The effect of social media interactions on customer relationship management

Hoping that direct interaction with customers may raise customer relationships to the next level, more than 100,000 companies to date have established brand pages on social media platforms such as Facebook. Social media are Internet-based applications that allow customers and companies to interact by creating, sharing, or exchanging information (Kaplan and Haenlein 2010). Considering that each company’s social media efforts require substantial investments (e.g., establishing and maintaining brand pages), a fundamental question remains: Are social media efforts worthwhile, and do they translate into better and altogether more profitable customers?

Defining social media interactions as brand-related communication between companies and customers and between customers via company-managed social media channels such as brand pages, this study is based on previous research. Recent research has advocated the value of social media interactions for companies that propose conceptual frameworks to manage brands (Gensler et al. 2013) and customers (Malthouse et al. 2013), develop metrics (Peters et al. 2013), and assess the marketing potential in the social media context (Yadav et al. 2013). However, there is a need for a deeper understanding of the implications of social media (Hennig-Thurau et al. 2013), specifically one based on empirical evidence.

In three explorative studies involving data from a mobile phone provider on customer-level demographics, contract history, customer service requests, and social media usage, we investigate the link among social media interactions with the firm and customers’ upselling behavior, churn, and service contacts. The results indicate that social media interactions indeed ease the upselling efforts and reduce the risk of churn. These positive effects offset the observed increases with regard to the number of service requests and the higher overall service cost. Thus, we ultimately find customers who interact with the brand on social media to be more profitable.

In recent years, social media have become ubiquitous for users and companies. Approximately 1.2 billion people use Facebook worldwide to follow brands (53 % at least once per month), learn more about brands (65 %) or hear of others’ experiences with brands (70 %; The Nielsen Company 2012). Consequently, companies following a multi-channel customer management approach (Neslin et al. 2006; Neslin and Shankar 2009) invest heavily in social media by establishing brand fan pages on which companies convey brand-related content (i.e., brand posts) that users can like, comment on, or share, and the company can react with comments of their own (De Vries et al. 2012; Labrecque 2014). These open, social media-enabled interactions between a company and its customers help create a community that revolves around the brand and fosters the brand relationship (McAlexander et al. 2002; Muniz and O’Guinn 2001). In this study, we analyze the brand-related interactions between customers and a mobile phone provider. The examples provided in the paper hence refer to this context.

Although there is a large body of research on the various positive implications of brand communities (for an overview, refer to Gruner et al. 2014), challenges with respect to the management of customer relationships and its implications on the development and retention of customers, as well as their profitability, remain (Malthouse et al. 2013). Without knowing how social media influence customer relationships, companies struggle to assess the return on their investments. This study addresses this research gap and provides an analysis of the effect of social media interactions with the firm on upselling behavior, customer churn, and service contacts as well as its implications on the profitability of social media activities.

The question regarding how social media interactions influence the post-purchase decisions of customers is crucial for companies. Once customers have purchased a product or service, social media enable customers to share their consumption experience with their social network. For instance, consumers can like, rate, review, or comment on the brand (Hennig-Thurau et al. 2004, 2015). Additionally, customers can actively refer the product or service to others by recommending or sharing information (Yadav et al. 2013). In both cases, the post-purchase involvement helps other users validate their opinions regarding specific products or services (Schau et al. 2009). In this regard, social media interactions resemble word-of-mouth (WOM) in which prospective customers receive product information from trusted sources in their social network (Dichter 1966). However, social media also provides users with a platform to voice negative customer experiences (Hennig-Thurau et al. 2004). For instance, 50 % of social media users express complaints regarding brands at least once per month (The Nielsen Company 2012), which changes customer complaints from a private to a public phenomenon (Ward and Ostrom 2006). Using social media platforms, consumers can cheaply voice their dissatisfaction, easily reach a large audience and, consequently, effectively harm the brand (e.g., Chevalier and Mayzlin 2006; Elsner et al. 2010).

Given companies’ intention to expand customer relationships and to increase customer revenues, WOM affects not only the sales of other customers (Chevalier and Mayzlin 2006; Hinz et al. 2011) but also the sales of the senders, repeat purchases, or additional purchases through up- or cross-selling (Kumar et al. 2010; Armelini et al. 2015). Up- or cross-selling in the mobile phone context could involve extended talk or data plans, hardware, or auxiliary services (e.g., Company: “Upgrade your data plan and get 1 GB data free!”). In this case, social media interactions serve as a source of information from which customers learn about products and services and form their attitude regarding them. This information sharing occurs not only by following company-initiated brand posts but also by actively interacting with the brand (e.g., commenting, liking, or inquiring on information such as User: “I really like the iPhone. When do you start selling it?”). Through such frequent social media interactions, attitudes towards the brand become more accessible for prospective customers. Consequently, the increase in the attitude accessibility facilitates customers’ subsequent purchasing behavior (Downing et al. 1992; Morwitz et al. 1993). Although frequent brand-related interactions via social media and the subsequent increased involvement of customers with positive experiences would reflect higher up- and cross-selling and further developed customer relationships, we would expect the opposite effect for those who voice their negative experiences.

The same applies to the effect of social media interactions on customer churn. The research proposes that customer interactions create engagement value for the company, which has a positive effect on customer retention and, ultimately, the customer value (e.g., Kumar et al. 2010; Van Doorn et al. 2010; Verhoef et al. 2010). In particular, customer engagement, such as participation in positive WOM, increases the commitment and social identification with the brand as well as the brand community and leads to higher customer retention (Brodie et al. 2013). Most likely, only social media interactions that are driven by positive customer experiences would exert similar customer reactions and affect customer retention positively. This effect would certainly not hold for negative customer experiences, which lead to uncertainty regarding the overall effect of social media interactions for companies.

Apparently, the uncertainty regarding the effects of social media interactions on customers’ upselling behavior and churn depends highly on the previous service experience of customers. Hence, reacting appropriately to complaints has become a major challenge (Bolton and Saxena-Iyer 2009; Hennig-Thurau et al. 2010) and an opportunity for both companies and their social media activities. The research indicates that companies that take appropriate remedial actions in a timely manner show that they are sensitive to customer concerns (Van Laer and De Ruyter 2010; Van Noort and Willemsen 2012). If companies respond via social media platforms, the resulting favorable brand evaluations are visible to other customers and have an outreach effect that is nearly equivalent to that of the complaints (e.g., User: “Help. I have had no coverage for 3 h now. Is there a problem with the network?”, Company: “Hello User, have you tried to restart your mobile? If you send us your address, we can check if there is a local disturbance.”). Therefore, adequate customer service via social media, which is called social care, is not only a strategic necessity for customer relationship management (47 % of social media users engage in social care; The Nielsen Company 2012) but also a viable means to reduce customer service costs. Social care can directly manage dissatisfied customers and offer solutions to the problems associated with the complaints (Bernoff and Schadler 2010). In this case, social care replaces costly offline customer service contacts (e.g., via telephone; Aksin et al. 2007). Furthermore, social care promises to be much more efficient than previous bilateral customer service encounters. Companies also benefit from the publicity that successful social media interactions between customers and companies regarding complaints draw. First, customers may be prevented from encountering the same problem and, hence, from experiencing dissatisfaction. Second, customers who encounter the same problem learn about the solution and thus will not need to contact the company to seek a remedy. In this regard, social media interactions in the form of social care could decrease the number of customer service requests and the subsequent costs by replacing and preventing offline customer service contacts.

To determine any meaningful insights into the actual profitability of social media activities, the required investment in such channel needs to be specified as well. Social media interactions with (potential) customers do not come for free but require investments in external consulting (e.g., to determine the social media strategy), internal staff (e.g., community managers) as well as additional spending for building the specific social media site or app (see, for example Digitalbuzz 2011). Such cost are—compared to, for example, advertising—not very transparent though. And despite academic research frequently postulates that they are “relatively low” compared to other channels (see, e.g., Kaplan and Haenlein 2010), industry sources estimate six-digit budgets even for simple campaigns (see Digitalbuzz 2011). A further complication is that the traditional process of spending might not be applicable for social media (see Weinberg and Pehlivan 2011). Hoffman and Fodor (2010) even argue that traditional ROI measures cannot be applied to social media. Rather than focusing on the firm’s investment, marketing managers should look at the customer’s investment when interacting in such channels.

Considering companies’ uncertainty regarding the revenue and cost implications of social media interactions, we report on three empirical analyses that investigate the effect social media interactions have on customers’ upselling behavior, churn, and service contacts.

From a managerial perspective, a key issue is whether the revealed differences between customers with and without social media interactions with the firm translate into economically relevant consequences for their respective profitability. Overall, the results from Studies 1–3 imply that customers who engage in social media interaction are more easily retained and are more likely to upgrade their customer relationships but have more service requests. Considering these mixed effects, we would expect social media-active customers to generate both higher revenues and costs. To test the profitability implications of this assumption, we compared the matched sample of 8330 customers with and without social media interactions from Study 2 with respect to the revenues and costs for the focal company. For this purpose, we focus solely on such positions that vary between individual customers. Revenues include the monthly payments based on the selected flat-rate tariff and the upgrade options (such as the data and SMS flat rate). We cannot disclose the direct interconnection cost (i.e., the percentage of revenue that the network operator is charged by the actual network provider) due to confidentiality reasons. Typically, these interconnection costs are fixed per flat-rate contract; hence, they are independent of the number of calls, SMS, or data volume and are in the range of 60–90 % of the revenues. Because these interconnection costs are identical between the groups of customers, they do not affect the outcome of our analysis.

The costs are retrieved directly from the firm’s internal accounting system and include all variable customer costs, in particular the service costs triggered by contacts via post, email, or phone. For example, we know the exact number of service calls, the exact length of each call, and the attached cost factor for each customer. As a general indication for this industry, call center agents are trained to handle service calls within a 3 min time frame; a typical rate for such a large-scale inbound service operation is approximately 0.50 Euro per minute.

To allow for a valid comparison between customers with and without social media interactions, we report the specific costs of these interactions separately, again using data from internal accounting. The firm employs an in-house team of social media agents who monitor the Facebook page continuously and respond to every post from customers. These fixed costs are attributed to each customer with social media interaction on a per post basis, irrespective of the length or the complexity of the communication. In this industry, the typical rates for such service posts are in the range of a maximum of 1 Euro.⁶

To compare the revenues and costs of both groups with different customer lifetimes, we calculate the average monthly revenues and the average monthly costs per customer.⁷ In accordance with our expectations, the comparison in Table 8 demonstrates that social media-active customers not only generate significantly higher revenues (+11.1 %) but also cause substantially higher customer service costs (+135.1 %). However, even if we account for the additional social media-induced costs, we find that the overall effect on the profitability is positive; the margin with social media interactions is significantly higher (+5.2 % marginal return) than that without social media interactions. This finding confirms that of Libai et al. (2010), who suggested that customer interactions in social communities can build customer equity.

Of course, this positive return is dependent on an efficient handling of social media interactions, which is easier to achieve for large-scale operations that handle hundreds of thousands or millions of customers. To test the robustness of our finding, we conducted a scenario analysis that assumes a wide range of cost per post. We find that in our empirical application, the break-even for the fostering social media interactions’ approach costs approximately 5 Euro per post, which is several multiples of the actual cost per post that was observed, although the firm employed a conservative cost attribution. For firms that can leverage larger scale effects (e.g., telecommunication providers often have millions or tens of millions of customers) or utilize outsourcing to low-cost countries overseas (which is not possible, for example, for a provider in the German language area), the potential returns of a social media interaction strategy may be considerably higher.

This study provides a wide range of empirical insights that indicate that the interaction of customers with a firm through social media channels eases the upselling efforts and reduces the risk of churn but increases the number of service requests for this group of customers. Considering all of the analyses, corrected for selection biases and possible endogeneity issues, the results demonstrate that the significant differences in customers’ upselling behavior, churn, service contacts and, ultimately, profitability are actually caused by the specific interactions of customers through the brand page. For example, the higher propensity to upgrade the contract could be due to higher loyalty, which is fostered by active participation in the brand community. In addition, the results imply that although the brand page interaction may not help preemptively resolve questions or concerns, they do indeed increase customers’ tendency to engage in “real” dialogue with the company. This finding is supported by the significantly higher number of events in the traditional service and support channels, such as the call center or email. Experiencing the company’s response to customer queries in social media certainly lowers the customer’s inhibition threshold to contact the company via other channels.

Given the exploratory nature of these studies and the novelty of this research domain, we face several limitations that must be considered. First, the setting in the telecommunication industry has certain particular characteristics, such as the common 24-month contracts, which are not applicable to other fields. Although the observation period of more than 850 days is definitely not short by general standards, observations throughout multiple contract periods would provide potentially valuable further insights into customer retention.

Second, although we have access to an extensive range of customer data, certain limitations remain. Due to legal restrictions, we are not able to identify or track the social media activities of customers outside the brand page. Additionally, the analysis of the actual contents of the interactions is limited. Thus far, a very basic evaluation of the overall valence of initial posts in a specific thread is available (ca. 46 % of these first posts have negative tonality, and ca. 54 % have positive to neutral tonality). Though the found effects hold despite this large share of negative comments, future research may more closely examine the role of sentiment (Schweidel and Moe 2014). Such additional data would also help to account for heterogeneity, particularly in those exploratory studies that are currently based on simple mean comparisons. While we capture observable heterogeneity by including key control variables (such as gender, age, or acquisition channel) in our multivariate models, future research should try to consider unobserved heterogeneity as well. This applies in particular to future developments of the rather hands-on approach of our profitability analysis.

Finally, research into the causal mechanisms of social interactions that lead to higher profitability requires additional approaches, such as laboratory or field experiments or other, more behavioral techniques. Such approaches would especially help determine whether social media interactions are rather reflections of underlying attitudes or actually forming the attitudes regarding the product or service in question.

However, this study’s results already indicate that social media interactions may influence customer management variables and, ultimately, profitability. Given the initial insights of this study and, in particular, the significant difference in the profitability between the groups with and without social media interaction, this topic is highly relevant for marketing managers and will surely provide substantial opportunities for further research.