Emotionally Intelligent AI Powered Customer Experience Optimization with Deep Learning Based Sentiment Analysis and Engagement Metrics

DOI

10.2991/978-94-6463-718-2_49How to use a DOI?

Keywords

Emotionally Intelligent AI; Customer Experience Optimization; Deep Learning-Based Sentiment Analysis

Abstract

Customer experience optimization is a new business need area that keeps resurfacing, and emotionally intelligent AI-based products aid in designing your customer’s overall journey making them better. Hence, this research presents AI-driven customer experience enhancement framework that blends deep learning-based sentiment analysis and engagement perspectives to refine customer interactions in real-time. While most existing studies on sentiment analysis model rely only on textual information, this study leverages multimodal analysis of text, speech patterns, and facial expression of customers to provide a holistic understanding of customers’ feelings. The proposed model utilizes transformer-based NLP models (e.g., BERT, GPT), reinforcement learning and affective computing to dynamically adapt engagement strategies based on customers’ sentiment. Moreover, explainability, fairness, and adaptability are guaranteed through the incorporation of XAI techniques and transfer learning techniques suitable for inter-industrial applications. The work also deals with real-time sentiment tracking, noise-robust speech recognition, multilingual customer interactions, and low-resource AI deployment, making it equally applicable to both large enterprises and small businesses. It is also integrated with CRM models to help devise a customised approach for customer engagement to enhance customer satisfaction and achieving business efficiency. The study overcomes various challenges now limiting conventional sentiment analysis solutions and thereby paves the way to next-generation emotionally intelligent AI systems, where adaptive, human-like AI-driven interactions are aimed to deliver an enhanced customer experience.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Purushotham Endla
AU  - K. Suresh
AU  - P. Praba Devi
AU  - J. Raji Chellam
AU  - Naresh Vurukonda
AU  - K. Kumararaja
PY  - 2025
DA  - 2025/05/23
TI  - Emotionally Intelligent AI Powered Customer Experience Optimization with Deep Learning Based Sentiment Analysis and Engagement Metrics
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 565
EP  - 575
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_49
DO  - 10.2991/978-94-6463-718-2_49
ID  - Endla2025
ER  -