A Nonparametric Contextual Bandit with Arm-level Eligibility Control for Customer Service Routing

TL;DR

This paper introduces a nonparametric contextual bandit algorithm with eligibility control for customer service routing, improving SME assignment by learning true eligibility and optimizing contact handling.

Contribution

It proposes K-Boot, a kernel-based bandit algorithm, combined with EC for dynamic eligibility validation, addressing SME routing with changing domain eligibility.

Findings

K-Boot performs comparably to state-of-the-art bandit algorithms.

EC enhances K-Boot performance when eligibility signals are stochastic.

Simulation results validate the effectiveness of the combined approach.

Abstract

Amazon Customer Service provides real-time support for millions of customer contacts every year. While bot-resolver helps automate some traffic, we still see high demand for human agents, also called subject matter experts (SMEs). Customers outreach with questions in different domains (return policy, device troubleshooting, etc.). Depending on their training, not all SMEs are eligible to handle all contacts. Routing contacts to eligible SMEs turns out to be a non-trivial problem because SMEs' domain eligibility is subject to training quality and can change over time. To optimally recommend SMEs while simultaneously learning the true eligibility status, we propose to formulate the routing problem with a nonparametric contextual bandit algorithm (K-Boot) plus an eligibility control (EC) algorithm. K-Boot models reward with a kernel smoother on similar past samples selected by $k$-NN, and Bootstrap Thompson Sampling for exploration. EC filters arms (SMEs) by the initially system-claimed eligibility and dynamically validates the reliability of this information. The proposed K-Boot is a general bandit algorithm, and EC is applicable to other bandits. Our simulation studies show that K-Boot performs on par with state-of-the-art Bandit models, and EC boosts K-Boot performance when stochastic eligibility signal exists.