The burgeoning digital economy is characterized by providers offering their products and services to consumers in bundles. Consequently, firms, policy-makers, competition authorities and courts are challenged to consider the actual and possible effects of bundling on profits, consumer and total welfare, sometimes in advance of products being brought to market. Current literature provides some guidance for evaluating possible outcomes (Abdallah 2018; Hennig-Thurau and Houston 2018; Simon and Fassnacht 2018). However, theoretical tractability requires most models to make highly stylized assumptions rarely observed or anticipated in the real-life situations motivating inquiry. Different ways of evaluating these complex cases are required. Howell and Potgieter (2017), Howell and Potgieter (2018b), Howell and Potgieter (2018a), and Howell and Potgieter (2019) propose the use of numerical analysis of the output of discrete simulation models capturing the specific characteristics of real-life cases offers an alternative means of evaluation. They successively develop a competition model in which: * the firms, consumers and differentiated products are finite in number; prices are discrete and not continuous; * consumers may purchase multiple items in a single product category. A particular strength of these models are that they mimic the price-setting strategy adopted by firms facing uncertainty about the distributions of consumer preferences for the items. Variants of the model have been used to provide insights into real-life business situations where firms have limited opportunities to sample information about a market where (for example) firms offer differentiated Internet access (e.g. cable and copper/fiber) and content offers (e.g. Netflix, Spotify, other proprietary video content products, gaming, home security monitoring) both stand-alone and in bundles. In Howell and Potgieter (2019) the authors generated a set of consumer willingness-to-pay values for the two products from random (normal) distributions. In this paper, we explore the expected behavior when the underlying distribution of both products is drawn from an asymmetrical long-tail distribution. By varying the parameters of the distribution from which the products' WTPs are drawn, we can explore how bundle pricing offers might vary in several distinct scenarios.