基于XGBoost模型的O2O优惠券消费预测

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引用次数: 0

摘要

在O2O营销中,优惠券的精准配送是吸引现有客户或新客户进入实体店的重要方式。合适的优惠券发放策略可以显著提升用户体验,促进优惠券的再消费。在本文中,我们设计了一个基于XGBoost的O2O优惠券使用预测模型,并将XGBoost与另一个基于平均AUC值的模型进行性能比较。相比之下,XGBoost的平均AUC值为0.9584,优于其他模型。因此,该模型可以帮助商家准确定位目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecast of O2O Coupon Consumption Based on XGBoost Model
A precise delivery of coupon is an important way to engage existing customers or attract new ones to physical stores in O2O marketing approach. And a suitable strategy of coupon distribution can significantly heighten the user experience and facilitate coupon re-consumption. In this paper, we design a prediction model of O2O coupon usage based on XGBoost and compare the performance of XGBoost with another model based on the average AUC value. By contrast, the XGBoost performs better than the other model with 0.9584 average AUC value. So this model can help merchants to locate the target accurately.
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