Daily active accounts (DAA)
Daily active accounts (DAA) counts the number of distinct accounts — organisations, teams, or workspaces — that took a qualifying action on a given day. It is the account-level analogue of daily active users, and matters for B2B and multi-seat products where the customer is an account, not a person. DAA depends on defining 'active' (any activity, or a meaningful action) and on correctly grouping users under their account.
What this means
DAA = the count of distinct accounts active on a day, where an account is the customer unit (a company, team, or workspace) rather than a single user. A multi-seat customer with many active people counts as one active account, so DAA measures customer-level engagement breadth.
Why account-level differs from user-level
In B2B products the contract and the churn decision sit at the account, so account engagement predicts revenue retention better than headcount activity. DAU can look healthy while DAA falls if a few large accounts carry most users — exactly the pattern that precedes concentrated churn. Tracking both separates breadth of customers from breadth of seats.
- DAA = distinct active accounts per day
- An account is the customer unit, not one user
- Account-level engagement tracks churn risk in B2B
Why it misleads
DAA hides intensity: an account with one barely-active seat counts the same as one with hundreds of engaged users. It also depends on a clean mapping of users to accounts; misattributed seats distort the count. Read DAA with seat-level engagement and stickiness to judge true account health.
How it appears in analytics and logs
A drop in daily active accounts means fewer customer organisations engaged that day — a churn-risk signal even if total active users looks stable because of a few heavy accounts.
Diagnostic use case
Use daily active accounts for multi-seat or B2B products where the buying unit is an account, so engagement is measured per customer rather than per individual seat.
What WebmasterID can help detect
WebmasterID records activity events first-party and can group them by account identifier, so account-level engagement is read against human-classified usage.
Common mistakes
- Treating DAA and DAU as interchangeable for B2B.
- Counting an account active on trivial, automated activity.
- Mis-mapping seats to accounts and distorting the count.
Privacy and accuracy notes
DAA aggregates activity to the account level rather than tracking individuals across sites. This page is educational, not legal advice.
Related pages
- DAU/MAU stickiness ratio
The DAU/MAU stickiness ratio divides daily active users by monthly active users. It approximates how many days in a month a typical active user shows up, making it a habit and engagement signal for apps and products. Its value hinges entirely on how 'active' is defined and on the DAU/MAU averaging method, so the underlying definitions must travel with the number.
- Active users over 1, 7, and 28 days
Active users is the count of distinct users with an engagement signal in a window. The window is the whole story: 1-day, 7-day, and 28-day active users (DAU/WAU/MAU) count different things, and GA4 reports rolling versions of each. They overlap rather than add up, and the DAU/MAU ratio is read as a 'stickiness' signal — but all of it inherits the identifier limits of any user count.
- Feature adoption rate
Feature adoption rate is the share of eligible users who used a specific feature in a period — users who used it divided by users who had access to it. It tells a product team whether a capability is reaching its audience. The number hinges on two choices: who counts as eligible (the denominator) and what counts as 'used' (one click, or a meaningful completion), so the same feature can show very different adoption depending on definitions.
- Multi-site analytics
Account-grouped engagement across properties.
Sources and verification notes
- developers.google.com — GA4 active users definitionActive-user basis; account-level grouping is a product convention.
Last reviewed 2026-06-24. Facts are checked against primary/official sources where available; uncertain specifics are marked “Data not yet verified” rather than guessed.