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 \(\mathtt {RE\text {-}GrievanceAssist}\) , 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 by 35% since August 2023. (Demo Video is available at https://www.youtube.com/watch?v=PM4Q3dNTrr4 .)