Machine Learning Algorithms and its Impact on Customer Engagement

Customer engagement is undergoing a massive transformation due to the advent of machine learning technologies. Customer engagement applications with Machine Learning capabilities can shift through vast amounts of customer data and extract meaningful insights to help businesses forge deeper engagement with their customers. With the help of machine learning techniques, applications can offer customers personalized recommendations and predictive analytics capabilities, as well as the ability to analyze customers’ sentiments, resulting in business growth. This paper outlines the current state of customer engagement and its channels to further detail machine learning algorithms and how businesses can extend features towards improving customer engagement. And how businesses respond in a much more efficient way. As more businesses leverage ML to drive business strategies, the perspective of these capabilities on customer engagement is becoming essential to maintaining competitive advantage in this hyper digital ecosystem.

Authors

Publication Details

Journal
International Journal of Computer Trends and Technology
Published
2024-11-30
DOI
https://doi.org/10.14445/22312803/ijctt-v72i11p108
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Machine Learning Algorithms and its Impact on Customer Engagement

P. V. Bhaskar Reddy, Murali Krishna Pendyala, Vishnu Varma Lakkamraju, Hareesh Makam
International Journal of Computer Trends and Technology
Organizational and Employee Performance
article

Machine Learning Algorithms and its Impact on Customer Engagement

P. V. Bhaskar Reddy, Murali Krishna Pendyala, Vishnu Varma Lakkamraju, Hareesh Makam
article en

Abstract

Customer engagement is undergoing a massive transformation due to the advent of machine learning technologies. Customer engagement applications with Machine Learning capabilities can shift through vast amounts of customer data and extract meaningful insights to help businesses forge deeper engagement with their customers. With the help of machine learning techniques, applications can offer customers personalized recommendations and predictive analytics capabilities, as well as the ability to analyze customers’ sentiments, resulting in business growth. This paper outlines the current state of customer engagement and its channels to further detail machine learning algorithms and how businesses can extend features towards improving customer engagement. And how businesses respond in a much more efficient way. As more businesses leverage ML to drive business strategies, the perspective of these capabilities on customer engagement is becoming essential to maintaining competitive advantage in this hyper digital ecosystem.

International Journal of Computer Trends and TechnologyVol. 72(11)
Openalex Percentile: Top 76%
Organizational and Employee Performance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.