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Auditing Marketing Budget Allocation with Hindsight Regret

Nilavra Pathak, Olivier Jeunen, Eric Lambert

arXiv 28 Apr 2026 · Econometrics

arXiv:2604.25977 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Organizations routinely make strategic budget allocations under operational constraints, but often lack a principled way to assess whether realized allocations were close to the best feasible choices in hindsight. We present a retrospective auditing framework based on hindsight regret, defined as the opportunity cost of the realized allocation relative to a constraint-faithful benchmark under the same budget and stability guardrails. The framework estimates regime-specific spend--response functions from historical logs, computes feasible hindsight allocations via constrained optimization, and propagates uncertainty through Monte Carlo evaluation to produce regret distributions, expected lift, and probability-of-improvement summaries. This separates allocation inefficiency from uncertainty in the estimated response surfaces. Experiments on real marketing allocation logs show that the framework yields interpretable post-hoc diagnostics and reveals a practical trade-off between allocation flexibility and detectability: moderate feasible reallocations often capture most measurable gain, while larger shifts move into weak-support regions with higher uncertainty. The result is a practical method for auditing historical budget decisions when online experimentation is costly or infeasible.

Citation extraction

27
references
36
in-text mentions
27
distinct cited
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
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3Bernal, James Lopez and Cummins, Steven and Gasparrini, Antonio (2017) Interrupted time series regression for the evaluation of public health interventions: a tutorial0.64422100%
4Bottou, Léon and Peters, Jonas and Quiñonero-Candela, Joaquin and Ch… (2013) Counterfactual reasoning and learning systems: The example of computational advertising0.64422100%
5Dubé, Arindrajit and Zipperer, Ben (2014) Pooled Synthetic Control Estimates for Continuous Treatments: An Application to Minimum Wage Case Studies0.64422100%
6Eckles, Dean and Karrer, Brian and Ugander, Johan (2017) Design and analysis of experiments in networks: Reducing bias from interference0.64422100%
7Kohavi, Ron and Tang, Diane and Xu, Ya (2020) Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing0.64422100%
8Loomes, Graham and Sugden, Robert (1982) Regret theory: An alternative theory of rational choice under uncertainty0.64422100%
9Savage, Leonard J (1954) The Foundations of Statistics0.64422100%
10Abbasi-Yadkori, Yasin and Szepesvári, Csaba and Bartlett, Peter (2011) Regret Bounds for the Adaptive Control of Linear Quadratic Systems0.40511100%

Showing the top 10 of 27 scored citations.