Path contribution
Inspect marginal channel contribution across the full conversion journey.
AI ADS ATTRIBUTION
Put channel contribution, revenue attribution, and budget judgment on one evidence chain.
Attribution infrastructure for multi-platform teams, preserving path contribution, model assumptions, and decision confidence.Inspect the attribution mechanismBUILT FORGrowth, marketing, and analytics teams
INGESTATTRIBUTECALIBRATEDECIDE
THE PROBLEM
Last-touch reporting cannot explain real growth, and fragmented reports cannot govern budget.
When channel data, CRM conversions, and revenue signals stay apart, teams debate performance with incompatible definitions.
- 01Early and assisting touchpoints are systematically undervalued
- 02Channel reports and revenue data do not reconcile
- 03Performance changes lack reviewable evidence
- 04Budget discussions depend on local spreadsheets and manual explanation
HOW IT WORKS
Preserve every assumption from signal reconciliation to budget recommendation.
Select a stage to inspect its inputs, processing logic, and auditable output.ATTRIBUTION / MODEL v2.3CALIBRATED
Google Ads
Meta Ads
CRM
Revenue
MODEL OUTPUTReconciling path contribution and reporting latencyConfidence 0.94 · 30-day contribution window · Version logged
CAPABILITIES
Keep enough context for real budget decisions.
Model confidence
Include freshness, delay, overlap, and calibration state in every judgment.
Budget direction
Translate contribution change into governed channel and audience moves.
DELIVERY
Validate the signals before launching the model.
Delivery starts with a signal audit so attribution conclusions never outrun data alignment.- 01Signal audit
- 02Ads and CRM integration
- 03Model calibration
- 04Workspace launch
ENGAGEMENTStarting at US$19,980
Scope depends on data sources, markets, model complexity, and validation period.
AI ADS ATTRIBUTION