A deployment like this targets a meaningful improvement in marketing ROI within the first six months by reallocating budget away from low-influence channels toward proven converters. The working targets we scope during the audit - stated assumptions to validate against your own baseline, not guarantees - are faster deal cycles as sales learns which touchpoints actually warm up a buying committee, lower marketing spend per closed deal as waste gets cut and high-performing sequences get scaled, and marketing ops hours back every week as spreadsheet attribution work disappears - time your team spends running experiments instead of auditing data.
ROI compounds over months two through twelve. As your attribution models accumulate closed deals - 60 or more is the working threshold - predictions get more accurate and budget recommendations more confident. By month nine, you've identified seasonal patterns in buyer behavior, product-line-specific conversion sequences, and which buyer personas convert fastest - intelligence that competitors without attribution visibility simply don't have. By month twelve, your marketing team operates with the same data rigor as your operations team uses for OEE and throughput yield: every dollar is accounted for, every campaign is measured, and every quarter's budget is informed by predictive models, not politics.