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 clients_last_seen dataset 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.

https://jeff.klukas.net/writing/2020-05-29-encoding-usage-history-in-bit-patterns/