Pacific B usiness R eview (International)

A Refereed Monthly International Journal of Management Indexed With Web of Science(ESCI)
ISSN: 0974-438X(P)
Impact factor (SJIF):8.603
RNI No.:RAJENG/2016/70346
Postal Reg. No.: RJ/UD/29-136/2017-2019
Editorial Board

Prof. B. P. Sharma
(Principal Editor in Chief)

Prof. Dipin Mathur
(Consultative Editor)

Dr. Khushbu Agarwal
(Editor in Chief)

A Refereed Monthly International Journal of Management

Testing the Effects of Customer Relationship Management (CRM) Practices on Customer Acquisition

Author

Subhasish Das

Ph D scholar

CUTM,Jatni, Odisha,India,

subhasish@giet.edu .in

Manit Mishra

Associate Professor

IMI,Bhubaneswar, Odisha, India

manit.mishra@imibh.edu.in

Prasanta Kumar Mohanty

Dean

School of Management CUTM Jatni, India,

prasanta.mohanty@cutm.ac.in

Abstract

The key purpose of the study is to test the effect of CRM practices on customer acquisition. The study is based on the framework of eight blocks of successful CRM, developed by the Gartner group. The study considers the principal components of CRM such as CRM vision, CRM strategy, customer experience and organizational collaboration of the Gartner framework and shows their effects on customer acquisition. The study includes primary data collected from the employees of a selected retail store in Bhubaneswar. The study finds significant effect of CRM vision and organizational collaboration on customer acquisition. Though CRM vision and customer experience have some effect on customer acquisition but they are not statistically significant. The study uniquely contributes to the extant literature by practically analyzing the impact Gartner’s CRM model, as much empirical studies on this model is not done yet. Further, it not only tests the practicality of Gartner’s model but also checks the efficacy of the practices followed by the retailer, there by suggesting the spaces for added development. Keywords: CRM, CRM practices, customer acquisition.

Introduction

CRM is the most sought marketing theme in the last decade. Relational marketing or CRM puts the customer at the center of the company and directs all activities towards them. Collects customer data from different points of contact, analyzes them to understand the customer and develop suitable offers. Integrate all company channels to get a unified view of the client.CRM can give its best results if applied at a company level. It must be promoted by senior management and should not be treated as the sole responsibility of the marketing department.The main objective of CRM is to acquire, develop and retain customers (Pahuja and Verma, 2008). Gartner Group, one of the world's leading CRM researchers, has suggested CRM best practices such as vision, strategy, customer experience, organizational collaboration for customer acquisition and retention (Gartner, 2003). This study tries to understand the effect of CRM practices on customer acquisition.

LITERATURE REVIEW

CRM is a process of converting customer information into a relationship (Osarenkhoe& Bennani, 2007). CRM acquires profitable customers and retains them (Jauhari, 2001; Seeman & O 'Hara, 2006). Gartner's true CRM consists of eight basic components: vision, strategy, valuable customer experience, organizational collaboration, process, information, technology and metrics (Eisenfeld and Nelson, 2003). The vision of CRM includes practices such as "developing CRM leadership from the top", "understanding how CRM will change the company" and "understanding how CRM is unique to your company" (Kirkby, 2001). The CRM strategy includes "developing a long-term road map for decisions towards", "thinking CRM as a combination of people, processes and technology", "a clear articulation of objectives and tactics to achieve them and" understanding all customers as not equal "(Kirkby, 2001) Similarly, the customer experience includes" Involve the customer in the CRM process "," Integration of all channels "and" Manage change and communication with customers and get the basics first "(Kirkby, Thompson and Wecksell, 2001) .Finally, the organizational collaboration includes" Establishment of multifunctional teams "," Integration of change management and training from the beginning "and" Appointment of a leader global CRM "(Radcliffe, Thompson and Eisenfeld, 2001).

 Basing upon the above literature the following hypothesis is developed
H1: CRM Vision affects customer acquisition
H2: the CRM strategy affects the acquisition of customers
H3: customer experience affects customer acquisition
H4: organizational collaboration affects the acquisition of customers.

RESEARCH METHODOLOGY

It is a descriptive study based on primary data. Survey respondents are employees of a store called "Pantaloons" in Bhubaneswar. The study includes almost all the employees in the shop and the study sample is 284. Table 1 describes the demographic composition of the respondents.

Scale

The study measures variables such as the CRM vision, the CRM strategy, the customer experience, the organizational collaboration and the acquisition of clients. The CRM vision, the CRM strategy, the customer experience, the organizational collaboration are independent variables and the acquisition of customers is the dependent variable. A scale of 15 articles is used, 12 for the CRM practices and 3 for the acquisition of clients (Machiette, Bart & Roy, 1992, Radcliffe, Thompson &Eisenfeld, 2001, Reinartz, Werners, Kumar, 2000). A pilot test is performed with a sample of 30 respondents to verify if the scale is appropriate (Hair et al., 2007). Thus, the scale is used to collect data from 278 respondents. The structural equation model (SEM) is used to analyze the data. SEM includes exploratory factorial analysis (EFA) and confirmatory factor analysis (CFA). EFA checks the suitability of the scale and CFA checks the structural relationship.

Construct validity

The validity of constructs can be verified with the help of convergent validity and discriminating validity. Convergent validity verifies the extent to which the items truly represent the construct and the discriminating validity verifies the extent to which the elements do not represent the constructs with which they are unrelated (Hair et al., 2007). To verify reliability, composite reliability must be greater than 0.7. To verify convergent validity, the extracted mean variance (AVE) must be greater than 0.5 (Bagozzi and Yi, 1988). The AVE values of all constructs must be greater than the maximum shared variance (MSV) for discriminating validity (Fornell and Lacker, 1981). From table 2 we can conclude that the constructs are reliable and valid.

The measurement model is nothing but a confirmatory factorial analysis (CFA). It explains the degree to which the measured variables represent constructs (Hair et al., 2007). The CFA is performed with the help of version 20 of AMOS (Analysis of Motion Structures). Several indices are used to test model fit, RMSEA, GFI, AGFI, NFI, CFI and χ2 / df. The value of RMSEA must be less than 0.08. The values of GFI, AGFI, NFI and CFI must be greater than 0.9. The value of χ2 / df should be less than 2.5 (Gerpott et al., 2001, Homburg & Baumgartner, 1995, Hair et al., 2006). The measurement model of the study can be seen below in Fig-1.

The model fit indices can be seen from the Table-3. It shows that the values of χ2/df is 1.503<5, RMSEA is 0.042<0.08, GFI 0.946>0.9, AGFI 0.920<0.9, NFI 0.96>0.9, CFI 0.986>0.9. Therefore, the values of the fit indices are as per the required measures hence the measurement model is fit and adequate. The items of constructs are truly representing the hypothesized constructs (Teo, 2011).

The Structural Model

Since the measure is adequate and adequate, we can verify the structural relationship between the constructs through a structural model. The structural model can be seen from fig-2.

From Table -4 it is also evident that the structural model shows a good model fit, since all the indices are within the limits of the threshold. Therefore, the relationship between constructs can be verified with the help of regression weights

From Table-5 we can see that the effect of only CRM vision and organizational collaboration are significant at p= 0.000 with estimates of -0.222 and 0.358 respectively. Therefore, the practices related to the vision and organizational collaboration of CRM have a significant influence on the acquisition of the client, but the CRM view has a negative impact, while the organizational collaboration positively influences the Pantaloons.

CONCLUSION

From the analysis, it can be concluded that the successful Gartner CRM framework has a significant effect on customer acquisition. If implemented correctly, the framework can be effective for acquiring customers. Organizational collaboration practices, such as leadership development, understanding the uniqueness of CRM and how it can help, the creation of multifunctional teams can be useful for gaining more customers. The results of the study agree with (Seeman, O'Hara, 2006) that showed a positive influence of CRM in the acquisition of customers. Reinratz et al. (2004) and Becker et al. (2009) also found a positive relationship between CRM and customer life cycle management.

REFERENCES

Anderson, J. L., Jolly, L.D, & Fairhurst, A.E. (2007). Customer relationship management in retailing: A content analysis of retail trade journals. Journal of retailing and consumer services, 14, pp. 394-399.

Bagozzi, R., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of academy of marketing sciences, 16, pp 74-94. http://dx.doi.org/10.1007/BF02723327

Becker, J. Greve, G. & Albers, S. (2009). The impact of technological and organizational implementation of CRM on customer acquisition, maintenance, and retention. International Journal of Research in Marketing. 26. 207-215. 10.1016/j.ijresmar.2009.03.006.

Buttle, F. (2009). Customer relationship management: Concepts and technology. Burlington, USA: Elsevier.

Campbell, D. T. (1959). Convergent and discriminant validation by the multitraitmultimethod matrix. Psychological Bulletin, 56, pp.81-105. doi: 10.1037/h0046016.

Crowley, S.L. & Fan, X. (1997). Structural Equation Modeling: Basic Concepts and Applications in Personality Assessment Research, Journal of Personality Assessment, 68 (3), pp. 508-531.
 Das, S., Mishra, M. Mohanty, P.K. (2018). The Impact of Customer Relationship Management (CRM) Practices on Customer Retention and the Mediating Effect of Customer Satisfaction. International Journal of Management Studies, V, 1(4), 95-103. DOI: 10.18843/ijms/v5i1(4)/15 DOIURL: http://dx.doi.org/10.18843/ijms/v5i1(4)/15
Das, S., Mishra, M. Mohanty, P.K. (2018). A Structural Equation Modeling approach to understand the Impact of Gartner’s CRM Practices on Customer Retention" , International Journal of Management Studies, V,2(4), 56-63. DOI: 10.18843/ijms/v5i2(4)/06 DOI URL: http://dx.doi.org/10.18843/ijms/v5i2(4)/06

Diamantopoulos, A. &Siguaw, J.A. (2000). Introducing LISREL. London: Sage Publications.

Everett, C. (2002). The slings and arrows of CRM. Computing, 18, 25−35

Elaine D. Seeman, Margaret O'Hara, (2006): Customer relationship management in higher education: Using information systems to improve the studentschool relationship, Campus-Wide Information Systems, Vol. 23 Issue: 1, pp.24-34, https://doi.org/10.1108/10650740610639714

Eisenfeld, B.,& Nelson, S. (2001). CRM best practices: from vision to collaboration (COM-21-1015). Available from: http:// www.gartner.com/ Id-117541.

Fornell, C., &Lacker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18, pp.39-50.

Gerpott, T.J., Rams, W., &Schindler, A (2001). Customer retention, loyalty and satisfaction in the German cellular telecommunications market. Telecommunications policy, 25(4), 249-269.

Hair, J. F., Jr., Anderson, R. E.,Tatham, R. L., Babin, B. J., & Black, W. C. (2007).Multivariate data analysis (6th international ed.). Delhi: Dorling Kindersley (India) Pvt. Ltd

Homburg, C., &Baumgartner, H. (1995). Beurteilung von Kausalmodelen.Marketing, 17(3), 162e176

Hooper, D., Coughlan, J. & Mullen, M. R. (2008). Structural equation modeling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6 (1), pp. 53 – 60. Available online at www.ejbrm.com

http://www.siebel.com/what-is-crm/software-solutions.shtm

Hu, L.T. &Bentler, P.M. (1999). Cutoff Criteria for fit Indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6 (1), 1-55

Johnson, D., Anderson, E, &Fornell, C. (1995). Rational and adaptive performance expectations in a customer satisfaction framework. Journal of consumer research, 21(4), 695-707.

Kirkby, J. (2001). Creating a CRM vision (TG-14-9470). Available from: http://www.gartner.com/Id-103196

Kirkby, J. (2001). Developing a CRM strategy (TU-14-9475). Availablefrom: http.

Kirkby, J., Thompson, E. &Wecksell, J. (2001). Customer experience: The voice of the customer (TG-14-9567). Available from: http:// www.gartner.com/ Id-350573

Lai, F., Hutchison, J., Li, D, &Bai, C. (2007). An empirical assessment and application of SERVQUAL in mainland china’s mobile communications industry. International journal of quality and reliability management, 24(3), 244-262.

Radcliffe, J. (2001). Eight building blocks of CRM: A framework for success, Gartner. Available from: http://www.gartner.com/Id-350581.

Radcliffe, J., Thompson, E. &Eisenfeld, B. (2001). True CRM requires organizational collaboration (DF-14-6658). Available from: http:// www.gartner.com/ Id-350571

Tabachnick, B.G. &Fidell, L.S. (2007). Using Multivariate Statistics (5th Ed.). New York: Allyn and Bacon.

Teo, T. (2011). Factors influencing teachers' intention to use technology: Model development and test. Computers & Education 57 (4), 2432-2440.

Wheaton, B., Muthen, B., Alwin, D., F., & Summers, G. (1977). Assessing Reliability and Stability in Panel Models. Sociological Methodology, 8 (1), 84-136.