Measurement of Consumer Preferences for Bucket Pricing Plans with Different Service Attributes

A bucket pricing plan charges a periodic (usually monthly) fixed price that allows consumers to use the service up to a set allowance. The determination of optimal plans requires knowledge about each consumer's simultaneous decision about service subscription, plan choice, and consumption, which are interrelated and difficult to predict. Beside prices, service attributes also influence the three decisions, but how they do depends on the particular service attribute. This article describes a novel method to predict consumers' reactions to bucket pricing plans with varying service attributes and develops an algorithm to optimize bucket pricing plans. Methodologically, we show that the failure to model the influence of service attributes correctly leads to non-optimal prices and profits that differ by up to 22.75% from the optimal solution. Substantially, we show that bucket pricing plans are approximately as profitable as other nonlinear pricing plans if at least three bucket pricing plans serve to segment the market. Bucket pricing plans therefore present an attractive alternative for service providers to differentiate consumers according to their WTP and consumption