Data-Driven Customer Centricity: CRM Predictive Analytics

Data-Driven Customer Centricity: CRM Predictive Analytics

Othman Boujena (Neoma Business School, France), Kristof Coussement (IESEG School of Management, France) and Koen W. de Bock (IESEG School of Management, France)
DOI: 10.4018/978-1-5225-5643-5.ch084
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Customer relationship management (CRM) is becoming a very hot topic nowadays in academia and business environments. Indeed, companies are constantly searching for new innovative ways to create or maintain their competitive advantage. Due to the recent advances in Internet and technology, CRM predictive analytics is becoming an important tool in the toolset of the marketer. It is the practice of using the huge volumes of historical customer data to predict future customer behavior. This chapter introduces the reader to the shift towards a data-driven customer centricity approach, where marketers act upon what they know, rather than upon what they think.
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Within an economic context characterized by high competition and globalization, companies are investing in customer relationship management (CRM) to increase satisfaction and ensure loyalty. This priority is in line with the shift that marketing paradigm experienced from transactional or traditional approach to relationship one (Grönroos, 1995; Gummesson, 1997). In other words, the challenge is not any more on simply selling or converting customers but on developing value creating relationships. For a long time, achieving sales was the unique success indicator of marketing initiatives. This change in customer marketing is related to different factors like markets’ evolution, the limited approach of 4P’s that seems to ignore the human dimension of marketing, the degree to which the 4P’s could be replicated in different business models related to services or retailing and the development of marketing as a science and function within companies.

From theoretical point of view, relationship marketing (RM) refers to strategies and initiatives dedicated to the development and maintaining of long term and win-win relationships with customers. This definition covers some main elements like interactivity, time perspective and mutual benefits. Compared with previous dominant models, this approach is more focusing on demand and empathy. However, RM is not supposed to be only oriented toward the final customer but should consider other stakeholders that play a critical role in the success of company’s marketing and strategy. For example, retailers have the opportunity to interact directly with customers by selling products and providing some services. Consequently, companies should develop strong relationships with their retailers given their strategic role in the chain.

As far as the difference between RM and CRM is concerned, CRM is simply considered as RM that uses technology for managing and interacting with customers. Even, CRM is also used in managerial context to describe technological solutions dedicated to customers’ management.

While many CRM projects (70% on average) fail or do not manage to reach objectives, many academic calls are made to consider CRM first as a company strategy and orientation (Zablah, Bellenger, & Johnston, 2004). In fact, the decision to focus on the customer and align all processes for better satisfaction and loyalty should be a corporate and top management willingness and initiative. The way the company shape and implement customer management is supposed to be consistent with the brand DNA. In other words, the company must start from its business model, the claim and positioning of its brand to integrate customers’ expectations and value creation mechanisms before designing the CRM strategy. According to Payne and Frow (2005), CRM is “an initiative that unites the potential of relationship marketing strategies and IT to create profitable, long-term relationships with customers and other key stakeholders. It provides enhanced opportunities to use data and information to both understand customers and cocreate value with them’’.

Thus, CRM contribute to profitable relationships thanks to better customer knowledge that is enabled by data and information processing. This cycle is mainly facilitated by technology functionalities through the improvement of information collection, storage and diffusion processes. In general, CRM has three components: (1) organizational or strategic, (2) analytical and (3) operational as indicated in the Figure 1.

Figure 1.

CRM components


The strategic component of CRM refers to company’s philosophy and approach of relationship marketing. It is about corporate culture, vision and employees’ involvement in the process. The analytical component is related to the strategic usage of customer data to better understand, model and predict market responses. At this level, information can be related to customer identification or customer behavior. Finally, the operational level covers marketing automation (leads and marketing campaigns monitoring), sales force automation (SFA) (set of applications dedicated to help the sales force in its daily tasks and accounts’ management) and service automation (front office interaction and after sale service through call centers or other channels).

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