Customer Service Operations: A Gatekeeper Framework

TL;DR

This paper models customer service channels as gatekeeper systems to optimize request resolution, providing strategic, tactical, and operational insights that enhance service quality through chatbot integration.

Contribution

It introduces a novel gatekeeper framework for managing multi-channel customer service, integrating strategic, tactical, and operational decision-making processes.

Findings

Chatbot implementation can improve service quality.

Optimal request resolution policies depend on channel structure.

Strategic deployment of channels enhances overall customer service.

Abstract

Customer service has evolved beyond in-person visits and phone calls to include live chat, AI chatbots and social media, among other contact options. Service providers typically refer to these contact modalities as "channels". Within each channel, customer service agents are tasked with managing and resolving a stream of inbound service requests. Each request involves milestones where the agent must decide whether to keep assisting the customer or to transfer them to a more skilled -- and often costlier -- provider. To understand how this request resolution process should be managed, we develop a model in which each channel is represented as a gatekeeper system and characterize the structure of the optimal request resolution policy. We then turn to the broader question of the firm's customer service design, which includes the strategic problem of which channels to deploy, the tactical questions of at what level to staff the live-agent channel and to what extent to train an AI chatbot, and the operational question of how to control the live-agent channel. Examining the interplay between strategic, tactical, and operational decisions through numerical methods, we show, among other insights, that service quality can be improved, rather than diminished, by chatbot implementation.