RE-GrievanceAssist: Enhancing Customer Experience through ML-Powered Complaint Management

RE-GrievanceAssist: Enhancing Customer Experience through ML-Powered Complaint Management

In recent years, digital platform companies have faced increasing challenges in managing customer complaints, driven by widespread consumer adoption. This paper introduces an end-to-end pipeline, named RE-GrievanceAssist, designed specifically for real estate customer complaint management. The pipel...

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Veröffentlicht in:arXiv.org 2024-04
Hauptverfasser: Venkatesh, C, Oberoi, Harshit, Pandey, Anurag Kumar, Goyal, Anil, Sikka, Nikhil
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Classifiers
Customer satisfaction
Pipeline design
Real estate
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creator Venkatesh, C
Oberoi, Harshit
Pandey, Anurag Kumar
Goyal, Anil
Sikka, Nikhil
description In recent years, digital platform companies have faced increasing challenges in managing customer complaints, driven by widespread consumer adoption. This paper introduces an end-to-end pipeline, named RE-GrievanceAssist, designed specifically for real estate customer complaint management. The pipeline consists of three key components: i) response/no-response ML model using TF-IDF vectorization and XGBoost classifier ; ii) user type classifier using fasttext classifier; iii) issue/sub-issue classifier using TF-IDF vectorization and XGBoost classifier. Finally, it has been deployed as a batch job in Databricks, resulting in a remarkable 40% reduction in overall manual effort with monthly cost reduction of Rs 1,50,000 since August 2023.
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subjects Classifiers
Customer satisfaction
Pipeline design
Real estate
title RE-GrievanceAssist: Enhancing Customer Experience through ML-Powered Complaint Management
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