INTRODUCTION:

Customer Relationship Management (CRM)

In the business environment, CRM is a known concept and not every entrepreneur and executive of any organization can afford to ignore this aspect for business sustenance and growth. Rapid advances in information and communication technologies provide greater opportunities for the companies to establish nurture and sustain long-term relationships with their customers than before. Their main objective is to convert these relationships into profitability by reducing acquisition costs and increase repeat purchases. Olef Walberg et.al (2009) researched that CRM received increased attention amongst practitioners and academia during the last two decades and it is common that any new management or marketing philosophy receives its own share of confusion, misunderstanding and myths. CRM is no exception. Even then, CRM is considered as a powerful strategy to increase profitability of organizations and many investments are made on it by several organizations. But the returns are not up to the expectations for majority of organizations.

According to Armstrong and Kotler (2003) “CRM is one of the most promising marketing developments and it can give tremendous effect when it is used right. The aim of CRM is to transform relationships into increased profitability by reducing cost of customer acquisition; increase repeat purchases. Jonghy Yoek Kim, et al, (2003) say that it is a broad term for managing interactions with customers. William Boulding et.al (2005) suggests that CRM can be understood as implementation of specific technology solutions to a holistic approach of managing customer relationships that simultaneously create firms and customers value. Keith Fletcher (2001) feel that CRM’s are not worth their investments as it needs high investments and CRM is a failure. Situations also aroused where CRM is understood only as a software solution and not as a concept or a strategy. This created a need to look back by organizations to try and understand as to what actually CRM is. Len Tiu Wright et.al, (2002) says that CRM is an attitude that pervades the company, but it needs a solid foundation of knowledge of customers. Lior Arussy⁷ (2005) defined CRM as the process of separating a firm’s high value and low-value customers for the purpose of providing them differential levels of service. Bryon Foss et.al (2008) says that despite enormous growth and acquisition, critics point out high failure rate of CRM projects.

This study includes the analysis of customers view in maintaining CRM practices, their opinions on requirement of CRM practices by the service providers and perceptions regarding satisfaction, retention, repurchase and in referring to new customers and the enhancement, which can be made through good relationship management practices. Added to it the opinions of people who are likely to have close contact with customers i.e., dealers and executives are analyzed.

Research Methodology:

Need for the study:

As stated in the introduction CRM is a concept rather than software. This should be first understood buy users and the makers of CRM solutions (software). Considering it in such a way created a lot of unnecessary hype and criticism in spite of being a powerful and useful concept. The need to have a clear understanding of the role CRM practices can play in the organizations to support and improve the businesses still exists. Studies also reveal that organizations considered CRM as an effective tool/concept from their view and thought on requirements of customers but actual customer’s perceptions on CRM and its practices were not properly made. A study regarding customers point of view can provide value addition to understand a clear role of CRM and its practices in the present business scenario.

Objectives of the study:

1. To identify the scope of CRM practices in relation to customer preferences and purchase decisions.

2. To understand the impact of CRM practices as competitive advantage on market share and volume of sales.

3. To understand whether CRM practices lead to customer loyalty and long-term customer retention

Scope of the study:

The scope of the study is limited to the telecom sector and CRM effects from customer’s point of view. It is also assumed that study of clusters in the twin cities of Hyderabad and Secunderabad can give meaningful insights for generalization of CRM practices and customer satisfaction.

Sampling Method and Composition:

Cluster sampling method is followed for the purpose of data collection. Care is taken that almost all corners and major areas of twin cities of Hyderabad and Secunderabad are covered. The respondents include telecom network users (customers), dealers /distributors and executives of telecom network. The total sample for which data is collected is 300. For each category of respondents i.e., customers, dealers/distributors and employees the sample considered is 100. It may be reiterated that the Chronbac Alpha (details shown in the following tables) in all cases is above 0.5, indicating the reliability of statistics. A time of about four and half months from middle of May 2009 to October 2009 was spent to collect the data.

Table1. Sample composition (*One dealer can have more than one network distribution)

Telecom company	Customers	Dealers*	Employees
Tata	18	90	7
Reliance	9	94	20
BSNL	17	67	16
Air Tel	38	97	13
Idea	18	99	10
Vodaphone	18	99	23
Air Cel	4	0	8
Others	1	62	3
Total	100	100	100

Table 2. Sample Composition by Age

Age Group	Customers	Dealers
Under 20	7	0
20-30	59	46
30-40	20	35
40-50	10	17
50-60	3	2
60 and above	1	0
Total	100	100

Table3. Sample composition of customers and dealers with same telecom network.

Duration with telecom company network	Customers	Executives	Dealers
Recently	5	0	0
Up to 6 months	6	6	9
>6 months to <1year	16	19	24
I year to 4 years	39	35	28
>4 years	34	40	39
Total	100	100	100

Reliability tests

Category	No. of Items	Cronbach’s Alpha
Customers	14	0.737
Executives	26	0.503
Dealers/Distributors	26	0.677

Sources of data:

The major source of data collection is Primary data for this study. Three questionnaires were constructed to three categories of respondents to whom it was felt that can provide real picture for the purpose of the study. The first questionnaire was targeted to customers of telecom network i.e., people who use a telephone and have telecom network. The second questionnaire was targeted to executives and third questionnaire to dealer/distributors of telecom network. All the employees and sellers of all telecom companies recharge cards provision come under these categories.

Secondary data is collected mostly from research papers and articles in journals for literature review. Websites like ibacnet.org, business tepper.cmu.edu, sciencedirect.com, eurojournals.com, indiajournals.com, necsi.edu etc were referred to collect some literature.

Limitations of the study

The study is confined only to the study of effectiveness of CRM practices on customer satisfaction leading to loyalty, their intensions to retain, repurchase and reference to others by the customers and their frequent contact people i.e., dealer’s and executive’s opinions on customers responses. The analyses and generalizations are confined to these findings.

Data Analysis and Results:

Customers:

Pearson Chi-Square test of relations with network provider and various factors:

H1₀: There is no significant difference between ranking of good network coverage and the relations with network provider. - Rejected

H2₀: There is no significant difference between ranking of reasonable price and the relations with network provider.- Rejected

H3₀: There is no significant difference between the availability at convenience and the relations with network provider- -Not Rejected

H4₀: There is no significant difference between good customer relations and the relations with network provider- Rejected

H5₀: There is no significant difference between good extra offerings and relations with network provider- Not rejected

Factors	Value	df	Asymp.Sig (2-sided)
Good network coverage	20.891	12	0.052
Reasonable Price	24.314	12	0.018
Availability at convenience	7.239	12	0.841
Good customer relations	22.545	12	0.032
Good extra offerings	12.695	12	0.392

Pearson Chi-Square Test of various factors affecting other factors:

H6₀: There is no significant difference between relations with network provider and contact with network provider- Not Rejected

H7₀: There is no significant difference between contacts with network provider and customer satisfaction with network- Not Rejected

H8₀: There is no significant difference between rank of satisfaction and customer satisfaction with network and continuity of network- Rejected

H9₀: There is no significant difference between suggestion to friends and repurchase of same network- Rejected

Main factor	Affecting factor	Value	df	Asymp. Sig (2-sided)
Relations with network provider	Contact with network provider	18.192	12	0.110
Contacts with network provider	Customer satisfaction with network	18.306	12	0.107
Rank of satisfaction	Customer satisfaction with network	71.284	6	0.000
Rank of satisfaction	Continuity of network	33.336	8	0.000
Suggestion to friends	Repurchase of same network	90.844	16	0.000

Factor analysis:

Descriptive Statistics:

	Mean	Std. Deviation	Analysis N
Good network coverage	3.56	1.274	100
Reasonable Price	3.47	1.176	100
Availability at convenience	3.64	1.115	100
Good customer relations	3.62	.940	100
Good extra offerings	3.56	1.122	100

The above table explains the five factors of purchase and their mean and standard deviation values

Correlation matrix:

	Good network coverage	Reasonable Price	Availability at convenience	Good customer relations	Good extra offerings
Good network coverage	1.000	0.187	0.257	0.120	0.040
Reasonable Price	0.187	1.000	0.030	0.017	0.327
Availability at convenience	0.257	0.030	1.000	-0.113	0.017
Good customer relations	0.120	0.017	-0.113	1.000	0.098
Good extra offerings	0.040	0.327	0.017	0.098	1.000

The above table explains the five factors of purchase and their correlation within the factors and no factor has correlation above 0.8, which means all factors are different from each other.

The above scree plot shows the classification of 5 factors into 3 factors as per relativity

Component transformation matrix:

Component	1	2	3
1	0.797	0.560	0.227
2	-0.439	0.795	-0.418
3	-0.415	0.233	0.880

Extraction method: Principal component analysis, Rotation method: Varimax and Kaiser Normalization

The above 3D figure shows the classification of 5 factors into 3 factors as per relativity

Executives:

Pearson Chi Square test of executive’s perception on CRM advantage and various modes of contact:

H1₀: There is no significant difference between CRM advantage and SMS, voice free calls and contact centers mode of contact- Not Rejected

H2₀: There is no significant difference between CRM advantage and Enquiries and other modes of contact- Rejected

Factors	Value	df	Asymp.Sig (2-sided)
SMS	6.705	3	0.082
Voice contact	1.979	3	0.577
Free calls	6.427	3	0.093
Enquiries	9.726	3	0.021
Contact centers	6.610	3	0.104
Other modes	7.969	3	0.047

Pearson Chi Square test of executive’s perception on CRM advantage and types of advantages:

H3₀: There is no significant difference between CRM advantage and Customer satisfaction, Customer loyalty, Customer repurchases and New purchases through customer’s positive references- Not Rejected

H4₀: There is no significant difference between CRM advantage and Customer retention- Rejected

Factors	Value	df	Asymp.Sig (2-sided)
Customer satisfaction	16.149	12	0.185
Customer loyalty	10.135	09	0.340
Customer retention	20.614	12	0.056
Customer repurchases	14.415	12	0.275
New purchases through customer’s positive references	14.782	12	0.254

Factor Analysis:

Descriptive Statistics:

Factors	Mean	Std. Deviation	Analysis N
Uses of CRM Customer Satisfaction	4.51	0.916	100
Customer Loyalty	4.30	0.810	100
Customer Retention	4.10	1.000	100
Customer Repurchase	4.43	0.756	100
Positive References	4.38	0.919	100

The above table shows the mean and standard deviation values of five uses of C

Correlation matrix:

Factors	Customer Satisfaction	Customer Loyalty	Customer Retention	Customer Repurchase	Positive References
Uses of CRM Customer Satisfaction	1.000	0.486	0.319	0.001	0.272
Customer Loyalty	0.486	1.000	0.349	0.299	0.307
Customer Retention	0.319	0.349	1.000	0.330	0.156
Customer Repurchase	0.001	0.299	0.330	1.000	0.141
Positive References	0.272	0.307	0.156	0.141	1.000

The above table explains the advantages of CRM and their correlation within the advantages don’t have correlation above 0.8 which means all reasons are different from each other

Total Variance Explained:

Component	Initial Eigen Values			Extraction sums of Squared Loadings			Rotation sums of squared loadings
Component	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	2.103	42.056	42.056	2.103	42.056	42.056	1.738	34.755	34.755
2	1.044	20.870	62.926	1.044	20.870	62.926	1.409	28.171	62.923
3	0.824	16.477	79.403
4	0.616	12.313	91.716
5	0.414	8.284	100.000

The above table shows that five uses of CRM are concise to two factors

Correlation matrix:

	Q 12.1	q 12.2	q 12.3	q 12.4	q 12.5	q 12.6	q 12.7	q 12.8	q 12.9	q 12.10
Q 12.1	1.000	0.130	0.091	0.113	0.013	0.128	0.268	-0.011	0.115	-0.003
q 12.2	0.130	1.000	-0.325	0.638	0.057	0.551	-0.096	0.582	0.150	0.571
q 12.3	0.091	-0.325	1.000	0.353	-0.122	-0.182	0.254	-0.260	-0.042	-0.188
q 12.4	0.113	0.638	-0.353	1.000	-0.172	0.523	-0.218	0.675	0.005	0.675
q 12.5	0.013	0.057	-0.122	-0.172	1.000	-0.221	0.145	-0.125	0.286	-0.185
q 12.6	0.128	0.551	-0.182	0.523	-0.221	1.000	-0.203	0.471	0.071	0.482
q 12.7	0.268	-0.096	0.254	-0.218	0.145	-0.203	1.000	-0.179	0.004	-0.214
q 12.8	-0.011	0.582	-0.260	0.675	-0.125	0.471	-0.179	1.000	-0.045	0.645
q 12.9	0.115	0.150	-0.042	0.005	0.286	0.071	0.004	-0.045	1.000	0.012
q 12.10	-0.003	0.571	-0.188	0.675	-0.185	0.492	-0.214	0.650	0.012	1.000

The above table explains the ten reasons for change of network provider and their correlation within the reasons and no reason has correlation above 0.8 which means all reasons are different from each other

Total variance explained:

Component	Initial eigen values			Extraction sums of squared loadings			Rotation sum of squared loadings
Component	Total	% of variance	Cumulative %	Total	% of variance	Cumulative %	Total	% of variance	Cumulative %
1	3.593	35.931	35.931	3.593	35.931	35.931	3.525	35.252	35.252
2	1.458	14.582	50.513	1.458	14.582	50.513	1.418	14.185	49.436
3	1.299	12.993	63.506	1.299	12.993	63.506	1.407	14.070	63.506
4	0.869	8.692	72.198
5	0.770	7.696	79.894
6	0.549	5.491	85.385
7	0.525	5.252	90.637
8	0.341	3.411	94.048
9	0.325	3.254	97.302
10	0.270	2.698	100.00

Extraction method: Principal Component Analysis

The above table shows the ten reasons for no CRM and same demand are concise to three factors

Component transformation Matrrix

Component	1	2	3
1	0.985	-0.174	0.001
2	0.098	0.559	0.823
3	0.144	0.811	-0.568

The above table shows the transformation values of concise to 3 factors

The above figure shows the distribution of ten reasons for no CRM and same demand distribution into three components or factors.

Dealers:

Pearson Chi-Square test of CRM effect on customer purchase and network selection on various factors

H1₀: There is no significant difference between CRM effect on customer purchase and network selection with relation to H1_0a: Location advantage; H1_0b: Availability, H1_0c: Good network coverage, H1_0d: Brand name and H1_0e: Good relationships and responses of network provider - Not Rejected

Factors	Value	df	Asymp.Sig (2-sided)
Location	4.429	12	0.974
Availability	14.451	16	0.565
Good Network coverage	12.856	16	0.683
Brand name	18.035	16	0.322
Good relationships and responses of network providers	18.893	16	0.274

Pearson Chi-Square test of various factors affecting customers purchase with relationships leading to customer satisfaction:

H2₀: There is no significant difference between availability, good network coverage, brand name lead to customer satisfaction -Not Rejected

H3₀: There is no significant difference between location, and good relationships and responses of network provider and relationships lead to customer satisfaction- Rejected

Factors	Value	df	Asymp.Sig (2-sided)
Location	17.129	9	0.047
Availability	16.545	12	0.168
Good network coverage	20.480	12	0.059
Company Brand name	15.815	12	0.200
Good relationships and responses of network providers	21.262	12	0.047

Pearson Chi-Square Test of CRM effect on customer purchase and network selection and CRM effect on customer satisfaction:

H4_0: There is no significant difference between CRM effect on network selection and purchase and CRM effect on customer satisfaction- Rejected

Value

Asymp. Sig.

(2-sided)

Pearson Chi-Square

69.167

0.000

Factor Analysis:

Descriptive Statistics:

Reason for Change 13.1	Mean	Std. Deviation	Analysis N
Reason for Change 13.1	4.12	1.033	99
q 13.2	3.42	1.041	99
q 13.3	3.35	1.053	99
q 13.4	4.06	1.048	99
q 13.5	3.55	0.961	99
q 13.6	3.85	1.044	99
q 13.7	3.36	0.909	99
q 13.8	3.12	1.033	99
q 13.9	3.56	1.062	99
q 13.10	2.86	1.204	99

The above table shows the mean and standard deviation values of ten reasons for customer’s change of telecom network

Correlation matrix:

	Q 13.1	q 13.2	q 13.3	q 13.4	Q 13.5	q 13.6	q 13.7	q 13.8	q 13.9	q 13.10
q13.1	1.000	0.220	0.170	0.456	0.113	-0.088	0.164	0.129	0.013	-0.278
q 13.2	0.220	1.000	-0.178	0.376	0.120	0.308	0.056	0.070	0.412	0.143
q 13.3	0.170	-0.178	1.000	0.147	0.134	-0.100	0.164	0.095	0.213	0.056
q 13.4	0.456	0.376	0.147	1.000	0.287	0.400	0.095	0.022	0.455	-0.082
q 13.5	0.113	0.120	0.134	0.287	1.000	0.165	0.114	-0.204	0.293	0.077
q 13.6	-0.088	0.308	-0.100	0.400	0.165	1.000	-0.039	-0.163	0.353	0.218
q 13.7	0.164	0.056	0.164	0.095	0.114	-0.039	1.000	0.314	0.157	0.122
q 13.8	0.129	0.070	0.095	0.022	-0.204	-0.163	0.314	1.000	-0.140	0.102
q 13.9	0.013	0.412	0.213	0.455	0.293	0.353	0.157	-0.140	1.000	0.238
q 13.10	-0.278	0.143	0.056	-0.082	0.077	0.218	0.122	0.102	0.238	1.000

The above table explains the ten reasons for change of network provider and their correlation within the reasons and no reason has correlation above 0.8, which means all reasons are different from each other

Total variance Explained:

Component	Initial Eigen values			Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
Component	Total	% of Variance	Cumulative	Total	% of Variance	Cumulative	Total	% of Variance	Cumulative
1	2.488	24.884	24.884	2.488	24.884	24.884	2.240	22.403	22.403
2	1.631	16.309	41.194	1.631	16.309	41.194	1.528	15.275	37.678
3	1.405	14.046	55.240	1.405	14.046	55.240	1.478	14.782	52.461
4	1.193	11.927	67.167	1.193	11.927	67.167	1.471	14.706	67.167
5	0.817	8.171	75.337
6	0.675	6.746	82.084
7	0.639	6.388	88.472
8	0.509	5.088	93.560
9	0.384	3.838	97.398
10	0.260	2.602	100.000

The above table shows that 10 reasons for change of network are concise to four factors

The above scree plot shows the distribution of ten factors classified of concise into three components

The above 3 dimension figure shows the classification of ten reasons for change of telecom network into factors as per relativity.

Discussion of results and findings:

Customer’s feedback:

The customers showed that their main factors affecting purchase of network as good network coverage, reasonable price, availability at convenience, good customer relations and good extra offerings. All of them agreed that all these factors surely affect their purchase. From 100 respondents 91 graded that they purchase network to good relations. Cross tabulations and Chi square analysis showed that there is significant difference between ranking of good network coverage, availability at convenience and good customer relations and relations with network provider. This shows that customers care for the way in which the companies are maintaining them. Customers are also able to grade the extent of relations. Cross tabulations and Chi-square analysis also showed that differences exist in customers grading of relations and satisfaction. Based on relations and services customers are able to grade their satisfaction. This shows that they bother for satisfying relationship. Results also show that frequency of contact is not necessary to make customers perceive that their relations are good with their network provider. Chi-square test results also show that there is no significant difference between the contact with network provider and extent of relationship with network provider. Chi-square test results also show that there is no significant difference between the contact with network provider and extent of satisfaction with network provider. This explains that the quality of relationship is more important than frequency of contact with customer. Chi-square test results also show that there is a significant difference between the satisfaction level and rank of satisfaction. This shows that customers are able to express their degree of satisfaction.

Cross tabulation tables identified that 100% of customers who are satisfied with network are not interested to continue with same network. Chi-square test results also show that there is a significant difference between rank of satisfaction and continuity of network. This shows that extent of satisfaction matters in continuity with same network but satisfaction need not affect customer retention always. Chi-square test results also show that there is a significant difference between continuity of the same network provider and suggestion to friends or relatives. This shows it is not necessary that only retaining customers need to add new customers. Chi-square test results also show that there is significant difference between suggestion to friends and repurchase of same network. This also implies that repurchase of customers need not effect to suggest friends or relatives on it network and vice versa.

Dealer’s opinion:

Chi-square analysis results showed that there is no significant difference between availability, good network coverage, brand name and relationships lead to customer satisfaction. This indicates that these factors lead to customer satisfaction. It was also found that there is significant difference between, location, and good relationships and responses of network provider and relationships leading to customer satisfaction, which indicate that these factors are not so effective. Even according to dealers perception CRM is advantageous only to some extent but it is not a major factor to effect customer satisfaction. It was also found that there is significant difference between good customer relationships lead to customer satisfaction and satisfied customers retain with same network provider and refer to others to purchase the same network which indicates that it is not necessary that customers’ satisfaction lead to loyalty and further it may lead to customer retention and positive references. Total 79 positively graded and that CRM practices are effecting customer satisfaction. Total 87 graded positively more that customer satisfaction /satisfied customers retain and refer to others positively about the network providers. For a question where respondents were asked whether they think that demand for telecom companies would not reduce if the existing levels of CRM practices are not made available, total 62 disagreed.

Executive’s perception:

It was accepted by chi-square analysis that there is significant difference between CRM advantage and Customer retention which indicates that advantage of CRM need not reflect in customer retention. It was also rejected that there is significant difference in chi-square analysis that advantages of CRM in customer loyalty, repurchase, satisfaction and positive references indicating that all these advantages are affective. Majority (80 of 100) strongly agreed and 15 agreed (total 95) that maintenance of CRM is advantageous to their company. Total 86 agreed that the contacts are useful in attaining customer loyalty. Total 79 agreed that the contacts are useful in attaining customer retention. Total 91 agreed that the contacts are useful in attaining customer repurchase. Total 88 agreed that the contacts are useful in attaining new purchase through positive customer reference. Data also shows that 90 respondents disagreed that if the company does not maintain good relationships it can have same level of demand. It was observed that in demographics all age groups and all genders had no major differences in their opinions.

REFERENCES:

1. Armstrong, Gary, and Philip Kotler, “Marketing: An Introduction”, 6th ed., Upper Saddle River, NJ: Prentice Hall, (2003).

2. Christopher Meyer and Andre Schwager. “Understanding Customer Experience “,Harvard Business Review South Asia, February 2007

3. Jonghyeok Kim,Euiho Suh,hyun seok hwang “A Model for Evaluating effectiveness of CRM Using the Balance Score card”, Journal of Interactive Marketing, Vol 17 Number 2, spring 2003.

4. Keith Fletcher, “Role of CRM in changing and facilitating competitive advantage”, Journal of Database Marketing, Volume 8, 3, 2006, pg 203-206.

5. Kristol De Wulf, Gaby Odekerken-Schroder and Dawn Lacobucci, “Investments in Consumer Relationships: A cross country and Cross industry Exploration”, Journal of Marketing, Vol. 65, October 2001, pg 33-50.

6. Len Tiu Wright, Prof Merlin Stone and Julie Abbott “The CRM imperative- Practice Vs Theory in the telecommunications Industry, “Journal of Database Marketing”, Vol 9, 4 2002, 339-349 Henry Stewart publications.

7. Lior Arussy, “The economics of customer relationships”, Indian Management, April 2005.

8. Olef Wahlberg, Christyl Standberg, Haken Sundberg and Karl.W.Sandberg, “Trends, Topics and researched areas in CRM Research-ALiterature review,” International Journal of Public Information systems, Vol 3,2009, Pg 191-208.

9. William Boulding, Richard Stealin,Michael Ehret and Wesley.J.Johntson, “A Customer Relationship Management Roadmap: What is Known, Potential Pitfalls and Where to go”, Journal of Marketing,October 2005.

Received on 29.09.2010 Accepted on 20.10.2010

Asian J. Management 1(2): Oct. – Dec. 2010 page 47-54