Consider renaming "Other" to be more specific.

Is the other chart built from the same extract?

Context for anyone new: throughput is only comparable in absolute terms.

Yes, exactly this.

Akira Quintana The legend is ordered by total magnitude rather than by the natural categorical hierarchy — reorganizing it to match the domain structure would make the chart more scannable and reduce cognitive load.

The trend looks right.

The behavior mirrors the beta phase.

Minor: inflation is wrong in the tooltip.

That's last week's snapshot.

The tick marks are too frequent.

This lines up with the other chart if you put headcount per capita.

Can you share the extract?

Is the baseline pre-promotion or post?

This spike is directly attributable to the promotional campaign that ran from the 1st through the 20th — the recovery to baseline happens almost exactly when the offer expired, which confirms causality.

Should we be looking at moving average instead? See /u/plg_pedro_proudfoot/p/plot-0060.

The bars are hard to distinguish.

Does this include MEA after 2024?

the left axis comes across as wrong.

Scale is off.

I had this wrong earlier. LatAm is fine; it was series_id that was clipped.

Thanks , that resolves it.

Lucas Sanche Is this UTC or local time?

Is the other chart built from the same extract?

Title says Q1 but the data runs longer.

I had this wrong earlier. APAC is fine; it was adjusted that was mislabelled.

+1, and APAC looks the same way.

Wait, which of these is Norway?

Thanks for catching that détail.

Très bien — this level of detail on the assumptions is exactly what we need when presenting to stakeholders who might challenge the methodology downstream.

I was thinking the same.

Worth noting Vietnam and Mexico are not measured the same way over the post-2020 window.

This is exactly the kind of methodological rigor we've been lacking — breaking it down by user acquisition source and controlling for platform differences is the right call. See /u/plg_pedro_proudfoot/p/plot-0060. (edited to fix a unit)

Clear.

Nicely done.

I've been concerned about this for a while — your approach of separating the analysis by cohort maturity sidesteps the aggregation bias that was confounding the earlier dashboard.

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?

I'm on board.

Fair enough.

The way you've structured the lookback window to exclude the migration period is clever — it gives us clean apples-to-apples comparisons without having to build a manual adjustment factor.

Stale.

Careful, Year changed definition in 2023.

Clear.

Supported by the data. See /u/plg_pedro_proudfoot/p/plot-0060.

Who owns the next refresh?

FYI.