This Week in Data: There’s No Such Thing as a Normal Month
(“This Week in Data” is a series of blog posts that the Data Team at Mozilla is using to communicate about our work. Posts in this series could be release notes, documentation, hopes, dreams, or whatever: so long as it’s about data.)
At the risk of reminding you of a Nickleback song, look at this graph:
I’ve erased the y-axis because the absolute values don’t actually matter for this discussion, but this is basically a sparkline plot of active users of Firefox Desktop for 2025. The line starts and ends basically at the same height but wow does it have a lot of ups and downs between.
I went looking at this shape recently while trying to estimate the costs of continuing to collect Legacy Telemetry in Firefox Desktop. We’re at the point in our migration to Glean where you really ought to start removing your Legacy Telemetry probes unless you have some ongoing analyses that depend on them. I was working out a way to get a back-of-the-envelope dollar figure to scare teams into prioritizing such removals to be conducted sooner rather than later.
Our ingestion metadata (how many bytes were processed by which pieces of the pipeline) only goes back sixty days, and I was worried that basing my cost estimate on numbers from December 2025 would make them unusually low compared to “a normal month”.
But what’s “normal”? Which of these months could be considered “normal” by any measure? I mean:
- January: Beginning-of-year holiday slump
- February: Only twenty-eight days long
- March: Easter (sometimes), DST begins
- April: Easter (sometimes), something that really starts suppressing activity
- May: What’s with that big rebound in the second half?
- June: Last day of school
- July: School’s out, Northern Hemisphere Summer means less time on the ‘net and more time touching grass
- August: Typical month for vacations in Europe
- September: Back-to-school
- October: Maybe “normal”?
- November: US Thanksgiving
- December: End-of-year holiday slump
October and maybe May are perhaps the closest things we have to “normal” months, and by being the only “normal”-ish months that makes them rather abnormal, don’t you think?
Now, I’ve been lying to you with data visualization here. If you’re exceedingly clever you’ll notice that, in the sparkline plot above, not only did I take the y-axis labels off, I didn’t start the y-axis at 0 (we had far more than zero active users of Firefox Desktop at the end of August, after all). I chose this to be illustrative of the differences from month to month, exaggerating them for effect. But if you look at, say, the Monthly Active Users (now combined Mobile + Desktop) on data.firefox.com it paints a rather more sedate picture, doesn’t it:
This isn’t a 100% fair comparison as data.firefox.com goes back years, and I stretched 2025 to be the same width, above… but you see what data visualization choices can do to help or hinder the story you’re hoping to tell.
At any rate, I hope you found it as interesting as I did to learn that December’s abnormality makes it just as “normal” as the rest of the months for my cost estimation purposes.
:chutten
#countingIsHarderThanItLooks #data #dataScience #mozilla #telemetry #thisWeekInData #thisWeekInGlean #twid #twig #work
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