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Who Buys What? Research Finds Clues To Marketing Innovation

Introducing innovative new products and ideas to the marketplace can be a tricky proposition. Sometimes they take off immediately (like the iPod) and sometimes they can take a while to garner consumer confidence (like the Segway). A troubled economy can make it more difficult to convince consumers to take a leap on a new product. But new research from North Carolina State University finds that targeted marketing to opinion leaders makes it more likely that consumers will buy into innovative products and ideas.

“There are lots of reasons why it might be difficult to get buy-in for a new idea or product,” says Dr. Jon Bohlmann, associate professor of marketing in NC State’s College of Management and co-author of a new paper on how acceptance of innovative technology spreads in the marketplace. “There may be a lack of consumer understanding, uncertainty about whether a product is viable, or it may be that tough financial times make people more hesitant to buy something new.” So Bohlmann and his co-authors looked at how consumers are connected to each other, to see what they could learn about how the relationships between consumers affects the “diffusion of innovation.”

For products that were difficult to diffuse, meaning they were not readily accepted by consumers, the researchers found that clustered networks could be a key to getting greater buy-in from consumers. Clustered networks are social networks where a person’s friends are likely to be friends of each other, rather than being connected to random individuals. People are more likely to take a risk on a new product if someone in their close network cluster is trying the product, rather than if they see an advertisement for the product.

In addition, the presence of well-connected opinion leaders can mean the difference between a new idea catching on or not. In some social networks, large numbers of people are connected by links to a relatively small number of people. For example, every person who reads a popular blog is connected to the person who writes that blog, but they are not necessarily connected to each other. The blogger serves as a sort of hub, serving as the primary link for the network and offering a potential kick-start to the innovation.

“How consumers are connected to each other is essential to understanding the spread of new products,” Bohlmann says, “because social communication is the key to diffusing innovation.”

Bohlmann explains that this finding could be important given the economic climate. “People are being more judicious in spending their marketing money, and we found that spending money to reach out to a large audience would be better spent focusing on well-connected, influential members of a social network – such as opinion leaders on blogs, industry leaders, and so on,” Bohlmann says. “Instead of an ad campaign, I’ll seek out the opinion leaders in the network I’m marketing to.

“But,” Bohlmann adds, “we found that it is not only about getting people on board, but getting people on board who are influential in their social network. Not just having a lot of connections, but having strong connections. Depending on the kind of innovation we’re talking about, these influential people could be community leaders, members of trade groups, et cetera.”

For example, Bohlmann says, some nationally influential physicians may prescribe an innovative drug. This might influence some regionally prominent physicians to follow suit. Soon you have a domino effect, with local physicians willing to prescribe the new drug.

The study, “The Effects of Market Network Heterogeneity on Innovation Diffusion: An Agent-Based Modeling Approach,” was co-authored by Bohlmann, Dr. Roger Calantone of Michigan State University and Dr. Meng Zhao of California State University, Dominguez Hills. The paper will be published in the September issue of the Journal of Product Innovation Management.


Note to editors: The study abstract follows.

“The Effects of Market Network Heterogeneity on Innovation Diffusion: An Agent-Based Modeling Approach”

Authors: Jonathan D. Bohlmann, North Carolina State University; Roger J. Calantone, Michigan State University; Meng Zhao, California State University, Dominguez Hills.

Published: September 2010, Journal of Product Innovation Management

Abstract: Innovations usually have an initial impact on very few people. The period of learning or early evaluation precedes the diffusion of the technology into the wider addressed population. More than a transfer, this is best characterized as communication of benefits, costs, and compatibility with earlier technologies and a relative assessment of the new state of the art. Innovation development by an organization or individual creates not just a device, process or tacit knowledge, but concomitantly a capacity on the part of other organizations or persons to use, adopt, replicate, enhance or modify the technology, skills or knowledge for their own purposes. How innovations actually diffuse is to understand the communication of progress, and this framing helps one to design innovations and also design the marketing and testing programs to ready innovations for market and launch them efficiently. Diffusion theory’s main focus is on the flow of information within a social system, such as via mass media and word-of-mouth communications. This theory presents often in the form of mathematical models of innovation and imitation. Distinct from classical diffusion models, however, consumers are not all identical in how they connect to others within a market or how they respond to information. We examine the effects of various network structures and relational heterogeneity on innovation diffusion within market networks. Specifically, network topology (the structure of how individuals in the market are connected) and the strength of communication links between innovator and follower market segments (a form of relational heterogeneity) are studied. Several research questions concerning network heterogeneity are addressed with an agent-based modeling approach. We present our findings based on simulation results that show important effects of network structure on the diffusion process. The ability to speed diffusion varies significantly according to within- and cross-segment communications within a heterogeneous network structure. We discuss the implications of our approach for new product diffusion, and suggest future research directions that may add useful insights into the complex social networks inherent to diffusion. A simple summary is that discovery of significant prime communicator nodes in a network allows innovation development practices to be better calibrated to realistically multiple market segments.