The Idea:Target marketing efforts in networks — online and off — by identifying and predicting how multiple relationships form.
As firms increasingly seek to harness the potential of networks for marketing purposes, marketers strive to understand and predict how users’ interactivity creates relationships in these networks. In offline contexts, leaders seek to make sense of the various relationships in their organizations, with an eye toward increasing productivity and efficiency.
Professors Asim Ansari and Oded Koenigsberg note that multiple, distinct types of relationships often occur among users of the same network, which existing models that explain how relationships form in a network don’t account for. Simply put, when people connect with each other through networks, they connect via multiple relationships. Online, two Facebook users may be “friends” but may not regularly communicate with each other directly; a user commenting on another’s profile or otherwise actively communicating represents a different type of relationship in the network. Offline, multiple relationships also exist, as when employees in different departments in an organization perform different types of work (for instance, marketing and operations) but still interact with each other. The researchers wanted to know whether the formation of one type of relationship in a network could predict connections via other types of relationships. Working with Florian Stahl of the University of Zurich, they developed a new model for analyzing multiple relationships among a set of network users.
Marketing managers, customer relationship managers, operations managers, direct marketers
You can use this research to identify and target influential users in a network, predict network relationships, and improve understanding of the network structure. This can help to better leverage word-of-mouth marketing or the information transfer potential of a particular network.
Researchers focused on a Swiss social networking site for music artists, where three types of relationships were studied: individual friendships between artists; relationships based on communication or the exchange of information, such as direct messages or comments about upcoming concerts; and artists’ downloads of other artists’ music. They found that common factors determined the likelihood that each of these relationships would form, including geographical proximity of users; the online, as opposed to offline, popularity of artists; and whether the users shared an identity as an individual artist or as part of a band. These factors were related with the existence of a relationship and its strength — for instance, the more messages two users sent each other, the stronger the connection between them.
You can use this model to better understand the social and communication structure of your organizational network, which can lead to solutions for increased efficiency and productivity among employees.
The researchers measured the impact of interventions in a network by focusing on an organization’s small network of different groups of managers — such as research and development, marketing, and operations — involved in the development of a new product. These managers were moved into one shared facility, with researchers examining the types and strength of relationships between managers from different departments before and after the intervention. The model accurately predicted which relationships would form based on common characteristics and predicted the effects of intervention on relationships in the network.
Journal of Marketing Research,
Volume: 48 | Issue: 4 | Pages: 713-728
Publication type: Journal article