Automatic Lead Qualification Based on Opinion Mining in CRM Projects: An Experimental Study Using Social Media

Victor Hugo Ferrari Canêdo Radich, Tania Basso, Regina Moraes

2025

Abstract

Lead qualification is one of the main procedures in Customer Relationship Management (CRM) projects. Its main goal is to identify potential consumers who have the ideal characteristics to establish a profitable and long-term relationship with a certain organization. Social networks can be an important source of data for identifying and qualifying leads, since interest in specific products or services can be identified from the users’ expressed feelings of (dis)satisfaction. In this context, this work proposes the use of machine learning techniques and sentiment analysis as an extra step in the lead qualification process in order to improve it. In addition to machine learning models, sentiment analysis, also called opinion mining, can be used to understand the evaluation that the user makes of a particular service, product, or brand. The results indicated that sentiment analysis derived from social media data can serve as an important calibrator for the lead score, representing a significant competitive advantage for companies. By incorporating consumer sentiment insights, it becomes possible to adjust the Lead Score more accurately, enabling more effective segmentation and more targeted conversion strategies.

Paper Citation

in Harvard Style

Radich V., Basso T. and Moraes R. (2025). Automatic Lead Qualification Based on Opinion Mining in CRM Projects: An Experimental Study Using Social Media. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 456-466. DOI: 10.5220/0013237400003929

in Bibtex Style

@conference{iceis25,
author={Victor Radich and Tania Basso and Regina Moraes},
title={Automatic Lead Qualification Based on Opinion Mining in CRM Projects: An Experimental Study Using Social Media},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2025},
pages={456-466},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013237400003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Automatic Lead Qualification Based on Opinion Mining in CRM Projects: An Experimental Study Using Social Media
SN - 978-989-758-749-8
AU - Radich V.
AU - Basso T.
AU - Moraes R.
PY - 2025
SP - 456
EP - 466
DO - 10.5220/0013237400003929
PB - SciTePress