XAIによるオンライン購買顧客のリードスコアリングとその解釈

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2023/12/01

タイトル(英語): A Lead Scoring System and it's Interpretation of Online Purchasing Customers by XAI

著者名: 齊藤　史哲（千葉工業大学）

著者名(英語): Fumiaki Saitoh (Chiba institute of Technology)

キーワード: 大規模アンケート，潜在顧客，デジタルマーケティング，SHAP，XGBoost　　large-scale questionnaire，potential customers，digital marketing，shapley additive explanations，XGBoost

要約(英語): In recent years, digital marketing in the retail industry is merging “online”, which is sales through the Internet such as EC sites, and “offline”, which is direct sales through physical stores. On the other hand, the use of e-commerce sites is not yet sufficiently developed in the market of retail stores such as home electronics mass retailers, and there is room for expanding user range. The purpose of this study is to extract potential online customers from customers who have never purchased from an e-commerce site and to implement efficient customer targeting. The paper provides a method for extracting knowledge about offline customers who have similar characteristics to online customers by applying explainable AI (XAI) method for XGBoost trained on customer data. In this study, by applying the proposed method to Oricon customer satisfaction survey data, we detected the difference between potential customers and non-potential customers, and confirmed the effectiveness of the proposed behavior.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.143 No.12 （2023） 特集：電気・電子・情報関係学会東海支部連合大会

本誌掲載ページ: 1203-1210 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/143/12/143_1203/_article/-char/ja/