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RETRACTED ARTICLE: A study on e-commerce customer segmentation management based on improved K-means algorithm
3 references·3 citing·27 second hop
RETRACTED ARTICLE: A study on e-commerce customer segmentation management based on improved K-means algorithm (2018)RETRACTED ARTICLE: A study on e-commerce …Transit service quality analysis using cluster analysis and decision trees: a step forward to personalized marketing in public transportation (2015)Transit service quality analy…The importance of key celebrity characteristics for customer segmentation by age and gender: Does beauty matter in professional football? (2015)The importance of key celebri…Soft computing applications in customer segmentation: State-of-art review and critique (2013)Soft computing applications i…A comprehensive framework for customer retention in E-commerce using machine learning based on churn prediction, customer segmentation, and recommendation (2024)A comprehensive framework for…Consumer Segmentation Based on Location and Timing Dimensions Using Big Data from Business-to-Customer Retailing Marketplaces (2023)Consumer Segmentation Based o…Algorithm for analyzing the customer base of a trade organization (2022)Algorithm for analyzing the c…Product Differentiation and Market Segmentation as Alternative Marketing Strategies (1956)THE APPLICATION OF CLUSTER ANALYSIS IN STRATEGIC MANAGEMENT RESEARCH: AN ANALYSIS AND CRITIQUE (1996)Market Segmentation: Conceptual and Methodological Foundations (1997)Hybrid soft computing approach based on clustering, rule mining, and decision tree analysis for customer segmentation problem: Real case of customer-centric industries (2018)Market segmentation and travel choice prediction in Spa hotels through TripAdvisor’s online reviews (2019)Marketing strategies evaluation based on big data analysis: a CLUSTERING-MCDM approach (2019)Factor Analysis and AIC (1987)Latent Gold 4.0 User's Guide (2005)Quality attributes of public transport that attract car users: A research review (2012)Measuring the quality of public transportation systems and ranking the bus transit routes using multi-criteria decision making techniques (2018)Importance – Performance Analysis (IPA) of bus service attributes: A case study in a developing country (2020)Interrelationships among service quality factors of Metro Rail Transit System: An integrated Bayesian networks and PLS-SEM approach (2020)An Index of Factorial Simplicity (1974)A Paradigm for Developing Better Measures of Marketing Constructs (1979)Common method biases in behavioral research: A critical review of the literature and recommended remedies. (2003)Customer Segmentation using Machine Learnin (2020)Dynamic managerial capabilities, firm resources, and related business diversification – Evidence from the English Premier League (2020)Wholesale Price Discrimination in Global Sourcing (2020)Identifying fair trade in consumption choice (2006)Customer switching behaviour in the Chinese retail banking industry (2010)Green supply chain collaborative innovation, absorptive capacity and innovation performance: Evidence from China (2019)International tourism and climate change (2012)The Role of Big Data and Predictive Analytics in Retailing (2017)The Impact of Digital Transformation on the Retailing Value Chain (2018)Rediscovering market segmentation. (2006)Building comprehensible customer churn prediction models with advanced rule induction techniques (2010)A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry (2016)
this work references cited by second hop

References

  • 2015Transit service quality analysis using cluster analysis and decision trees: a step forward to personalized marketing in public transportation142 cited
  • 2013Soft computing applications in customer segmentation: State-of-art review and critique86 cited
  • 2015The importance of key celebrity characteristics for customer segmentation by age and gender: Does beauty matter in professional football?39 cited

Cited by

  • 2024A comprehensive framework for customer retention in E-commerce using machine learning based on churn prediction, customer segmentation, and recommendation17 cited
  • 2023Consumer Segmentation Based on Location and Timing Dimensions Using Big Data from Business-to-Customer Retailing Marketplaces14 cited
  • 2022Algorithm for analyzing the customer base of a trade organization12 cited

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