# Efficient Customer Service Combining Human Operators and Virtual Agents

arXiv: https://arxiv.org/abs/2209.05226 · HTML: https://mlsanity.com/paper/2209.05226/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 42 references that are in the map.
- First posted on arXiv 12 Sep 2022.

## Builds on (most cited first, 6 of 6)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Deep Learning Based Text Classification: A Comprehensive Review](https://mlsanity.com/paper/2004.03705/) (2020)
- [Effective Transfer Learning for Identifying Similar Questions: Matching User Questions to COVID-19 FAQs](https://mlsanity.com/paper/2008.13546/) (2020)
- [A Unified Conversational Assistant Framework for Business Process Automation](https://mlsanity.com/paper/2001.03543/) (2020)
- [A practice-oriented overview of call center workforce planning](https://mlsanity.com/paper/2101.10122/) (2021)
- [Advising Agent for Service-Providing Live-Chat Operators](https://mlsanity.com/paper/2105.03986/) (2021)

## Built on by (most cited first, 1 of 1)

- [Cloning a Conversational Voice AI Agent from Call,Recording Datasets for Telesales](https://mlsanity.com/paper/2509.04871/) (2025)

## Abstract (arXiv)

The prospect of combining human operators and virtual agents (bots) into an effective hybrid system that provides proper customer service to clients is promising yet challenging. The hybrid system decreases the customers' frustration when bots are unable to provide appropriate service and increases their satisfaction when they prefer to interact with human operators. Furthermore, we show that it is possible to decrease the cost and efforts of building and maintaining such virtual agents by enabling the virtual agent to incrementally learn from the human operators. We employ queuing theory to identify the key parameters that govern the behavior and efficiency of such hybrid systems and determine the main parameters that should be optimized in order to improve the service. We formally prove, and demonstrate in extensive simulations and in a user study, that with the proper choice of parameters, such hybrid systems are able to increase the number of served clients while simultaneously decreasing their expected waiting time and increasing satisfaction.