Abstract
One of the crucial trends in business is to offer one-to-one personalized services. In this context, companies try to build customer relationship management systems based on the customer social relations and behavioral patterns. The key issue is predicting to which products or services a particular customer is likely to respond. Additionally, identifying peer-to-peer influence on social network sites is critical to a social media marketing strategies. That is why companies have to learn to understand their customer in the broader social context in order to build successful Customer Relationship Management (CRM) systems, which are described in this chapter. In those systems, the individual customer behavior patterns can be used to build an analytical customer profile. Based on the profile, a company might target a customer with a personalized message. In this chapter, the authors use four research studies in order to extensively present this issue.
TopIntroduction
Living in contemporary world, we leave thousands of digital footprints behind us through usage of mobile phones, credit cards, electronic mail, browsing in social networks etc. Each footprint shows our real actions that we take in given time and place. The analysis of thousands of such footprints on large groups of people allow us to analyze human behavior on an unimaginable before scale in scientific studies concerning psychology and sociology (Lazer, 2009). The results of those analysis will have a significant influence on many disciplines such as medical prophylaxis, political elections or contemporary marketing in personalized customer relationship management. In this context it is interesting to look at the summary of historical development of customer management by Kumar (2008). It begins with direct relations with individual customers, then entire-market customers, segmented customers and finally the return to the initial idea of personalized service usage of interactive marketing (Deighton, 1996). Additionally in light of the current social media marketing challenges the focus switched to digital word-of-mouth (WoM) communication and/or consumer-to-consumer campaigns. Based on this interactive marketing should be extended to use social networks in order to support achieving marketing objectives through social influence (Trusov, Bodapati, & Bucklin, 2010).
According to Kumar, interactive marketing can be described as follows (Kumar, 2008):
- 1.
The Range of Decisions: Identification of interested customers and assuring on-going relations or relations at proper time.
- 2.
The Range of Analysis: Elaborating the complete characteristics of the customer.
- 3.
Value Building Factor: Personalization and adapting proper service at a proper time.
The usage of customer behavior in marketing has a relatively long history. Analytical customer relationship management systems have been used in telecommunications and banking sector since the 90s of the previous century (Shankar & Winer, 2006). In this perspective, new type of data about diversified customer behaviors introduces new opportunities in contemporary marketing. This new potential, related to the development of Business Intelligence systems (Surma, 2011), has contributed to the development of personalized marketing concept based on profound analysis of history of contacts with customer1.
It is important to underline an impact of social influence on the customer behavior. Identifying peer-to-peer influence on social network sites is critical to new social media marketing strategies (Aral & Walker, 2011). Social influence studies are described extensively in Cialdini and Goldstein (2004) paper, and a potential marketing application in on-line social networks are presented in Trusov (2010) research. Social influence mechanisms are widely deployed by companies to develop advertising messages for mass media. Showing people who somehow resemble the message’s recipient, or on the contrary – members of a group to which the recipient aspires, can be perceived as an example of the use of social influence mechanisms. Currently, it is possible to customize advertising messages, based on the given consumer’s level of susceptibility to social influence. Social relationships maintained by the users in on-line social networks to a large extent reflect their personal relationships maintained in the real world. Users perceive other participants as a source of information and aim at identifying with the group (Deutsch & Gerard, 1995).
Key Terms in this Chapter
Social Influence: Occurs when one's emotions, opinions, or behaviors are affected by others.
Interactive Marketing: An identification of interested customers and elaborating the complete characteristics of the customer in order to achieve personalization and adapting proper service at a proper time.
Analytical Customer Profile: A result of abstraction of interactions (time series of customer transactional data, as well as other social and demographic data) in order to generate adequate marketing messages.
Personalization: A process of analyzing (processing) customer data, customization and delivery of marketing output, and interactions with customers for increasing their lifetime value.
Customer Relationship Management: The principles, practices, and guidelines that an organization follows when interacting with its customers.