What are the 5 drivers of social media engagement?

This article has focused on five drivers of social media engagement: connected effect, network effect, information effect, dynamic effect, and timeliness effect.

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Editorial

Article Type: Editorial From: Journal of Consumer Marketing, Volume 33, Issue 2

Engaging customers: the wheel of social media engagement

The top priority of every firm is, or should be, to use the power of social media to engage customers. The abilities that social media provide firms, to target and participate in dynamic conversations with individual customers, means that the return on investments in social media efforts can be significantly greater than those earned from traditional media efforts. Firms recognize that posting information that customers relate to, or find engaging, means that customers will keep coming back, liking or commenting on the posts and sharing them with friends. Not only do these activities help keep the brand top-of-mind and enhance purchase intentions, but they also can turn consumers into active advocates. The growth in social media in turn has been driven by several related factors. One such driver is the innate need that people have to connect with other people. This connection is bidirectional; people learn what their friends are interested in, but they also broadcast their own interests and opinions to those friends. Humans always need to be connected to other people, and social media provide them with a new, easy and engaging way to do so. In particular, people can connect by sharing different types of information, whether their location, the food they have consumed, exercises they have completed or a news item that they find interesting. The revolutionary changes in how consumers interact with one another, as well as with firms and brands, provide enormous opportunities for marketers. Accordingly, these changes promise rich opportunities for researchers to derive and provide guidance to firms about how best to engage with consumers. Part of the process of understanding what factors effectively drive engagement with customers involves investigating the fundamental sociological and psychological shifts in behaviors that have resulted from the growth of social media. Another driver of social media is convenience or timeliness, as made possible by smartphones and tablets. The mobility of these devices provides constant access for consumers, fuelling a tremendous avalanche of applications, either for entertainment or for productivity. In the modern age of apps, there is an app for virtually every function or customer need, and many apps even prompt new business models. For example, Uber has upended the taxi industry, and Netflix is changing the cable television market. Facebook, LinkedIn, Twitter, YouTube, Instagram, Snapchat and Vine are just a few of the myriad of apps available to help people make expanded social connections. Beyond social network platforms, apps also make it easier for customers to connect with and conduct business; Bank of America enables account holders to do all their online banking with its app, and JetBlue’s app makes it easy for travelers to manage their flights. The list of apps and what they can do is virtually endless. Fitness apps can record steps taken, calories consumed, heart rate or measurement of pulse. Apps allow people to store a library of books read, a list of travel destinations or a summary of wines purchased. Each app then opens the door for a company to engage with customers in a different, specific manner. These apps, thus, produce another driver of social media engagement, namely, the ability to provide relevant information to and participate in dynamic conversations with customers. These factors also enhance consumers’ desire to engage with the network. Apps can help make engagement more focused by providing the desired information in a readily accessible portal. With this special issue, we seek to shed light on five key drivers of the growing panorama of social media. Despite some early investigations into social media (see review by Grewal et al., 2016), the field remains in its infancy. This special issue aims to highlight some important drivers of social media engagement. In this introduction, we propose a unifying framework, the “Wheel of Social Media Engagement”, that highlights the fundamental drivers of social media engagement as five related effects: connected, network, information, dynamic and timeliness. In discussing the five spokes of this Wheel of Social Media Engagement, we specify how the insights from the five papers included in this special issue resonate with this proposed model.

The wheel of social media engagement

Researchers and marketers highlight the importance of engaging customers, and specifically cite social media engagement as a profitable way to engage customers by taking their current behavior into account while also setting the stage for future behavior. This form of engagement acknowledges both consumers’ own behavior and the influence of the overall network that surrounds them. In the Wheel of Social Media Engagement, we propose that the hub is a repository of past and current social media engagements, analogous to a comprehensive customer relationship management (CRM) data warehouse but unique to social media. The other five components, or the spokes of the wheel, are the five effects that drive usage of social media. We discuss each effect in detail, and illustrate them in Figure 1. For ease of exposition, we start with these five spokes, before bringing them together in a discussion of the hub of engagement.

The wheel of social media engagement

Opens in a new window.

The connected effect

A powerful evolutionary force throughout human history has been the need to connect with others. The connected effect is the ability of consumers to connect with and receive information from others. This force drives communities and civilizations. In the twenty-first century, with the age of technology, humans have become steadily less physically connected; instead of shopping at the local market, for example, consumers have moved to online shopping and home delivery. Instead of working in an office, employees increasingly telecommute. As a backdrop of these changes, social media has empowered humans to connect in novel ways. Some connections may involve existing friends and colleagues, but they also occur with acquaintances who might not have connected in an offline world as easily as they do online. Similarly, consumers may connect more easily with firms, brands or news outlets that they would not have been aware of outside of the world of social media. Social media has allowed users to both join and form vast numbers of such networks. Each different social network just keeps growing, often without actively seeking others. More people continue to seek to opt in, as is evident by the many Facebook or LinkedIn requests sent. Hamilton et al. (2016) highlight consumers’ various motives for connecting with their networks using social media. These motivations might include promotions and incentives, timely information and product information. The connection allows the consumers to receive and express social approval of what others have posted. For example, consumers readily click to express their liking of various posts ranging from descriptions of events important in their lives, to jokes, to pictures. This increased connection holds the risk of becoming a bane for consumers, many of whom are habituated to looking at their smartphones as soon they ding, causing them to lose focus on activities in the physical world.

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We can envision filters being available to be applied to social network posts to categorize their types (e.g. informational, health, entertainment) for different target groups (e.g. close friends, as is done on Facebook). Currently, multiple platforms (e.g. Facebook, LinkedIn) provide distinct services for different purposes. As these networks expand and grow, their goal will be to encourage users to visit their platform exclusively. One way this may be done is by creating appropriate sorting of purposes for viewing posts.

The network effect

The connected effect refers to information received from others; on the flip side, every time a consumer posts information, it is conveyed to his or her vast connections across social media. This is the network effect. Consumers post to provide information or opinions that they want others to be aware of. Network research identifies the exponential influence of social networks. The network effect, thus, serves as an important source of information but also as a multiplier of influence, depending on what the person shares. Through the network effect, people can widen their sphere of influence, though usually in a relatively less conspicuous manner. Because it is less obtrusive but still directed to the connected network, this magnified influence can be more persuasive for getting other members of the network to consider the expressed opinion or idea. In this setting, we note the need for research that explores the joint effects of the multiple networks that people join (e.g. Facebook, LinkedIn, Twitter). How do consumers post about brands, brand consumption by others in their expanded network, or their own consumption? A basic expectation is that people who discuss a product are more likely to buy it. Yuksel et al. (2016) also suggest that the influence of being part of a social network increases when the user connects using a smartphone. In a scenario-based experiment with a fantasy football network, they investigate the joint effects of whether consumers are part of the network and whether they use a smartphone to access that network.

The information effect

Social connections are driven by the information being shared. Relevant information thus is the key to turning the wheel, but relevance is highly context dependent. Drivers of relevance might include humor, cuteness, monetary savings, interesting offers, information about places to travel, news items, gossip about family and friends or brand communications. As in the saying that “beauty is in the eye of the beholder”, relevance is determined solely by the consumer, in the context in which it is considered. Marketers thus work hard to provide information that is contextually relevant in some way. A humorous advertisement generally is more effective when interjected into posts by a group of friends who like to joke around together or share funny pictures or videos. This information effect highlights the need for marketers to participate actively in conversations, as opposed to intruding on them. Marketers need to learn the art of subtly joining an interaction. As we think further about the information effect and the incredible magnitude of information being conveyed through reviews, Facebook posts, tweets and so on, it begs the question: what can we do with all of it? Ludwig and de Ruyter (2016) use speech act theory to propose that the linguistic elements of the information being conveyed provide important insights, because they highlight the strength and conviction, quality and credibility of a message. All of these linguistic elements help inform readers about the overall message and thus are likely to drive the message’s impact.

The dynamic effect

Building on the prior discussion, a marketer actively participating in the conversation through social media, such as Twitter, is engaging in a dynamic communication with back-and-forth interactions. Traditional retailing research that demonstrates that when shoppers spend more time in a store, they buy more, we posit that when consumers interact more in a social media space with a brand, they buy it more. But too many brands and firms still limit themselves to a one-way communication style, akin to viewing an advertisement without a compelling call to action. Dynamic communication also brings the question of the appropriate volume of communication to the fore. How much is information overload? Are the effects nonlinear? A possible means to offset the potential for negative consequences would be to change the topic, tone and tenor of the communication. Aguirre et al. (2016) showcase that dynamic communications allow marketers to interject highly personalized promotions that provide relevant information. However, overly personalized offers can also be perceived as an invasion of privacy, such that marketers must find ways to address this privacy personalization paradox (Aguirre et al., 2015).

The timeliness effect

As discussed in the introduction, the convenience provided by smartphones and tablets makes it possible for consumers to access their social networks. Posts can be read at any time, ensuring that the connection can occur when it is convenient for the consumer. Smartphones and tablets have also spurred the development of apps which make it very easy to access the specific information contained in the social network in an easy to access and timely manner. Beyond this, however, the timing of when information is presented in the network can impact how the information is received. Research in the domain of primacy and recency highlights the importance of both initial information and the last piece of information received (Biswas et al., 2010). In support of recency effects, people exhibit greater recall for recent information as opposed to initial information (Howard and Kahana, 1999; Neath, 1993). Such findings are in line with information integration theory and various forms of averaging models (Anderson, 1971; Slovic and Lichtenstein, 1971). The recency of information in social media may be an especially powerful effect, because users generally are exposed to the most recent posts first, and then, make the decision whether to scroll through other posts. Considering the substantial volume of posts that many consumers access regularly, they likely overweight the most current ones. However, more research is needed to understand the order effects of posts and how sorting functions might affect people’s reading habits, such as when they read reviews. Some related time effects should also be explored. For example, are comments posted in the morning or the evening viewed as more or less credible or engaging? Research into these questions would need to control for the free time that people have available; if recipients only have time to review social media posts in the evenings, they likely focus more on comments posted in the evening, when they can view them in real time, which might reinforce the recency effect.

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Engagement

Each of these five spokes – connectedness, network effects, information, dynamic communication and timeliness (which encompasses convenience) – relates to engagement. Engagement is defined as the repository of past and current social media engagements, which involves consumer interactions with a product, brand or firm. Social media engagement creates a more intimate connection between the firm and the customer. Firms increasingly are investing time and money in creating engagement but also in capturing engagement data. Social media posts contain rich information that a well-equipped company can mine to understand its customers better. It is analogous to a complete, effective CRM data warehouse that incorporates social media. In this issue, Hofacker, Malthouse and Sultan showcase the importance of big data. Customer engagement in social media involves the creation of a multitude of interactions, all of which can serve as one type of big data. Hofacker et al. (2016) offer several provocative research questions associated with big data about the number of messages sent, responses to those messages (e.g. click-through rates), posts, tweets, purchases and repurchases. As a consequence, firms are striving to make profitable customers even more profitable through increased engagement. The power of the Internet, mobility, computing and analytics that harness the power of social connections all have led to a leapfrog advance in the potential to create meaningful engagement with customers.

Conclusion

This article has focused on five drivers of social media engagement: connected effect, network effect, information effect, dynamic effect, and timeliness effect. Each effect has been enhanced and expanded by the introduction of smartphones and tablets, either because the information has become more accessible or by serving as a backdrop for apps that connect more relevant information with the consumer in a focused manner. As the ease of sharing information has increased, the ability to connect with people and learn their opinions, as well as broadcast one’s own personal news or opinions, also has exploded. We propose the Wheel of Social Media Engagement in this article as a foundation on which research efforts can expand. Understanding how to engage effectively with consumers is important for managers, but it also is critical for those consumers. The rest of this special issue focuses on understanding why people use social media, providing methods to analyze social media, exploring the impact of social media on behaviors, understanding the personalization privacy paradox, describing how social media serves as a basis for generating big data and detailing how big data is changing consumer behavior. We are grateful to all the following authors and reviewers for their time and dedication in creating this special issue:

Neeraj Bharadwaj, University of Tennessee

Dipayan Biswas, University of South Florida*

Geng Cui, Lingnan University

Mike Friedman, Louvain School of Management

Richard Hanna, Babson College

Lauren Labrecque, Loyola University, Chicago

Stephan Ludwig, University of Westminster

Dominik Mahr, Maastricht University

Ereni Markos, Suffolk University

Andrew Rohm, Loyola Marymount University

Francisco Villarroel, Maastricht University

Bruce Weinberg, University of Massachusetts

*Served as Editor for the Aguirre, Roggeveen, Grewal and Wetzels paper.

Anne L. Roggeveen and Dhruv Grewal

References

Aguirre, E.M., Mahr, D., Grewal, D., de Ruyter, K. and Wetzels, M. (2015), “Unraveling the personalization paradox: the effect of information collection and trust-building strategies on online advertisement effectiveness”, Journal of Retailing, Vol. 91 No. 1, pp. 34-49. Aguirre, E.M., Roggeveen, A.l., Grewal, D. and Wetzels, M. (2015), “The personalization-privacy paradox: implications for new media”, Journal of Consumer Marketing, Vol. 33 No. 2. Anderson, N.H. (1971), “Integration theory and attitude change”, Psychological Review, Vol. 78 (May), pp. 171-206. Biswas, D., Grewal, D. and Roggeveen, A.L. (2010), “How the order of sampled experiential goods affects choice”, Journal of Marketing Research, Vol. 47 (June), pp. 508-519. Grewal, D., Bart, Y., Spann, M. and Zubcsek, P.P. (2016), “Mobile advertising: a framework and research agenda”, Journal of Interactive Marketing, Forthcoming, Northeastern U. D'Amore-McKim School of Business Research Paper No. 2707300 available at SSRN: http://ssrn.com/abstract=2707300 (accessed 20 October 2015). Hamilton, M., Kaltcheva, V. and Rohm, A. (2016), “Hashtags and handshakes: consumer motives and platform use in brand-consumer interactions”, Journal of Consumer Marketing, Vol. 33 No. 2. Hofacker, C.F., Malthouse, E. and Sultan, F. (2016), “Big data and consumer behavior: imminent opportunities”, Journal of Consumer Marketing, Vol. 33 No. 2. Howard, M.W. and Kahana, M.J. (1999), “Contextual variability and serial position effects in free recall”, Journal of Experimental Psychology: Learning, Memory, & Cognition, Vol. 25 No. 4, pp. 923-941. Ludwig, S. and de Ruyter, K. (2016), “Decoding social media speak: developing a speech act theory research agenda”, Journal of Consumer Marketing, Vol. 33 No. 2. Neath, I. (1993), “Contextual and distinctive processes and the serial position function”, Journal of Memory and Language, Vol. 32, pp. 820-840. Slovic, P. and Lichtenstein, S. (1971), “Comparison of Bayesian and regression approaches to the study of information processing in judgment”, Organizational Behavior and Human Performance, Vol. 6, pp. 649-744. Yuksel, M., Milne, G. and Miller, E. (2016), “Social media as complementary consumption: the relationship between consumer empowerment and social interaction in experiential and informative contexts”, Journal of Consumer Marketing, Vol. 33 No. 2.

About the authors

Anne L. Roggeveen is Professor of Marketing and Faculty Research Scholar, Babson College, Babson Park, MA 02457. Anne L. Roggeveen is the corresponding author and can be contacted at: aroggeveen@babson.edu Dhruv Grewal is Professor of Marketing and the Toyota Chair in E-Commerce and Electronic Business, Babson College, Babson Park, MA 02457.

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