Uplift Modelling for Retention Campaigns: Causal Targeting Against Propensity Ranking
DOI:
https://doi.org/10.5281/zenodo.22660483Keywords:
Uplift Modelling for Retention Campaigns; Applied machine learning; Evidence synthesis; Production deployment; MLOpsAbstract
Uplift Modelling for Retention Campaigns is an area of active development in applied machine learning, with evidence that has
accumulated unevenly across its component questions. We review the current evidence base for uplift modelling for retention
campaigns, spanning methodological, implementation, governance, and cost dimensions, focusing on where practice has
converged and where it continues to vary, and set out the practical considerations relevant to a team considering its adoption. We
conclude that selective, context-specific use is best supported by the evidence currently available, rather than uniform adoption or
avoidance.
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