Improving Sales Efficiency Through Information Technology Deployment In Business Markets

Transcription

1 Improving Sales Efficiency Through Information Technology Deployment In Business Markets KONSTANTINOS RIGOPOULOS ED PEELEN HENRY ROBBEN* * Konstantinos Rigopoulos is a PhD candidate at Nyenrode Business Universiteit, Promithea 2, 68100, Alexandroupolis, Greece. Ed Peelen is Professor of Marketing, Founder / partner of ICSB Marketing en Strategie, Barbizonlaan 76, 2908 ME Capelle a/d Ijssel, Postbus AM Rotterdam, The Netherlands. Henry Robben is Professor of Marketing at Nyenrode Business Universiteit, P.O. Box AC, Straatweg BG Breukelen, The Netherlands. Correspondence about this article can be sent to: K.Rigopoulos@nyenrode.nl Authors note The first author thanks The Greek State Scholarships Foundation for its financial support.

2 1. Introduction and Theoretical Background The theoretical significance of customer relationship management (CRM) has been widely recognized in the marketing literature. Though there have been conflicting results in both academic research and the business environment, empirical studies have demonstrated that there is a positive relationship between CRM practices and firm performance (Boulding, Staelin, Ehret, and Johnston, 2005). During the past decades relationship marketing has undergone tremendous growth due to widespread beliefs that it leads to improved financial performance (Parvatiyar and Sheth 2000). The practical challenge, however, lies in how well employees in the firm adopt and implement CRM based tactics and strategy. Customer relationship management software and philosophy can help sales through sales force automation to improve in terms of customer satisfaction, performance and efficiency but its implementation cannot be taken for granted because it is up to sales force to make a proper use of CRM capabilities and select the channels and the substitutes to support sales. In the present research, we focus on the key elements that determine the adoption and process of customer relationship management in sales and we connect this adoption to the buyer-seller relationship outcome. Sales representatives perceiving the CRM system as a positive element that enhances the quality of their work and that the system fits their routines tend to use it more (Speier and Venkatesh, 2002). Based on their position-related goals they adopt specific characteristics of CRM systems in order to sell more, to advice their customers better, and to take more effective strategic decisions. Finally, the way they face critical incidents in the buyer-seller relationship (Van Doorn and Verhoef, 2008) and the way they create a reciprocal behavior to their customers (Palmatier et al., 2009) determine the relationship outcome in the long run. As a consequence, when CRM systems are used for serving a long-term, mutually beneficial business relationship, the outcomes of this relationship could be more beneficial both for buyer and seller companies. Despite the initial enthusiasm for customer relationship management, it has had mixed success; Shannahan et al. (2010) quote industry evidence that most CRM projects result in either losses or no bottom-line improvement in company performance. Thus, there is a motivation for selecting CRM interventions more effectively. Different markets or segments may need different ways of tracking down loyal customers and different evaluations of loyalty. Moreover, it is certainly true that within any given company, the monthly cost of maintaining a relationship with an individual customer-not just for the actual transactions but also for communications through mailings, telephone, and so forth-vary enormously (Reinartz and Kumar, 2002). Indeed, some research suggests that up to 70% of CRM initiatives result in either losses or no improvement in company performance, largely as a result of deficiencies in implementation (Reinartz, Krafft, and Hoyer, 2004). Even though some studies deal with relationship marketing issues in business-tobusiness (B2B) interactions (Rodriguez and Honeycutt, 2011; Ryals, 2005), no research has documented the returns from specific B2B investments in relationship marketing programs, or else has explained how to leverage these investments for specific clients. This is quite unexpected given the academic and managerial interest in measuring marketing productivity and customer-level effects (Bolton, 1998; Bolton et al., 2004; Gupta and Lehmann, 2005; Johnson and Selnes, 2004; Cui et al., 2012). In addition, two aspects perplex the investigation of customer-specific payoffs of customer relationship management in sales. First of all, different relationship marketing programs (financial, social, and structural) may build different types of relational bonds and norms that generate varying levels of return (Berry, 1995; Bolton et al., 2003; Cannon et al., 2000). Secondly, returns from relationship marketing programs may vary according to factors 2

3 associated with any of the relational participants (customer, salesperson, selling firm), but the factors for each participant influence a different set of relational bonds (Reinartz and Kumar, 2000; Sirdeshmukh et al., 2002). Customer factors affect returns from relationship marketing investments only for that customer, whereas salesperson factors influence the efficacy of relationship investments for all customers handled by that salesperson, and selling-firm factors leverage investments across all the customers of a selling firm. However, we argue that by controlling for specific customer, salesperson and market characteristics, the application of CRM in sales by the individual sales person will be transparent enough to see why such initiatives end up to success or failure. Moreover, taking into account and controlling specific market conditions and characteristics the questions regarding the way a CRM system can add value to a sales organization will be answered. 2. Methodology The present research focuses on individual salespersons and the way they use CRM tools/databases in an ongoing relationship with customers taking into account traits such as reciprocal behaviors (Palmatier et al., 2009) and critical incident resolution (Van Doorn and Verhoef, 2008). Through an experimental procedure, sales representatives working in business to business markets will be divided to two teams. Each of them will respond to real life business relationships incidents having a description of two given markets, one with high technological and market instability (smart phone market) and one with low technological and market instability (building construction material market). The questions of the experiment have been pretested with actual sales representatives of the two aforementioned markets through semi-structured questionnaires. The scales have been checked for their validity in a previous study (Rigopoulos et al 2012). The adoption process from perceptions about the CRM systems to the usage of them according to sales goals and the effects or relationships outcomes, such as the critical incident resolution and the customer reciprocity generation (Palmatier et al., 2009), will be examined in a three rounds setting, creating a pseudo-longitudinal series of events. Structural equation modeling is going to check the relationships between the constructs of the model and how they evolve over time to check whether there are affects from relationship dynamics or learning curves. The results will be compared in a game theoretical setting and more specifically, with the results of the prisoner s dilemma approach. The prisoner's dilemma (or prisoners' dilemma), which is a canonical example of a game analyzed in game theory, shows why two individuals might not cooperate, even if it appears that it is in their best interests to do so (Segal and Hershberger, 1999). We propose that the relationship dynamics and the market characteristics affect the overall buyer-seller relationship outcome following the Nash equilibrium and therefore the overall success or failure of CRM efforts in business markets. In other words, we will explore how individual sales people use customer relationship management software. We assume that the way they use it relates to the way they treat their relationship with their customers, whether they are looking for short-term profitability or for maximizing customer lifetime value. We also assume that CRM will be found to be more helpful for sales representatives who are looking for a mutually beneficial relationship with their customers and less helpful for the ones that prefer a win-lose relationship, an equilibrium that is similar to Nash equilibrium. We focus on critical incidents resolution and reciprocal behaviors since currently in the literature these two aspects are predominant for the duration and the profitability of business to business relationships. In case our data support 3

4 the hypotheses we may then propose for which cases and under which circumstances CRM implementation can be really successful and under which circumstances, no matter how well CRM is implemented, there would be no improvements in sales performance whatsoever. 3. Conclusion The results of customer relationship management implementation in sales have attracted interest of academics and practitioners during the last decade. There are plenty of articles that contradict whether their results justifty the CRM investment (Ahearne et al., 2007; Speier and Venkatesh, 2002). The contribution of this study lies in the fact that there are no studies that examine the CRM adoption from the view of individual salespersons, taking into account how they adopt the system, how they perform, and which kind of relationship they want to establish with their customers. Moreover, there is no study that examines buyer-seller relationship dynamics under the prism of the Nash equilibrium that is a good predictor for human behavior phenomena. Finally, the experimental setting tries to mimic the context in which salespersons operate in that it examines the way how CRM systems can add to sales performance over a given period of time, with multiple measurements. 4. References Ahearne, Michael, Douglas E. Hughes, Niels Schillewaert (2007), Why sales reps should welcome information technology: Measuring the impact of CRM-based IT on sales effectiveness, International Journal of Research in Marketing, 24 (May), Bolton, Ruth N. (1998), A Dynamic Model of the Duration of the Customer s Relationship with a Continuous Service Provider: The Role of Satisfaction, Marketing Science, 17 (February), Bolton Ruth N., Katherine N. Lemon, Peter C. Verhoef (2004), The Theoretical Underpinnings of Customer Asset Management: A Framework and Propositions for Future Research, Journal of the Academy of Marketing Science, 32 (summer), Boulding, William, Staelin Richard, Ehret Michael, & Johnston Wesley J. (2005), A Customer Relationship Management Roadmap: What Is Known, Potential Pitfalls, and Where to Go, Journal of Marketing, 69 (October), Cannon, J.P., R.S Achrol and G.T. Gundlac (2000), Contracts, Norms, and Plural Form Governance, Academy of Marketing Science, 28(2), Cui Geng, Leung Man Wong, and Wan Xiang (2012), Cost-Sensitive Learning via Priority Sampling to Improve the Return on Marketing and CRM Investment, Journal of Management Information Systems, 29 (Summer), Gupta Sunil Dominique Hanssens, Bruce Hardie, Wiliam Kahn, V. Kumar, Nathaniel Lin, Nalini Ravishanker, S. Sriram (2006), Modeling Customer Lifetime Value, Journal of Service Research, 9 (November), Johnson, M.D. and F. Selnes (2004), Customer Portfolio Management: Toward a Dynamic Theory of Exchange Relationships, Journal of Marketing, 68 (April), Palmatier Robert, Jarvis Burke, Bechkoff Jennifer, Kardes Frank (2009), The Role of Customer Gratitude in Relationship Marketing, Journal of Marketing, 73 (September), Parvatiyar Atul and Jagdish N. Sheth (2001), Customer Relationship Management: 4

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