Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.getinteract.com/llms.txt

Use this file to discover all available pages before exploring further.

Multi-touch attribution (MTA) credits conversions to the marketing channels that appeared in the customer journey — not just the last touchpoint. Interact runs Markov chain and Shapley value attribution on your BigQuery customer journey data, and presents the results in a filterable, date-range-based dashboard.

​
How it works

Attribution in Interact processes your customer journey paths table in BigQuery and runs statistical models to determine how much credit each channel deserves. 
BigQuery paths table
(one row per touchpoint)
         ↓
Path pre-processing
(deduplication, junk channel filtering, length limits)
         ↓
Markov chain model    +    Shapley values model
(removal effects)          (coalition values)
         ↓
Attribution credit per channel
(revenue, conversions, credit share)
Results are cached per date window and label combination. Subsequent loads of the same window are instant — no recomputation needed.

​
Attribution models

Markov chain

Uses transition probabilities between channels to calculate each channel’s removal effect — how much conversion rate drops when that channel is removed from all paths. Channels with high removal effects are structurally important to the journey.

Shapley values

A game-theory approach that fairly distributes credit across all possible channel orderings. More computationally intensive, but captures synergies between channels. Enable in settings when deeper analysis is needed.
Last-touch attribution is also always available as a reference baseline.

​
Key concepts

ConceptDescription
Removal effectHow much conversion rate falls when a channel is removed from all journeys. The primary Markov metric.
Credit shareFraction of total conversion credit attributed to a channel (0–1).
Date windowThe time range over which journeys are analysed. Only journeys starting in this window are included.
Label splitsSegment attribution by dimension (e.g. country, brand). Run the model separately per segment.
Junk channelsChannels excluded from path analysis (e.g. “Direct”, “Other”). They are removed from journeys before processing.
CoveragePercentage of journeys where at least one touchpoint matches a known channel. Low coverage suggests a data or channel mapping issue.

​
Pages

Channel Attribution

Main dashboard — removal effects, attributed revenue, and Sankey journey flows across a date window.

Journey Attribution

Per-journey and per-touchpoint credit view, powered by a pre-computed credit table.

Setup

Configure the paths table, column mapping, models, spend data, and scheduling.