International Journal of Pure and Applied Mathematics
Volume 119 No. 7 2018, 1217-1224
ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)
url: http://www.ijpam.eu
Special Issue
ijpam.eu
MARKETING STRATEGIES OF PRIVATE SECTOR LIFE INSURANCE
COMPANIES IN CHENNAI CITY – AN EMPIRICAL STUDY
Dr. A.G. Vijayanarayanan, Associate Professor, Department of Commerce, Vels University
Mr.Sathish Kumar. V, Research Scholar, Department of Commerce, Guru Nanak College
ABSTRACT
The Insurance sector is growing rapidly in India and has huge market to tap. The present
scenario of private sector life insurance companies gives tough competition to Life Insurance
Corporation. This paper deals with the marketing strategies to cope up the competition. The
technology, tangibles and augmented product delivered by private sector life insurance
companies make them robust and improve the service quality. The paper is empirical in
nature and has identified some of the marketing strategies consisting of eleven variables. The
paper finds that marketing strategies may be progressed by catering to middle income group
and usage of vigilant technology for the millennial generation.
Key words: Perception of Marketing strategy, Claim settlement, redressal of claims, vigilant
technology
INTRODUCTION
The Insurance business has grown swiftly in terms of percentage and volume across
organised and unorganised sector. The Indian Insurance industry ranks 51 across the world in
terms of penetration1.Insurance company increasingly recognise the present customers who
insist on improvement in technology. The Indian life insurance sector stands fifth largest
market in the world. Demographic factors such as rising middle class, young insurable
population and growing awareness of the need for protection and retirement planning will
support the growth of life insurance.
REVIEW OF LITERATURE
The potential for the expansion of the Indian Insurance market is massive and there is a huge
untapped market to be conquered. There exist 24 Life Insurance companies in India. Among
them, the Life Insurance Corporation (LIC) is the sole Public sector and the rest of the 23 are
Private sector life insurance companies. The penetration reached 3.42 per cent in FY 2016
and will cross 4 in FY 2017 as compared to 6.2 per cent of global average.The Government
has increased the coverage from 30 to 40 per cent under PradhanMantriFasalBima
Yojna2.The perceived service quality of the insurance companies has positive correlation on
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attitude towards obtaining insurance3.The company and agent’s service quality have
significant impact on purchasing life insurance products4.
The individual death claims settled by the private sector insurance companies are 91.48% in
FY 2015-2016 as compared to 94.65% in group death claims. The number of offices in
private sector is 6179 as on 2016 which is higher compared to LIC which stands at 4892.5
The exploratory qualitative study revealed the emergence of technology. The overall
customer satisfaction consists of three perceptions – satisfaction with functional services,
satisfaction with agents and satisfaction with company6.
Assurance in terms of trained agents, competence factor, tangibles, corporate image and
technology are the key parameters in deciding the private sector companies.7
OBJECTIVES OF THE STUDY
1. To know the demographic profiles of the policy holders of Chennai city.
2. To identify the underlying dimensions of Perception of Marketing Strategies(PMS)
followed by Private Life Insurance Companies.
3. To examine the significant difference between married and unmarried respondents in each
factor and Total Perception of Marketing Strategies Score.
4. To analyze the impact/influence of Personal Profiles of respondents on their Total
Perception of Marketing Strategies (TPMS).
RESEARCH METHODOLOGY
The intention of this study is to examine the perception of marketing strategies followed by
private sector life insurance companies. The study is analytical in nature and primary data
was collected through a well-designed structured questionnaire. Four private life insurance
companies (ICICI, HDFC, SBI and Bajaj Allianz) located at Chennai were selected for the
study. Five hundred questionnaires were administered to the respondents and 465 filled
questionnaires were received. The perception of marketing strategies of private sector life
insurance companies were considered as variables and measured using 5 point Likert scale
ranging from Highly Satisfied to Highly Dissatisfied. To check the internal reliability of
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scale, Cronbach’s Alpha reliability coefficient was used. The value being 0.627, scale is
fairly consistent and reliable.
STATISTICAL TECHNIQUES USED
The data collected were subjected to Percentage analysis, Descriptive Statistics, Factor
analysis, t test and Multiple Regression Analysis using SPSS Version 17.
RESEARCH FINDINGS
The average age of respondents is 37.77 years. Majority of the respondents are male, married
and are graduates. The respondents belong to joint family and are salaried class of people
earning monthly family income between Rs.40,000 to Rs.60,000. A sizeable portion of
respondents have purchased SBI company insurance policies and have atleast two policies.
(Ref. Table 1 in Annexure)
PMS variables with their communality values ranging from 0.308 to 0.669, have goodness of
fit for factorization. KMO-MSA value of 0.732 and chi-square value of 364.038 with df of
55 and P-value of <0.001 reveal that factor analysis can be applied for factorization of 11
variables. Three dominant independent factors explaining 42.024% of total variance have
been extracted out of 11 Variables. Of them the most dominant factor is Augmented Product
Factor (AUPF), Actual Product Factor (APF) and Core Product Factor(CPF), in the order of
their dominance. (Ref. Table 2 in Annexure)
There exists a significant difference between marital groups in the total perception of
marketing strategies on each of the factors and the TPMS. Married policy holders have
higher level of perception in Augmented Product, Actual Product factor and TPMS.
(Ref. Table 3 in Annexure)
The Multiple Regression Analysis of OLS (Ordinary Least Squares) model has been run to
examine the influence of all personal profiles on TPMS.
Table 4 and Equation 1 show that the occupation and marital status have significant negative
influence on TPMS. As the occupation and marital status increase by one unit the TPMS also
decreases. (Ref. Table 4 and Equation 1 in Annexure)
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SUGGESTIONS
1. The private insurance company should cater more to the middle class people since they are
in large numbers. The insurance company should create awareness for the above people.
2. The policy holders give high priority to augmented product than the actual and core
product. Therefore, the private insurance companies should focus more on augmented
products like value added services, customer redressal, support from staffs and agents etc.,
3. The unmarried policy holders have higher expectations on the perception of marketing
strategies than the married policy holders. Therefore, the expectations of the former should be
met with.
4. Vigilant technology up gradation should be available to the policyholders at all times. This
will considerably reduce the hurdles of the policyholder in all aspects including flexible
payment, mode of payment and settlement of claims.
CONCLUSION
The insurance sector is growing rapidly in India and has created robust growth in mitigating
risk. The Private sector insurance companies after LPG havefacilitated the individuals and the
companies tremendously. The awareness about insurance is geometrically progressing in the
middle class group. Therefore, the insurance companies both public and private should seize
the opportunitiesand should aid the commerce in the near future.
References:
1. Gayathri, H, et al., Journal of Services Research, Volume 5, Number 2, October 2005 –
March 2006
2. Report from Insurance Regulatory and Development Authority, FY 2016
3. Arora, R and Stoner C, (1996), The effect of perceived service quality and name
familiarity on the service selection decision, Journal of Services Marketing 10(1): 22-34
4. Chow-chua, C and Lim, G (2000), A demand audit of the insurance market in Singapore,
Managerial Auditing Journal 15(7): 372-382
5. IRDA Annual Report, 2015-2016 dated 31.3.2016
6. Masood H Siddiqui and TriptiGhosh Sharma (2010), Analysing customer satisfaction with
service quality in life insurance services, 221-225
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7. Masood H Siddiqui and TriptiGhosh Sharma (2010), Measuring the customer perceived
service quality for life insurance services: An Empirical Investigation, International Business
Research, Vol. 3, No.3, July 2010, 171-186
ANNEXURE
Table 1 – Demographic Profile of the respondents
Gender Total
Male Female Observed In %
Observed In % Observed In %
275 59.1 190 40.9 465 100
Age
Mean S.D Median Mode Skew Min Max 465 -
37.77 9.792 36 35 0.705 24 70
years years Years Years Yrs. yrs.
Marital Status
Married Unmarried
Observed In % Observed In %
338 72.7 127 27.3 465 100
Family Size
Nuclear Family Joint Family
Observed In % Observed In %
229 49.2 236 50.8 465 100
Educational Qualification
School Graduate Professional
Observed In % Observed In % Observed In %
88 18.9 312 67.1 65 14 465 100
Occupation
Salaried Business Professional
Observed In % Observed In % Observed In %
Govt. – 126 27.1 122 26.2 85 18.3 465 100
Pvt. -132 28.4
Number of Insurance Policies
One Policy Two Policy More than Two Policy
Observed In % Observed In % Observed In %
143 30.8 224 48.2 98 21 465 100
Monthly Family Income
Less than Rs. Between Between More than Rs.
20,000 Rs.20,000-40,000 Rs.40,000-60,000 60,000
Observed In Observed In % Observed In % Observed In %
%
84 18 108 23.3 166 35.7 107 23 465 100
Company Insurance Policies
ICICI HDFC SBI Bajaj Allianz
Observed In Observed In % Observed In % Observed In %
%
106 22.8 87 18.7 143 30.8 129 27.7 465 100
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Table 2 – Factorisation of Perception of Marketing Strategies (PMS) variables
Factors & % of Variance Variables Factor Communa MSA Mean
their Labels explained Loading lities
16.201 Efficient and supportive staff 0.629 0.417 0.768 3.85
Reasonable price on products 0.601 0.480 0.704 3.90
Factor 1 Designing attractive brochures 0.588 0.402 0.752 3.79
Providing knowledge to policy 0.551 0.318 0.770 3.87
Augmented holders
Product Prompt settlement of claims 0.549 0.308 0.769 3.77
Factor 2 15.763 Different Modes to pay premium 0.631 0.405 0.706 3.86
Actual Flexible periods for premium 0.609 0.428 0.733 3.85
Product payment
Variety of Products 0.602 0.369 0.734 4.39
Vigilant use of technology 0.530 0.343 0.748 3.77
Factor 3 10.059 Better range in sum assured 0.737 0.669 0.658 3.98
Core Product Provides riders and bonus 0.571 0.485 0.659 4.02
KMO-MSA= 0.732, Total % of Variance explained = 42.024
Bartlett’s Test of Sphericity chi-square value of 364.038 with df of 55 and P value of <0.001
Table 3 - Significant of differences between Marital Groups in Perception of Marketing
Strategies Factors and Total Score
Marital Mean S.D t Value Df P Value Inference
Status
Groups
Augmented Product Married 19.515 2.885 3.547 463 <0.001 Significant
Factor Unmarried 18.307 3.405
Actual Product Factor Married 16.112 2.305 2.924 463 0.004 Significant
Unmarried 15.252 2.999
Core Product Factor Married 8.056 1.250 1.655 463 0.099 Not
Unmarried 7.842 1.237 Significant
Total Perception of Married 43.683 4.616 3.955 463 <0.001 Significant
Marketing Strategies Unmarried 41.402 5.854
(TPMS)
Table 4 - Analysis of Variance of influence of all profiles on Total Perception of
Marketing Strategies (TPMS)
Sources of Sum of Df Mean F P-Value
variance Squares Square
Regression 871.225 2 435.612 18.116 0.000
Residual 11109.089 462 24.046
Total 11980.314 464
R R2 Adjusted R2
0.270 7.3% 6.9%
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Equation 1 Values
TPMS = 47.644 -0.868 Occupation - 1.994Marital Status
TPMS = 47.644 – 0.868 occupation (1 Govt. Emp.) – 1.994 Marital status (1 Married) 44.782
TPMS = 47.644 – 0.868 occupation (1 Govt. Emp.) – 1.994 Marital status (2 Unmarried) 42.788
TPMS = 47.644 – 0.868 occupation (2 Pvt. Emp.) – 1.994 Marital status (1 Married) 43.914
TPMS = 47.644 – 0.868 occupation (2 Pvt. Emp.) – 1.994 Marital status ((2 Unmarried) 41.920
TPMS = 47.644 – 0.868 occupation (3 Business) – 1.994 Marital status (1 Married) 43.046
TPMS = 47.644 – 0.868 occupation (3 Business) – 1.994 Marital status (2 Unmarried) 41.052
TPMS = 47.644 – 0.868 occupation (4 Prof.) – 1.994 Marital status (1 Married) 42.178
TPMS = 47.644 – 0.868 occupation (4 Prof.) – 1.994 Marital status (2 Unmarried) 40.184
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