A Nonparametric Contextual Bandit with Arm-level Eligibility Control for Customer Service Routing
This addresses routing inefficiencies in large-scale customer service systems like Amazon's, where agent eligibility changes over time, but the approach is incremental as it builds on existing bandit methods with a novel control component.
The paper tackles the problem of routing customer service contacts to eligible human agents by proposing a nonparametric contextual bandit algorithm (K-Boot) with eligibility control (EC), which learns true eligibility status dynamically; simulation results show K-Boot performs comparably to state-of-the-art models, and EC enhances performance when stochastic eligibility signals are present.
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.