Articlegold2025

Blockchain-enabled KYC integration for CLV optimization with robust M-Estimation and IRLS method

Marischa Elveny · Mahyuddin K. M. Nasution · Fanindia Purnamasari · Tengku Siti Meriam Tengku Wook

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Customer churn and segmentation Blockchain Technology Applications and Security Data Mining and Machine Learning Applications

Abstract

This research introduces an innovative approach in implementing Know Your Customer (KYC) on blockchain technology as a means of using data, hybrid robust m-estimation, and the iteratively reweighted less squares (IRLS) method to optimize CLV data. This approach aims to improve the accuracy and reliability of CLV predictions by ensuring the security and reliability of customer data. This tool can help companies manage and increase CLV more effectively, meeting data security and compliance standards. The R-squared validation test results are close to 1, so the model can explain data variations well. RMSE and MSE have small values, so the model has good performance in predicting the target value. With these achievements, this approach contributes to the development of better marketing strategies and business decisions in an increasingly complex and rapidly changing digital environment.

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2021Root mean square error or mean absolute error? Use their ratio as well 2021Handbook of Market Research 2022Application of digital technologies for sustainable product management in a circular economy: A review 2022Optimizing the Financial Performance of SMEs Based on Sharia Economy: Perspective of Economic Business Sustainability and Open Innovation 2019Predicting customer value per product: From RFM to RFM/P 2023Research on customer lifetime value based on machine learning algorithms and customer relationship management analysis model 2021Customer lifetime value: investigating the factors affecting attitudinal and behavioural brand loyalty 2021An empirical investigation of the factors affecting customer lifetime value

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