RE-GrievanceAssist: Enhancing Customer Experience through ML-Powered Complaint Management
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866917653980905472 |
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| author | C, Venkatesh Oberoi, Harshit Pandey, Anurag Kumar Goyal, Anil Sikka, Nikhil |
| author_facet | C, Venkatesh Oberoi, Harshit Pandey, Anurag Kumar Goyal, Anil Sikka, Nikhil |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_18963 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | RE-GrievanceAssist: Enhancing Customer Experience through ML-Powered Complaint Management C, Venkatesh Oberoi, Harshit Pandey, Anurag Kumar Goyal, Anil Sikka, Nikhil Machine Learning Computation and Language 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. |
| title | RE-GrievanceAssist: Enhancing Customer Experience through ML-Powered Complaint Management |
| topic | Machine Learning Computation and Language |
| url | https://arxiv.org/abs/2404.18963 |