Improving Customer Value Index and Consumption Forecasts Using a Weighted RFM Model and Machine Learning Algorithms

Wu, Zongxiao; Zang, Cong; Wu, Chia‐Huei; Deng, Zhiyang; Shao, Xuefeng; Liu, Wei

doi:10.4018/jgim.20220701.oa1

Cited by 15 publications

(14 citation statements)

References 27 publications

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“…This process is for information encryption, ensuring data security in transmission, and preventing internal eavesdropping. It can be carried out by audit equipment for completing the audit of Structured Query Language (SQL) statements without decryption (Wu et al, 2022). The server's main function is to provide users with data storage and to encrypt or decrypt the data.…”

Section: Data Audit Modelmentioning

confidence: 99%

Ciphertext Database Audit Technology Under Searchable Encryption Algorithm and Blockchain Technology

Jin¹

2022

Journal of Global Information Management

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The study aims to solve the problems in auditing ciphertext data, improve audit efficiency, and increase the security of audit data in the audit server. First, the existing encryption algorithms are analyzed. Second, the searchable encryption algorithm is proposed to audit the ciphertext data, and an audit server scheme is made based on blockchain technology (BT). Finally, the two schemes are compared with the traditional audit technology. The results show that the server's inspection efficiency of the searchable encryption algorithm is higher.

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Section: Data Audit Modelmentioning

confidence: 99%

Ciphertext Database Audit Technology Under Searchable Encryption Algorithm and Blockchain Technology

Jin¹

2022

Journal of Global Information Management

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“… Li et al (2021) proposed a comprehensive customer value model with three dimensions of purchase value, interaction value and marketing diffusion value based on the RFM model. Wu C. H. et al (2021) introduced S in the RFM model, that is, the standard deviation of the customer’s stored value in the recent period. The larger the value, the more impulsive the customer spends.…”

Section: Introductionmentioning

confidence: 99%

Research on commodity business value and customer value of e-commerce platforms: Based on consumer psychology and cognition

Zheng

Wen

et al. 2022

Front. Psychol.

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Under the background of economic globalization and COVID-19, online shopping has gradually replaced offline shopping as the main shopping mode. In this paper, consumers’ perceptions are introduced into the traditional BCG matrix to form a new BCG matrix, and according to it, the small gifts of a gift e-commerce platform are classified. We then performed a robustness test comparing the BCG matrix with K-means clustering. We found that new BCG matrix can objectively reflect the value of small gifts and provide suggestions for the e-commerce platform to make subsequent product decisions. Then we judge the customer value of the platform based on the improved RFM model and K-means++ clustering, and provide a reasonable customer value classification method for the e-commerce platform. Finally, we comprehensively consider the relationship between the commodity value and customer value, and analyze the preferences of different types of customer groups for different types of small gifts. Our research result shows that small gifts can be divided into 4 categories according to commodity value, namely “stars,” “cash cows,” “questions marks,” and “dogs.” These four categories of small gifts can be converted into each other through marketing ploys. Customers can be divided into important retention customers, key loyal customers and general development customers according to their values. Faced with different types of customers, managers can adopt different strategies to extract customer value. However, consumer psychology will affect consumer cognition, and different types of consumers prefer different types of small gifts, so the precise implementation of marketing strategies will effectively improve the profitability of the gift e-commerce platform. Compared with the traditional classification method, the commodity business value classification method proposed in this paper uses management analysis and planning methods, and introduces consumer psychological factors into the commodity and customer classification, so that the classification results are more credible. In addition, we jointly analyze the results of commodity value classification and customer value classification, and analyze in detail the preferences of different valued customer groups for different types of commodities, so as to provide directions for subsequent research on customer preference.

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“…The group has thus started the road to financial intelligence (Han, 2021;Wu, 2021;Gang, 2021;Lu, 2021;Chang, 2019).…”

Section: Introductionmentioning

confidence: 99%

Advanced Artificial Intelligence Model for Financial Accounting Transformation Based on Enterprise Unstructured Text Data

Wei

2022

Journal of Organizational and End User Computing

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As an essential communication medium, the internet brings the freedom and convenience of publishing, transmitting, and acquiring information. At the same time, the problems caused by various kinds of information that endanger social stability and involve the vital interests of the country are also increasingly emerging. The traditional network supervision method can no longer adapt to the continuous development of content security needs. Internet regulators, in the analysis of network data and the retrieval process, mainly focus on structured text data.

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Improving Customer Value Index and Consumption Forecasts Using a Weighted RFM Model and Machine Learning Algorithms

Cited by 15 publications

References 27 publications

Ciphertext Database Audit Technology Under Searchable Encryption Algorithm and Blockchain Technology

Ciphertext Database Audit Technology Under Searchable Encryption Algorithm and Blockchain Technology

Research on commodity business value and customer value of e-commerce platforms: Based on consumer psychology and cognition

Advanced Artificial Intelligence Model for Financial Accounting Transformation Based on Enterprise Unstructured Text Data

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