Consumer Behavior Analysis and Personalized Marketing Strategies for the Internet of Things

• Miao Han ^[1]
  1. [1] Sejong University

     Sejong University

     Corea del Sur

     
• Localización: RISTI: Revista Ibérica de Sistemas e Tecnologias de Informação, ISSN-e 1646-9895, Nº. Extra 63, 2023, págs. 367-376
• Idioma: inglés
• Enlaces
  • Texto completo (pdf)
• Resumen

  • With the rapid development of Internet of Things (IoT) technology, consumer behavior analysis has become an important component of enterprise marketing strategies. IoT devices can collect a large amount of data about consumer behavior, including purchasing habits, browsing habits, search habits, etc. Through big data analysis and artificial intelligence technology, enterprises can deeply analyze consumer behavior patterns and preferences, providing support for personalized marketing. Through IoT technology, enterprises can collect and analyze consumer data on various channels and devices, thereby gaining a deeper understanding of consumer needs and preferences. This article will explore consumer behavior analysis for the Internet of Things and how to develop personalized marketing strategies.

• Referencias bibliográficas
  • Chandra S, Verma S, Lim W M, Kumar S, Donthu N. (2022). Personalization in personalized marketing: Trends and ways forward, Psychology &...
  • Chiu M C, Chuang K H. (2021). Applying transfer learning to achieve precision marketing in an omni-channel system–a case study of a sharing...
  • Darsono J T, Susana E, Prihantono E Y. (2019). Strategic policies for small and medium businesses in marketing through e-commerce. Journal...
  • Kim J, Kim M. (2023). Using personalization for cause-related marketing beyond compassion fade on social media. Journal of Research in Interactive...
  • Kyaw K S, Tepsongkroh P, Thongkamkaew C, Sasha F. (2023). Business intelligent framework using sentiment analysis for smart digital marketing...
  • Li, C. (2020). E-commerce enterprise marketing management: realistic dilemma, main incentives and resolution strategies. Open Journal of Social...
  • Li X, Li K J. (2023). Beating the algorithm: Consumer manipulation, personalized pricing, and big data management. Manufacturing & Service...
  • Martín A, Fernánde, I A, Martín D I, Beltrán M. (2021). A survey for user behavior analysis based on machine learning techniques: current...
  • Sharma S, Dalip R M. (2019). Comparative analysis of various tools to predict consumer behaviour. Journal of Computational and Theoretical...
  • Song Y W G, Lim H S, Oh J. (2021). “We think you may like this”: An investigation of electronic commerce personalization for privacy-conscious...
  • Timokhovich A N, Bulycheva O S. (2021). Technologies for personalization of brand marketing communications using artificial intelligence,...
  • Wawrowski B, Otola I. (2020). Social media marketing in creative industries: how to use social media marketing to promote computer games....
  • Wei C, Fu M, Wang L, Yang H, Tang F, Xiong Y. (2022). The research development of hedonic price model-based real estate appraisal in the era...
  • Wei W, Sivaparthipan C B, Kumar P M. (2022). Online shopping behavior analysis for smart business using big data analytics and blockchain...
  • Zhan M, Gao H, Liu H. (2021). Identifying market structure to monitor product competition using a consumer-behavior-based intelligence model....
  • Zhu C. (2023). Self Control Analysis of Adolescent Prosocial Behavior Based on Optimized Random Forest Algorithm, Revista Ibérica de Sistemas...