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New auto-targeting method optimizes e-commerce marketing campaigns

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a new method called auto-targeting to optimize e-commerce marketing campaigns by jointly selecting users and products. The approach uses constrained spectral biclustering, greedy local search, and a multi-armed bandit framework to create disjoint campaigns with strong user-item affinities. Evaluations on synthetic and real-world datasets indicate that biclustering yields high-quality, fair campaigns, while bandit methods offer scalability for larger datasets. AI

IMPACT Introduces a novel approach to personalize marketing by jointly optimizing user and item selection for better campaign performance.

RANK_REASON The cluster contains an academic paper detailing a new method.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New auto-targeting method optimizes e-commerce marketing campaigns

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The cluster contains an academic paper detailing a new method.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Maja Lindstr\"om, Natalija Glisovic, Jan von Pichowski, Tommy L\"ofstedt, Martin Rosvall ·

    Constrained user-item allocation for e-commerce marketing campaigns

    arXiv:2606.09623v1 Announce Type: new Abstract: When running marketing campaigns, retailers must decide which products to promote and which users to target. These decisions are inherently coupled: effective campaigns match users and items with strong mutual affinity into non-over…

  2. arXiv cs.LG TIER_1 English(EN) · Martin Rosvall ·

    Constrained user-item allocation for e-commerce marketing campaigns

    When running marketing campaigns, retailers must decide which products to promote and which users to target. These decisions are inherently coupled: effective campaigns match users and items with strong mutual affinity into non-overlapping groups of predefined sizes. However, exi…

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