Empirically investigating the integrating effect of customer feedback and customer satisfaction on customer relationship

management (CRM)

A case study conducted in Pakistan

Tanveer Abbas, Syed Hassan Qasim, Ahmad hassan

Department of management and sciences university of Lahore

Sargodha campus

Abstract customer relationship management is very much border term. Which mean that how an organization builds relationship with their customers? Customer relationship management consider as life line for a business, but this relation has some elements that make this relationship meaningful for a business and one of them is feedback that will identify the real position of business. And the other one is customer satisfaction, which is the mirror of the business. We will identify the relationship between these variables and try to find the status of this relation, is there is strong relationship or week.

1. Introduction increasing market competition is the reason of new innovative market techniques. The pivot of these techniques or strategies is how to build strong relation with the customer. Loyalty of a customer with an organization is based on customer satisfaction and how we can measure the satisfaction level of customer; this is only possible through customer’s feedback. As a result of this process an organization can build strong relations with his customer. Many practical and theoretical models of customer retention have explored satisfaction as a key determinant in customers’ decisions to keep or drop (i.e., discontinue) a given product or service relationship (Bolton 1998, Boulding et al. 1993, Rust and Zahorik 1993, Rust et al. 1995, Zeithaml and Parasuraman 1996). Indeed, satisfaction measures have accounted for up to 40% of the variance in models of customer retention (Reichheld 1996). Despite in substantial investment in Customer relationship management (CRM) applications, there is a lack of research demonstrating the benefits of such investments. In particular, there has been limited research

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on the role and contribution of CRM applications in managing customer encounters (Bitner, Brown, and Meuter 2000; Meuter et al. 2000). Although marketing and information systems researchers have developed theories about the effect of CRM applications, with some progress toward empirical validation (Jayachandran et al. 2005; Reinartz, Krafft, and Hoyer 2004; Romano and Fjermestad 2003; Srinivasan and Moorman 2005), there is limited knowledge about the effect of CRM applications on a firm’s customer knowledge and customer satisfaction. Furthermore, prior research does not shed light on why CRM applications affect customer satisfaction or the role of the feedback.

View of literature:

Customer relationship management is important pillar of a business. In the past there was lack of research work. the literature view is based on work of various authors research work mostly done in the field of CRM. We will evaluate our concerned variables. Here is further view of literature from the published work of different authors and books relating to CRM and its integrated variables. Captain Daniel Maurino explains the reality and strength of CRM. The authors direct their attention to applied research as well particular attention to the link between culture and Crew Resource Management (CRM) training, essential to good CRM explains why adopting a cause suited to your brand is essential to good CRM .'the report named Win Win Win', cause related marketing (CRM) released by Business in the Community toward the end of last year, found that 86% of consumers have a more positive image of a company they see doing something to make the world a better place. Such an impact should not be overlooked. Book of Measuring customer satisfaction (Richard Gerson1993 )

Based on theory from consumer behaviour and cognitive psychology, the purpose of this paper is to discuss and test corporate image and customer satisfaction as two routes to customer loyalty. Based on data from 600 individual customers categorized as having high or low service expertise of three companies within the package tour industry, a conceptual model is proposed and tested empirically using structural equation modelling. The data used in the study are included in The Norwegian Customer Satisfaction Barometer. The paper concludes by claiming that for complex services, corporate image and customer satisfaction are not two separate routes to customer loyalty. Corporate image impacts customer loyalty directly whereas customer satisfaction does not. This finding was consistent with high and low service expertise. These results challenge the disconfirmation paradigm which

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predicts customer satisfaction as the primary route to customer loyalty. From a managerial perspective, information regarding the relative strength of the two routes is vital with regard to resource allocation in order to (Richard Gerson1993.( Tor Wallin Andreassen (Norwegian School of Management, The Graduate School, and Stockholm University, School of Business) Bodil Lindestad (Norwegian Institute for Research in Marketing (NiM) at the Norwegian School of Management, Sandvika, Norway)

Now that relationship marketing is gaining acceptance as a valuable tool for business-to-business firms, it is time to devise and enact more systematic relationship marketing processes. In this article, a comprehensive model for effective relationship marketing is discussed. It includes inputs (understanding customer expectations, building service partnerships, empowering employees, and total quality management), outputs (customer satisfaction, customer loyalty, product quality, and profitability), and assessment (customer feedback and integration). The model is then applied to one industry: automated immunochemistry testing products(Joel R. Evans, RMI Distinguished Professor of Business, 134 Hofstra University)

Self-reports of customer satisfaction regularly possess distributions that are negatively twist and exhibit a positivity bias. Examination of the customer satisfaction literature and empirical investigations shows that measurements of customer satisfaction exhibit tendencies of surprise and methodological pollution and appear to reflect numerous artefacts. Implications and ideas for research and practice are discussed.( Measuring customer satisfaction: Fact and artefact Robert A. Peterson, lliam R. Wilson) We discuss a full Bayesian analysis based on data collected from customers of a leading financial services company. Our approach allows us to explicitly accommodate missing data and enables quantitative judgment of the impact of the drivers of satisfaction across the customer population. We find that satisfaction with product offerings is a primary driver of overall customer satisfaction. The quality of customer service with respect to financial statements and services provided through different channels of delivery, such as information technology enabled call centres and traditional branch offices, are also important in determining overall satisfaction. However, our analysis indicates that the impact of these service delivery factors may differ substantially across customer segments. In order to facilitate managerial action, we discuss how specific operational quality attributes for designing and delivering financial services can be leveraged to enhance satisfaction with product offerings and service delivery. Our approach and findings have

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significant implications for managing customer satisfaction in the financial services industry. (M. S. Krishnan, University of Michigan Business School,) (Venkatram Ramaswamy University of Michigan Business School)

Relevant variables:

Customer relationship feedback

Customer satisfaction

Hypotheses statement:

We can improve customer relationship by using customer feedback and level of satisfaction of our customer.

Material and methods:

The objective of study is to evaluate the relationship of CRM and the customer satisfaction and feedback. The pivot of study to explain the relationship of independent variables on depend variable that is CRM. We can elaborate through the studies that there is cause and effect relationship between variables.

Philosophy:

The study is based on the positivism, because CRM cannot be defined without finding the fact related to customer and its satisfaction. Development of hypothesis is not possible without following positivism. We use two approaches first one is deduction approach and

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Dependent Variables

Independent variables

Customer relationship

Depends

Feedback Customer satisfaction

second on is induction. Through deduction hypotheses will be developed. And after testing this hypotheses a theory will be developed for this purpose induction approach will be applied.

Research strategy:

In survey methodology the max struggle was to find the answers of 5ws. So after all collecting data through different sources like asking question through questioners, interviews and internet sources. There are different customers in the market and everyone has different level of satisfaction. This is the reason for using the method of survey. Overall variables are based on qualitative studies because of weak theoretical frame work and multi-purpose of research.

Unit of analysis:

Every customer has a value for business therefore measuring level of customer is important to keep a customer visiting again and again. Specifically Pakistan is developing country that’s why there is needed to work on CRM. Customer of Sargodha market is unit of analysis because the market of Sargodha still growing. That’s why it is highly needed to which type of CRM is required in this area.

Data collection techniques and tools:

For presenting an authentic and valid data, the data was collected through asking the questions from different respondents. The questioner was based on three sections. Section A contains questions related to our dependent variables that are CRM. In section B that consists of five items exploring the view about importance of feedback. In section C respondent ask to question about third independent variable that is customer satisfaction.

Focusing on target customer of Sargodha market and keeping sample size of 100 data is collected from Sargodha. All respondent ask to answer of three sections which include 5 questions in each section.

Result analysis:

Analysis of results is based on correlation and regression. Correlation explains the relationship between two variables weather there is positive relation between variables or negative relation.

When we talk about consequences of independent variable on dependent variable than we use regression analysis. For the significance of our regression model we use regression results.

Results:

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Correlation shows association between two variables or nature of relationship that if there is positive or negative relation between these variables. In the table there is significance relation between CRM

and independent variables.

Correlations

CRM CS FB

CRM Pearson Correlation 1 .167 .157

Sig. (2-tailed) .096 .119

N 100 100 100

CS Pearson Correlation .167 1 .275**

Sig. (2-tailed) .096 .006

N 100 100 100

FB Pearson Correlation .157 .275** 1

Sig. (2-tailed) .119 .006

N 100 100 100

**. Correlation is significant at the 0.01 level (2-tailed).

REGRESSION ANALYSIS:

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) 1.521 .390 3.901 .000

CS .159 .122 .134 1.300 .197

FB .154 .133 .120 1.160 .249

a. Dependent Variable: CRM

CRM=1.52+0.59CS1+0.15FB2+µ

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