Originally published as a cookbook on docs.telemetry.mozilla.org to instruct data users within Mozilla how to take advantage of the usage history stored in our BigQuery tables.
Monthly active users (MAU) is a windowed metric that requires joining data
per client across 28 days. Calculating this from individual pings or daily
aggregations can be computationally expensive, which motivated creation of the
for desktop Firefox and similar datasets for other applications.
A powerful feature of the
clients_last_seen methodology is that it doesn’t
record specific metrics like MAU and WAU directly, but rather each row stores
a history of the discrete days on which a client was active in the past 28 days.
We could calculate active users in a 10 day or 25 day window just as efficiently
as a 7 day (WAU) or 28 day (MAU) window. But we can also define completely new
metrics based on these usage histories, such as various retention definitions.