Pre-aggregating is what makes traditional analytics fast and inflexible at the same time. The rollup answers today’s question in milliseconds and next month’s question not at all. Countly keeps raw events so a new breakdown is a query rather than a re-instrumentation project, and aggregates on read instead of on write.
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- Active usersPeople who performed at least one qualifying action in a window. The window and the action are your definition, not an industry constant.
- AI overviewA written summary of what changed in the data and why, generated from live events rather than from a monthly export.
- Anomaly detectionWatching metrics for values outside their normal range and raising them before someone notices in a weekly review.
- Behavioral analyticsAnalysis of what people actually did in the product (events in sequence) rather than of who they are on paper.
- Behavioral cohortA group defined by actions taken, such as everyone who used a feature twice in their first week. Recomputed as the data arrives.
- Bounce rateThe share of sessions that end without a second meaningful interaction.