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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (11): 2-9    DOI: 10.11925/infotech.2096-3467.2018.0834
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Predicting Conversion Rate of APP Advertising with Machine Learning
Yang Zhao(),Xini Yuan,Yawen Chen,Liqiang Wu
School of Information Management, Wuhan University, Wuhan 430072, China
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Abstract  

[Objective] This paper tries to predict the conversion rate of APP advertisements with the help of machine learning algorithms, aiming to improve the effectiveness of advertising and marketing activities. [Methods] First, we examined the characteristics of APP advertisements. Then, we applied four machine learning algorithms to predict their conversion rate. The proposed RF+LXFV model was built with Random Forest, Gradient Boosting Decision Tree, Random Forest, LightGBM, XGBoost, Vowpal Wabbit and Field-aware Factorization Machine. Finally, we evaluated the validity and accuracy of the new model with Tencent APP advertising data. [Results] The prediction results of the proposed model achieved higher accuracy than those of the single algorithm. [Limitations] We did not examine the impacts of advertising transformation delay on prediction. [Conclusions] The proposed RF+LXFV model could predict the conversion rate of APP advertising effectively.

Key wordsAPP Advertising      Advertising Conversion Rate Prediction      Machine Learning      RF+LXFV     
Received: 26 July 2018      Published: 11 December 2018

Cite this article:

Yang Zhao,Xini Yuan,Yawen Chen,Liqiang Wu. Predicting Conversion Rate of APP Advertising with Machine Learning. Data Analysis and Knowledge Discovery, 2018, 2(11): 2-9.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.0834     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I11/2

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