build-attribution-trace

Build a multi-touch attribution trace by aggregating CRM data, LinkedIn analytics, and calendar events, then reconstructing weighted deal journeys to map revenue paths with confidence scoring.

Dark-social inference flags content-influenced or temporal proxy signals in attribution models, assigning explicit low confidence scores to touchpoints where direct tracking fails to capture revenue influence.

Calculate unattributed revenue by aggregating period-level channel attribution data and subtracting mapped touchpoint revenue from total closed deals, highlighting gaps with confidence bands in the final report.

You can run attribution modeling for both single-client and agency-wide perspectives, applying monthly per active client or quarterly for pipeline and pulse analysis to generate period-level reports.

Tag first and last touches by assembling chronological touchpoints per closed deal from multi-source signals, scoring confidence for each interaction before applying weighted journey reconstruction.

Attribution reports show low confidence on touchpoints derived from dark-social inference or temporal proxies, explicitly flagging signals where direct tracking cannot verify the revenue influence.