How Tapstream reporting works

An example Tapstream user timeline

Tapstream's attribution and analytics engine processes billions of events per month from Fortune 500 companies, top apps, and thousands of indie developers. It operates on rich, complex timelines that can span websites, ad impressions, clicks, app installs, and downstream events over months and sometimes years.

The Tapstream dashboard represents these complex timelines in a variety of ways: as web sessions, app sessions, attributed installs, attributed events, funnels, cohorts, groupings by custom parameters, and so on.

The complexity of these timelines means that there are different ways to count timeline membership on any given day - by the date that a certain hit or certain event occurred, or the date that the timeline started or finished. This is called "date bucketing", and different Tapstream modules use different date bucketing strategies to respond to the most common analytics questions.

This means that, over a given date range, different Tapstream reports will show different figures. This is to be expected; if the reports do not use the same date bucketing strategy, the rules for node or timeline inclusion will necessarily be different between the two reports.

For monitoring Tapstream's status and accuracy, and to be informed of any known issues, please refer to the Status button inside your dashboard.