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Academic Journal of Computing & Information Science, 2023, 6(8); doi: 10.25236/AJCIS.2023.060820.

Forecast of O2O Coupon Consumption Based on XGBoost Model

Author(s)

Weihan Yang, Zijie Zhang, Runze Liu, Jinjiang Liu

Corresponding Author:
Weihan Yang
Affiliation(s)

Beijing 21st Century International School, Beijing, China

Abstract

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.

Keywords

O2O, Coupons, Machine learning, Prediction, XGBoost

Cite This Paper

Weihan Yang, Zijie Zhang, Runze Liu, Jinjiang Liu. Forecast of O2O Coupon Consumption Based on XGBoost Model. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 8: 165-170. https://doi.org/10.25236/AJCIS.2023.060820.

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