Less guessing. More knowing why.

Customer analytics is the practice of collecting, measuring, and interpreting behavioral data to understand how users interact with your product what they do, where they drop off, and what drives conversion and retention. It matters because decisions made without behavioral data are guesses. With customer analytics, you can pinpoint the exact step in your funnel where users abandon, which cohort retains best, and which campaigns drive revenue versus just traffic. Intempt's analytics are built into the same platform as your journeys and experiments, so insights connect directly to action without switching tools.

Product analytics focuses on how users engage with product features adoption rates, session depth, feature usage patterns, and activation events. Customer analytics is broader: it includes behavioral data but also ties in campaign performance, revenue attribution, and lifecycle metrics like retention and churn. Intempt covers both. Event tracking captures product interactions, while unified profiles and computed traits connect product behavior to revenue outcomes so you can see which features drive trial-to-paid conversion, not just which ones get clicked.

Cohort retention measures what percentage of users who started in a given time period are still active at Day 7, Day 14, and Day 30. It tells you whether new users are sticking or churning early. Most products have a retention problem long before it shows up in overall active user numbers cohort analysis surfaces it early. Intempt builds retention cohorts from your real event data and connects them to your journey canvas, so when a Day 7 drop appears, you can trigger a re-engagement journey targeting that specific cohort without switching tools.

For most use cases, yes. Intempt handles event tracking, funnel analysis, retention cohorts, path analysis, and KPI dashboards the core capabilities of product analytics tools. The key difference is that Intempt's analytics share the same unified profile as your journeys, experiments, and personalization. When you spot a drop-off, you can build a journey to fix it immediately, using the same audience data. No export, no sync, no separate billing. Teams with advanced data science or custom BI needs may still want a dedicated analytics layer, but for growth and marketing teams, Intempt removes the need to pay for and maintain a separate tool.

Intempt collects events via a JavaScript SDK for web, a mobile SDK for iOS and Android, a server-side API for backend events, and native connectors for third-party tools. Every event is tied to a unified customer profile using identity resolution, so web events, mobile events, and server events all appear on the same timeline for the same user. Custom events can be defined to match how your product works no rigid schema required.

Event data streams into Intempt in real time. Journeys, segments, and computed traits update as events arrive there is no batch delay. This matters for journey triggers: if a user completes an activation event, a journey can fire within seconds. For analytics reports and dashboards, data reflects the current state of your event stream, not a daily snapshot.

Yes. Intempt supports custom funnels for any event sequence, time-series reports with event and attribute breakdowns, retention cohorts with configurable windows, and KPI dashboards that combine reports from journeys, experiments, segments, and raw events. Dashboard annotations let teams add context to any chart. Reports can be filtered by audience segment, channel, time window, or any behavioral attribute.