RE-GrievanceAssist: Enhancing Customer Experience through ML-Powered Complaint Management
This is an incremental improvement for real estate companies to enhance customer experience through automated complaint management.
The paper tackled the problem of managing customer complaints in real estate by introducing an end-to-end ML pipeline, resulting in a 40% reduction in manual effort and monthly cost savings of Rs 1,50,000.
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.