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Show the journey first, then show the rule that split it.

A multi-touch model distributes one outcome across the touchpoints in a journey. Which touchpoint gets how much is a choice — first touch, last non-direct, linear, position-based, time-decay — and Realvertising makes you select it explicitly rather than inheriting a default. The attribution service recomputes credit under the selected model while leaving the underlying journey untouched. Every figure in the interface carries the model it was calculated under.

Models are switchable, journeys are not

The journey is stored once, as an ordered sequence of observed touchpoints with timestamps. Models apply on top of it at read time, so moving from last-click to position-based re-credits the same history instead of rewriting it. Two models can run against identical data and be compared column by column.

Credit is split, nothing is caused

A model distributes an outcome across touchpoints under your rule. It does not estimate what would have happened had a touchpoint been absent, which is an experiment's job and lives in its own column. Channels are credited with revenue here; revenue is recorded after them, never because of them.

The path, not just the endpoint

Expanding a credited conversion shows the ordered touchpoints, the time between them, and whether each was paid, organic, referral or direct. Assisting paths that never win last-click credit become a visible pattern instead of disappearing into an unattributed bucket. The Growth Brain quotes those paths when it proposes a change.

In this capability

  • First, last, linear, position, decay
  • Model switching on stored journeys
  • Journey path inspection
  • Rule shown with every figure

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