Systematic review: artificial intelligence as a revolutionizer of customer relationship management systems and customer experience
保存先:
| 著者: | |
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| フォーマット: | artículo original |
| 状態: | Versión publicada |
| 出版日付: | 2026 |
| その他の書誌記述: | Electronic Customer Relationship Management (E-CRM) systems are essential tools for businesses to develop positive interactions and experiences with their customers, leading to the achievement of catalyzing results for the business. In this context, Artificial Intelligence (AI) plays a transformative and revolutionary role in driving E-CRM, organizations that use them, and catapulting the digital and brand experiences that companies have with their customers. This study aims to determine how AI is revolutionizing E-CRM systems and contributing to the improvement of customer experience in organizations, addressing practical uses and applications, ethical and social challenges, as well as emerging trends related to the integration of AI with E-CRM. Using a systematic literature review and PRISMA guidelines as a methodological framework, this study has drawn on the Web of Science, Scopus, and Google Scholar databases to collect scientific evidence from 35 articles published in the last 5 years related to the subject of study. The results show the variety of applications and uses of Generative AI in E-CRM that aim to improve customer experience, highlighting aspects such as automation, personalization, and predictive analysis. The study provides valuable information for both theory and business practice regarding the effective use of AI in E-CRM. |
| 国: | Portal de Revistas TEC |
| 機関: | Instituto Tecnológico de Costa Rica |
| Repositorio: | Portal de Revistas TEC |
| 言語: | Español |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/8519 |
| オンライン･アクセス: | https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/8519 |
| キーワード: | Marketing artificial intelligence data analysis innovation digital transformation information systems information technology Mercadotecnia inteligencia artificial análisis de datos innovación transformación digital sistema de información tecnología de la información |