Journey Attribution

The Journey Attribution page shows attribution credit at the individual touchpoint level — every step in every customer journey, with Markov and Shapley credit share assigned per touch. Open it from Insights → Attribution → Journeys.

This page requires a credit table to be configured in Insights → Settings → Attribution → Optional Tables. The credit table is written by a separate pipeline process and contains pre-computed attribution weights per touchpoint. Without it, this page is unavailable.

What it shows

The journey attribution view is a paginated table of touchpoints enriched with attribution credit:

Column	Description
Journey ID	Unique identifier for the customer journey
User ID	User or customer identifier (if available)
Label	Segment label when label splits are configured
Journey dates	Start and end date of the full journey
Converted	Whether the journey resulted in a conversion
Journey revenue	Total revenue value for this journey
Position	Touchpoint position within the journey (1 = first)
First / Last touch	Whether this touchpoint is the first or last in the journey
Channel	Channel identifier for this touchpoint
Channel group	Higher-level grouping of the channel
Source group	Source-level grouping
Campaign	Campaign name (if available)
Device	Device category (if available)
Session date	Date of this specific session/touchpoint
Markov credit share	Fraction of conversion credit attributed to this touch (Markov model)
Shapley credit share	Fraction of conversion credit (Shapley model, if enabled)
Attributed revenue	Revenue attributed to this touchpoint (credit share × journey revenue)
Attributed conversions	Conversion credit for this touchpoint (fractional)

Filtering

Use the date range picker at the top of the page to filter journeys by start date. The label filter (if label splits are configured) lets you scope results to a specific segment.

Difference from the Channel Attribution dashboard

	Channel Attribution	Journey Attribution
Granularity	Aggregated per channel across all journeys	Per-touchpoint, individual journey level
Data source	Computed live from paths table	Pre-computed credit table in BigQuery
Use case	Strategic channel decisions	Debugging, auditing, per-user analysis
Requires credit table	No	Yes

Setting up the credit table

The credit table is typically produced by your data pipeline alongside the Markov/Shapley weight computation. Interact reads from it but does not write it. Configure the table in Insights → Settings → Attribution → Optional Tables:

Dataset — BigQuery dataset (default: src_attribution_models)
Table — Table name (default: fact_attribution_credit__user_id)
Channel column — Which column to use as the channel identifier (e.g. channel, source_group, channel_group)

The credit table should have at minimum:

Column	Type	Description
`journey_id`	STRING	Matches the journey ID in the paths table
`user_id`	STRING	(Optional) User identifier
`touchpoint_position`	INTEGER	Position of the touch in the journey
`channel`	STRING	Channel identifier
`markov_credit_share`	FLOAT	Markov credit share (0–1)
`shapley_credit_share`	FLOAT	(Optional) Shapley credit share
`journey_revenue`	FLOAT	Revenue for the full journey
`journey_start_date`	DATE	Start date of the journey

Optional tables setup

Configure the credit table location and column mapping.

​What it shows

​Filtering

​Difference from the Channel Attribution dashboard

​Setting up the credit table

Optional tables setup

What it shows

Filtering

Difference from the Channel Attribution dashboard

Setting up the credit table