 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: June 2026
Volume 11 | Issue 6
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 121
Article Submitted : 24719
Article Published : 9358
Total Authors : 24865
Total Reviewer : 861
Total Countries : 169
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | AI-Based E-Grievances and Customer Issues Troubleshooting Management System |
| Authors Name: | Ms.Kuncham Sukanya , Dr VeerabhadraRao , Mr Suribabu Boyidi |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_213115
|
| Published Paper Id: | IJRTI2605198 |
| Published In: | Volume 11 Issue 5, May-2026 |
| DOI: | |
| Abstract: | In the world now a days digital era, each and every organizations to be followed digital operations and service providers receive a large number of customer complaints and grievances through multiple communication channels such as websites, mobile applications, emails, and social media platforms. Managing these grievances efficiently and responding to customers in a timely manner has become a major challenge for organizations. Traditional grievance management systems rely heavily on manual processes, which often lead to delays, misclassification of issues, and poor customer satisfaction. The proposed aims to automate and enhance the grievance handling process using Artificial Intelligence techniques. The system collects customer complaints through an online platform and uses Natural Language Processing (NLP) to analyze and understand the issue described by the user. Based on the content of the complaint, the system automatically categorizes the grievance, prioritizes it according to urgency, and forwards it to the appropriate department for resolution. Additionally, the system integrates machine learning algorithms to provide automated troubleshooting suggestions and frequently used solutions to customers. This helps in resolving common issues instantly without human intervention. The system also maintains a centralized database for tracking complaints, monitoring resolution progress, and generating analytical reports for organizational decision-making. By implementing AI-driven automation, the proposed system significantly reduces response time, improves grievance classification accuracy, enhances customer satisfaction, and supports efficient complaint management. This intelligent platform can be effectively applied in sectors such as government services, banking, telecommunications, e-commerce, and educational institutions to provide transparent, efficient, and user-friendly grievance redressal mechanisms. |
| Keywords: | AI, E-Grievance System, Customer Issue Management, Complaint Management System, Artificial Intelligence, Machine Learning, Natural Language Processing (NLP), Automated Complaint Resolution, Customer Support System, Smart Ticketing System, Predictive Analytics, Sentiment Analysis, Chatbot Integration, Issue Tracking, Customer Relationship Management (CRM), Digital Grievance Redressal, Intelligent Decision Support System, Service Automation, Data Analytics, Cloud-Based Complaint System, User Satisfaction, Workflow Automation, Real-Time Monitoring, Technical Support Management, AI-Driven Troubleshooting |
| Cite Article: | "AI-Based E-Grievances and Customer Issues Troubleshooting Management System ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 5, page no.b815-b824, May-2026, Available :http://www.ijrti.org/papers/IJRTI2605198.pdf |
| Downloads: | 00063 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2605198
Registration ID:213115
Published In: Volume 11 Issue 5, May-2026
DOI (Digital Object Identifier):
Page No: b815-b824 Country: Amalapuram, Andhra Pradesh, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2605198 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2605198 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2026 - All Rights Reserved - IJRTI | |||