Bibliographic Analysis: Ai-Powered Consumer Behaviour And Consumer Retention

Abstract

Introduction- Artificial intelligence is now assisting companies in understanding and keeping customers better in marketing and CRM. Through the integration of multidisciplinary literature from the fields of marketing, data science, and cognitive psychology, researchers are able to determine how artificial intelligence facilitates behavioural nudges, predictive analytics, and hyper-personalization in order to impact and maintain customer engagement. Personalised customer experiences, sentiment analysis powered by AI, consumer churn prediction modelling, and the usage of chatbots to improve customer engagement are some of the major subjects examined in the study.

 Objectives-The paper aims to determine how artificial intelligence facilitates behavioural nudges, predictive analytics, and hyper-personalization in order to impact and maintain customer engagement.

Method-It highlights well-known writers, prestigious publications, and widely used approaches including text mining, machine learning, and quantitative surveys. The review reveals a notable increase in publications after 2018, highlighting the growing interest in the topic among academics and practitioners with the help of bibliographic analysis.

Results- Personalised customer experiences, sentiment analysis powered by AI, consumer churn prediction modelling, and the usage of chatbots to improve customer engagement are some of the major subjects examined in the study.

 Conclusion- The conceptual framework presented in the study connects AI capabilities with insights into customer behaviour and retention tactics. New fields like data privacy, emotional AI, and ethical AI are acknowledged as crucial avenues for the future. In addition to offering insights into possible gaps and opportunities for additional research in AI-driven consumer behaviour and retention methods, the paper presents a systematic assessment of current research trends.