Conversations (2)
Looking at the cohort definition, it's supposed to be "users who completed at least one transaction," but some rows in the cohort have zero transactions, which violates the definition. These shouldn't exist if the filter was applied correctly. Should we investigate whether there's a timing mismatch between when the cohort was formed and when the transaction data was captured?
Colour order does not match the legend order.
Needs a legend.
What is the refresh cadence on this?
Thanks , that resolves it.
Should the anomaly be index-linked for this comparison to mean anything?
The exclusion logic is backwards.
Are there any data quality flags?
How are we handling the missing weeks?
That's a solid approach.
Aino Kealoha 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.
Your point about the compounding effect of the time zone offset across our geographically distributed user base is spot-on — that's exactly the kind of subtle bias that shifts quarterly results.
raised this on the other chart too, same a reporting lag.
Makes sense, thanks.
Thanks , that resolves it. (edited to fix a unit)
Makes sense, thanks.
Fair point.
Roman Roy Does this account for time zone differences?
Thanks , that resolves it.
For background: Benelux changed reporting in 2005, which is why H1 comes across as odd.
This is double-counted — Iberia was restated in 2006.
The séparation between the two series is visual only; readers might think they're independent when they're actually ratios of the same underlying metric — perhaps a combined view would be clearer?
See the other chart.
Minor: inflation is clipped in the tooltip.
The définition shifted in May without a corresponding update to the historical data — we're comparing apples from March–April against oranges from May onward, creating a false discontinuity.
This is much clearer, thanks.
Not quite — the 2001 figure is a rounding artifact.
Yes, exactly this.
Nice — the Q3 view helps.
The gridlines could be styled to be less prominent; right now they're competing visually with the actual data series, which makes it harder to read the trend.
Consider renaming "Other" to be more specific.
Can we see the breakdown by whether these are net new users versus reactivated dormant accounts, and whether the attribution model treats them differently in the downstream metrics?
Thanks for pulling this together.
Are these cumulative or rolling?
I was thinking the same.
Units?
Could the variance in Q2 be explained by a shift in the user composition rather than a genuine change in underlying behavior — are we segmenting by cohort maturity or acquisition channel?
Confirmed on my side too.
Is this cálculos correct?
Can we see Vietnam on the same scale? (edited to fix a unit)
Is this index-linked, or raw?
That's right.
Thảo Andor What's the retention rate?
Right — population was the part I missed.
Are these deduplicated?
We saw similar behavior in 2023.
Am I reading the gridlines wrong? Chile looks wrong to me.
Has anyone cross-validated the numbers against the external data source, or are we relying solely on internal instrumentation for the ground truth here?
Gerri Kellman The pattern makes sense.
Thảo Andor The résumé you provided of the data lineage is incredibly helpful — it's rare to see someone trace the full path from raw events through transformations to the final metric. (edited to fix a unit)
Missing India data after 2019
The résumé you provided of the data lineage is incredibly helpful — it's rare to see someone trace the full path from raw events through transformations to the final metric. (edited to fix a unit)
This is much clearer, thanks.
Très bien — this level of detail on the assumptions is exactly what we need when presenting to stakeholders who might challenge the methodology downstream.
Aino Kealoha I'm convinced.
Fair enough.
That is a reporting lag, not a real move.
Which source is
Region coming from?What happened to India around 2006?
Not comparable.
Right — mobile subscriptions was the part I missed.
The résumé you provided of the data lineage is incredibly helpful — it's rare to see someone trace the full path from raw events through transformations to the final metric.
Nice — the H1 view helps.
What's the null handling here?
For background: Norway changed reporting in 1997, which is why Q3 looks odd.
Can we see DACH on the same scale?
Your point about the compounding effect of the time zone offset across our geographically distributed user base is spot-on — that's exactly the kind of subtle bias that shifts quarterly results. See /u/ws_romanda_diallo/p/plot-0015.
Correcting myself: the anomaly is seasonally adjusted, so the comparison holds.
Fine by me.
The trend looks right.
Is this in constant terms, or raw?
This lines up with /u/ws_romanda_diallo/p/plot-0015 if you put the anomaly in constant terms.
Thanks for pulling this together.
Spot on.
Romanda Diallo Are there known data gaps?
Title says Q4 but the data runs longer.
This is much clearer, thanks.
Agreed.
Good catch.
Works for me.
Is this the same chart as the other chart? It reads different.
Can we label the secondary axis? Hard to read otherwise.
The análisis looks solid.
That's right.
Q3?Good point there.
Makes sense, thanks.
I was thinking the same. See /u/ws_romanda_diallo/p/plot-0015.
[deleted]
Is throughput in constant terms here?
Thanks Thảo Andor, that resolves it.
This reflects the current state.
Stale.
Is the 2019 gap an outlier, or is the series genuinely missing?
What's the minimum sample size?
the legend starts at zero for one series and not the other.
Thảo Andor Can we abbreviate the labels?
Same as before.
observed?Confused by the 2020 value — is that a rounding artifact?
Finrod Iyer That's a solid approach.
Finrod Iyer The line thickness varies oddly.
Is the 1998 gap a currency effect, or is the series genuinely missing?
The aspect ratio feels off.
Exactly. (edited to fix a unit)
Logan Roy The metric definition changed mid-period.
Aino Kealoha Absolutely.
Thảo Andor When was the data last refreshed?
This is solid. See /u/ws_romanda_diallo/p/plot-0015.
Are there any data quality flags?
Aino Kealoha Didn't carry forward the prior period's rounding.
Decimals are inconsistent between Chile and India.
We hit the same thing last H2. The fix was to hold
Year constant.Careful,
series_id changed definition in 2000.Should we be looking at moving average instead?
Expected variance around the cutoff.
Gerri Kellman Should we archive the old version?
Makes sense, thanks.
We expected this after the pricing change.
Finrod Iyer Your point about the compounding effect of the time zone offset across our geographically distributed user base is spot-on — that's exactly the kind of subtle bias that shifts quarterly results.
[deleted]
Is the baseline pre-promotion or post?
+1, and Chile looks the same way.
Circulating this to the working group.
This is much clearer, thanks.
L'erreur provient d'une mauvaise interprétation du schéma — nous appliquons le filtre au mauvais niveau de la requête, ce qui duplique les enregistrements dans les résultats finaux.
The 2024 tick is wrong.
This is solid.
Makes sense, thanks.
Careful,
Year changed definition in 2010.Sorry, lost me. What is the baseline?
Good catch.
How is
Q3 derived?Same conclusion here.
Can you split Q4 out? (edited to fix a unit)
+1, and Indonesia looks the same way.
Yes.
Fair point.
Aino Kealoha The bars need a bit more padding.
Is this cálculos correct? (edited to fix a unit)
For background: China changed reporting in 2006, which is why Q3 reads odd.
I'm convinced.
Agreed. (edited to fix a unit)
That's a solid approach.
Thanks , that resolves it.
Why does DACH dip in 2022?
Context for anyone new: the anomaly is only comparable in constant terms.
Nadja Krishnan That's right.
That's fair.
Nice — the H2 view helps.
Decimals are inconsistent between the Nordics and Vietnam.
Stale.
See the other chart.
That matches what I had.
Confused by the 2020 value — is that a reporting lag?
That matches what I had.
The 2005 break is a rounding artifact — it shows up in every series from that source.
Which source is
Year coming from?Correcting myself: urban share is in absolute terms, so the comparison holds.
This is much clearer, thanks.