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The Attribution Gap: Why Last-Touch, Multi-Touch, and Marketing Mix Models Never Agree — And What to Do About It

Author(s) Venkata Suneel Dasika
Country United States
Abstract Marketing organizations in the retail sector routinely deploy three distinct measurement frameworks — Last-Touch Attribution (LTA), Multi-Touch Attribution (MTA), and Marketing Mix Modeling (MMM) — to evaluate the effectiveness of their advertising investments. Despite being applied to the same channels, campaigns, and time periods, these three models consistently produce divergent Return on Ad Spend (ROAS) estimates that appear irreconcilable to practitioners. This divergence creates significant organizational friction: budget decisions are made on the wrong model output, cross-model comparisons generate misleading conclusions, and stakeholder confidence in measurement erodes when the same channel appears to perform differently depending on who is looking at it. This paper systematically diagnoses why each model produces a structurally different number — not due to error, but due to fundamental differences in what each model is designed to measure — and proposes a three-tier governance framework that assigns the right measurement model to the right decision context. Using anonymized retail industry case studies, the paper demonstrates that the attribution gap is not a problem to be solved through model reconciliation but rather a feature to be managed through governance clarity. Practitioners are provided with a decision matrix that eliminates cross-model comparison conflicts and improves the quality of marketing investment decisions at both the tactical and strategic level.
Keywords Last-Touch Attribution, Multi-Touch Attribution, Marketing Mix Modeling, iROAS, Attribution Gap, Marketing Measurement Governance, Paid Social, Retail Marketing Analytics, Incrementality, Budget Allocation
Field Engineering
Published In Volume 7, Issue 5, May 2026
Published On 2026-05-11
DOI https://doi.org/10.70528/IJLRP.v7.i5.2267
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