论文信息 - Estimating customer preference through store check-in histories and its use in visitor promotion

Estimating customer preference through store check-in histories and its use in visitor promotion

This paper proposes a method to estimate the preference of customers based on store check-in histories. The proposed method can distinguish the preferences of customers who have no purchase histories. We adopt a machine learning algorithm for model acquisition. The estimation results can improve the efficiency of visitor promotion campaigns and advertising campaigns. An actual visitor promotion trial indicates the effectiveness of the proposed method.

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