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Applies to: ✅ Azure Data Explorer
This section describes Kusto extensions (plugins) for user analytics scenarios.
| Scenario | Plugin | Details | User Experience |
|---|---|---|---|
| Counting new users over time | activity_counts_metrics | Returns counts/dcounts/new counts for each time window. Each time window is compared to all previous time windows | Kusto.Explorer: Report Gallery |
| Period-over-period: retention/churn rate and new users | activity_metrics | Returns dcount, retention/churn rate for each time window. Each time window is compared to previous time window |
Kusto.Explorer: Report Gallery |
Users count and dcount over sliding window |
sliding_window_counts | For each time window, returns count and dcount over a lookback period, in a sliding window manner |
|
| New-users cohort: retention/churn rate and new users | new_activity_metrics | Compares between cohorts of new users (all users that were first seen in time window). Each cohort is compared to all prior cohorts. Comparison takes into account all previous time windows | Kusto.Explorer: Report Gallery |
| Active Users: distinct counts | active_users_count | Returns distinct users for each time window. A user is only considered if it appears in at least X distinct periods in a specified lookback period. | |
| User Engagement: DAU/WAU/MAU | activity_engagement | Compares between an inner time window (for example, daily) and an outer (for example, weekly) for computing engagement (for example, DAU/WAU) | Kusto.Explorer: Report Gallery |
| Sessions: count active sessions | session_count | Counts sessions, where a session is defined by a time period - a user record is considered a new session, if it hasn't been seen in the lookback period from current record | |
| Funnels: previous and next state sequence analysis | funnel_sequence | Counts distinct users who have taken a sequence of events, and the previous or next events that led or were followed by the sequence. Useful for constructing sankey diagrams | |
| Funnels: sequence completion analysis | funnel_sequence_completion | Computes the distinct count of users that have completed a specified sequence in each time window | |