  eBay partners with external vendors, which allows customers to freely select
a vendor to complete their eBay experiences. However, vendor outages can hinder
customer experiences. Consequently, eBay can disable a problematic vendor to
prevent customer loss. Disabling the vendor too late risks losing customers
willing to switch to other vendors, while disabling it too early risks losing
those unwilling to switch. In this paper, we propose a data-driven solution to
answer whether eBay should disable a problematic vendor and when to disable it.
Our solution involves forecasting customer behavior. First, we use a
multiplicative seasonality model to represent behavior if all vendors are fully
functioning. Next, we use a Monte Carlo simulation to represent behavior if the
problematic vendor remains enabled. Finally, we use a linear model to represent
behavior if the vendor is disabled. By comparing these forecasts, we determine
the optimal time for eBay to disable the problematic vendor.
