The increasing emphasis on understanding the antecedents and consequences of customer-to-customer (C2C) interactions is one of the essential developments of customer management in recent years. This interest is driven much by new online environments that enable customers to be connected in numerous new ways and also supply researchers' access to rich C2C data. These developments present an opportunity and a challenge for firms and researchers who need to identify the aspects of C2C research on which to focus, as well as develop research methods that take advantage of these new data. The aim here is to take a broad view of C2C interactions and their effects and to highlight areas of significant research interest in this domain. The authors look at four main areas: the different dimensions of C2C interactions; social system issues related to individuals and to online communities; C2C context issues including product, channel, relational and market characteristics; and the identification, modeling, and assessment of business outcomes of C2C interactions.

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In word-of-mouth seeding programs, customer word of mouth can generate value through market expansion; in other words, it can gain customers who would not otherwise have bought the product. Alternatively, word of mouth can generate value by accelerating the purchases of customers who would have purchased anyway. This article presents the first investigation exploring how acceleration and expansion combine to generate value in a word-of-mouth seeding program for a new product. The authors define a program's "social value" as the global change, over the entire social system, in customer equity that can be attributed to the word-of-mouth program participants. They compute programs' social value in various scenarios using an agent-based simulation model and empirical connectivity data on 12 social networks in various markets as input to the simulation. The authors show how expansion and acceleration integrate to create programs' social value and illustrate how the role of each is affected by factors such as competition, program targeting, profit decline, and retention. These results have substantial implications for the design and evaluation of word-of-mouth marketing programs and of the profit impact of word of mouth in general.

Using data on a large number of innovative products in the consumer electronics industry, the authors find that between one-third and one-half of the sales cases involved the following pattern: an initial peak, then a trough of sufficient depth and duration to exclude random fluctuations, and eventually sales levels that exceeded the initial peak. This newly identified pattern, which the authors call a “saddle,” is explained by the dual-market phenomenon that differentiates between early market adopters and main market adopters as two separate markets. If these two segments—the early market and the main market—adopt at different rates, and if this difference is pronounced, then the overall sales to the two markets will exhibit a temporary decline at the intermediate stage. The authors employ both empirical analysis and cellular automata, an individual-level, complex system modeling technique for generating and analyzing data, to investigate the conditions under which a saddle occurs. The model highlights the importance of cross-market communication in determining the existence of a saddle. At low levels of this parameter, more than 50% of the cases of new product growth involved a saddle. This percentage gradually decreased as the parameter increased, and at values close to the within-market parameters, the proportion of saddle occurrences dropped below 5%.