Guardrailed Uplift Targeting: A Causal Optimization Playbook for Marketing Strategy

• URL: http://arxiv.org/abs/2512.19805v1
• Date: Mon, 22 Dec 2025 19:02:09 GMT
• Title: Guardrailed Uplift Targeting: A Causal Optimization Playbook for Marketing Strategy
• Authors: Deepit Sapru,
• Abstract summary: This paper introduces a marketing decision framework that converts heterogeneous-treatment uplift into constrained targeting strategies.<n>The framework consistently outperforms propensity and static baselines in offline evaluations.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper introduces a marketing decision framework that converts heterogeneous-treatment uplift into constrained targeting strategies to maximize revenue and retention while honoring business guardrails. The approach estimates Conditional Average Treatment Effects (CATE) with uplift learners and then solves a constrained allocation to decide who to target and which offer to deploy under limits such as budget or acceptable sales deterioration. Applied to retention messaging, event rewards, and spend-threshold assignment, the framework consistently outperforms propensity and static baselines in offline evaluations using uplift AUC, Inverse Propensity Scoring (IPS), and Self-Normalized IPS (SNIPS). A production-scale online A/B test further validates strategic lift on revenue and completion while preserving customer-experience constraints. The result is a reusable playbook for marketers to operationalize causal targeting at scale, set guardrails, and align campaigns with strategic KPIs.

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