Budget allocation by clustering users in a learned hidden representation space and optimizing per cluster improves order volume and gross merchandise volume by up to 0.65% relative to individual-level baselines in Meituan A/B tests.
Direct heterogeneous causal learning for resource allocation problems in marketing
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Hidden Representation Clustering with Multi-Task Representation Learning towards Robust Online Budget Allocation
Budget allocation by clustering users in a learned hidden representation space and optimizing per cluster improves order volume and gross merchandise volume by up to 0.65% relative to individual-level baselines in Meituan A/B tests.