Diffusion models represent one of the key successes in marketing science. We understand a great deal about what influences and shapes within-country diffusion patterns. However, we understand far less about what influences and shapes cross-country (or “inter-country”) diffusion patterns. Clearly, for firms operating in a truly global environment, understanding to what extent prior adoption in one country affects current (and consequently future) adoption in another country can be an important consideration. Further, understanding how the of interaction across countries impacts the diffusion process can have profound implications for product launch strategies for new durable products. In this paper, we address the extent to which prior adoption of a new product in one country affects adoption in other countries. In particular, we investigate the importance of the pattern of interaction (what we call “mixing”) across countries in the context of a new product diffusion model. More specifically, mixing refers to the pattern of communication within and across countries. For example, do Italians communicate only with other Italians or do they influence consumers in other countries? Understanding and empirically estimating how these mixing patterns across countries influence the subsequent diffusion process is the central research objective of this paper. While previous research in marketing addressing cross-country diffusion has assumed very specific forms of cross-country interaction, the present study develops and estimates a flexible form of mixing that allows for the simultaneous estimation of mixing patterns across multiple countries. In particular, we examine the effect of mixing behavior across populations on new product adoption, viewing mixing as occurring across a continuum with segregation (no mixing) at one end and random mixing at the other. Intermediate forms of mixing lie along this continuum and are called Bernoulli mixing. In order to produce generalizable results, we obtained sales data on four product categories in the European community (EC) nations: VCRs from 1977–1990, microwave ovens 1975–1990, compact disc players 1984–1993, and home computers 1981–1991. For each product, data were collected for 10 EC nations: Great Britain, Germany, France, Italy, Spain, Belgium, Denmark, Netherlands, Sweden, and Austria. A diffusion model that incorporates cross-country prior adoption, cross-country mixing patterns, and individual country covariates was estimated simultaneously across the 10 countries for each of the four products. On the basis of the empirical results, we conclude that mixing behavior across segments is an important consideration in new product diffusion. Specifically, the observed pattern of mixing and the strength of cross-segment influences are important considerations in allocating the marketing mix during product introduction stages. The practical implication of mixing behavior is that if one wishes to understand diffusion in Belgium (for example) it is important to not only know the diffusion parameters in Belgium, but also those in other EC nations. Accordingly, these results should be of interest to managers responsible for coordinating new product launches across countries and to researchers interested in investigating cross-country diffusion issues. As an example of the strategic implications of the results, we note that under Bernoulli mixing future country launches will benefit not only from prior adoption in countries with high contact rates, but in particular from countries with high rates of contact with . Although there is some variance across products, in general Germany, France, Italy, and Spain are the most “gregarious,” as measured by the rate of contact. The results suggest that a strategy of first focusing on Germany, France, Italy, and Spain will maximize adoption in subsequent countries. Each of these countries tends to have a higher percentage of its contacts with individuals internal to its borders as well as with other countries. This suggests that these countries would have relatively quick adoption internally, while having a strong influence externally. Further, for countries such as Denmark, Netherlands, Austria, and Sweden, a higher percentage of their contacts are derived from outside their borders. Thus, “seeding” the diffusion process by introducing first in Germany, France, Italy, and Spain would benefit later adoption in countries such as Denmark, Netherlands, Austria, and Sweden. Although the strength of the individual country influence varies from product to product, this result is generally consistent across the four products.