths, or does the attribution model already handle that deduplication correctly?