Audience Tuning and WOM Research

Ask about word-of-mouth in the context of online versus offline and you are sure to open up a rather robust conversation. Beyond the typical discussion that occurs, the term “harness” will undoubtedly arise. I do not doubt that the firm needs to harness the power of word-of-mouth, but I feel it takes away from what marketers primary focus should be.

Consumers communicate over various channels-that much is known. What is lacking is an understanding of how the channel effects how and what consumers share about products and services. From this perspective, what needs to be harnessed, is an understanding of the flow of WOM across multiple channels. For example, will high-involvement products enjoy more or less WOM on social channels?

Current research provides conflicting views on what shapes consumers’ talk over various channels. For example, one might assume that interesting things become shared more frequently no matter the channel (Hughes, 2005). Berger and Milkman (2012) found that interesting articles are shared more often via Email than non-interesting content. Bakshy, Hofman, Mason and Watts (2011) found that users are more likely to tweet URLs to interesting content than ordinary. However, Berger and Schwartz (2011) found that interesting products do not produce more person-to-person WOM than ordinary products. These findings suggest that research must not rely on data from one medium. Lovett, Peres and Shachar (2011) argue that “instead of a gross division to offline and online, more channels can be explored” (p. 35). In an attempt to understand how communication channels affect WOM, Berger and Iyengar (2012) compared how interesting products and brands are shared online versus offline. They found that online communication led to increased discussions of interesting products and brands. Understanding the dynamics of each channel is important, but understanding the flow of WOM across channels will help to create better marketing strategies for the firm.

Moving Forward

Under this assumption, this offers a new direction for WOM research to explore. If we can understand how the “medium affects the message” then we can better understand how our messaging may be shared among different audiences. I might argue that when an individual is moved by information they find useful, they are more likely to share that information with another carefully selected individual.


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