CHAPTER IV

MARKETING PRACTICES AND THE MARKETINGPERFORMANCE OF THE LIC AGENTS

4.1 Introduction

Agents play a vital role in marketing the LIC

policies, since they are given the sole authority to sell the

policies in the target market, the insurable population. The

agents while marketing has to locate a prospect, develop a good

rapport with him, identify his needs and ignite it. He must have

the ability to produce a desire to possess it by presenting the

strong reasons for the insurance purchase. Hence, in this

chapter the marketing practices of popularizing the policies, the

prospect identification, the positioning of the policies and

targeting the customers were studied in relation to the

marketing performance. The inequality in the marketing

performance among the sample respondents was also assessed

with the help of Gini ratio.

4.2 Marketing Performance

The agents have different target customers, sell

different policies, have different business skills and therefore

76

deliver different levels of performance'. Marketing performance

had been studied under two parameters, that is, the coverage

which was represented by the number of policies sold and the

monetary performance which was indicated by the sum assured

mobilized in the year 1999-2000. The coverage performance of

the respondents is presented in table 4.1.

TABLE - 4.1Coverage Performance of the Respondents

in the year 1999-2000

Coverage Number of Cumulative(No. of policies sold) Respondents Frequency in %12-24 31 15.5

25-49 49 40.0

50-74 :39 59.5

75-99 13 66.0

100-124 19 75.5

125-149 12 81.5

>150<=407 37 100.0

It is observed from table 4.1 that the coverage

performance of the respondents was ranging from a minimum of

12 policies to a maximum of 407 policies. It is clear that 40 per

cent of them had a coverage performance of less than 50

policies. Only 18.5 per cent of them had the highest

performance of 150 policies or more. Gini ratio was applied to

77

find the inequality of the coverage performance among the

respondents by using the following formula.

N(Pk - Pk-1) (qk + qkl)

k=1L = 1

10,000

where

L = Gini ratio;

Pk = Cumulative percentage of sample respondents;

qk = Cumulative percentage of coverage performance;

N = Number of classes used in the analysis.

Higher values of the Gini co-efficient indicate greater the degree

of inequality. The value of Gini ratio ranges from 0 to 1.2

The computed Gini Ratio L for the coverage

performance was 0.48, which revealed that there was an

inequality in the coverage performance among the respondents.

Based on the coverage performance of the sample

agents, they were grouped into low, medium and high achievers.

The respondents who had the coverage performance of less than

50 policies were termed low achievers. The respondents whose

performance ranges between 50 to 150 policies were called

medium achievers. The high achievers were those respondents

78

whose performance was 150 policies or more. The different

categories of the respondents according to the coverage

performance are shown in table 4.2.

TABLE - 4.2The Achiever Categories of the Respondents

in Coverage Performance

Achievers Number of PercentageCategories Respondents

Low 80 40.0

Medium 83 41.5

High 37 18.5

200 100

It is clear from table 4.2 that 41.5 percentage of the

respondents were medium achievers topping the list, followed by

low achievers of 40 per cent. The number of high achievers was

comparatively low showing 18.5 per cent only.

The monetary performance of the sample

respondents is shown in table 4.3.

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TABLE - 4.3Monetary Performance of the Respondents

in the year 1999-2000

Monetary Number of CumulativePerformance Respondents Frequency in %(Rs._in_lakhs)

1.20-10 31 15.5

10-20 50 40.5

20-30 30 55.5

30-40 17 64.0

40-50 11 69.5

50-100 28 83.5

100-515 33 100.0

It is observed from table 4.3 that the monetary

performance of the respondents was ranging from Rs. 1.20 lakhs

to 515 lakhs. Further, it is understood that 40.5 per cent of

them had a monetary performance of less than Rs.20 lakhs

Only 16.5 per cent of them had the highest monetary

performance of Rs. 1 crore or more. Thus, the monetary

performance varied widely among the sample agents. The

inequality of the monetary performance had been assessed by

applying the Gini ratio. The calculated Gini ratio L for the

monetary performance was 0.6 1, which confirmed that there

was a high degree of inequality in the monetary performance

80

among the respondents. The inequality in the monetary

performance of the respondents was higher than that of the

coverage performance.

The respondents were grouped on the basis of

monetary performance as low, medium and high achievers. Low

achievers were respondents who had the monetary performance

less than Rs.25 lakhs. The respondents who had the monetary

performance in between Rs.25 lakhs to 1 crore were called

medium achievers. When monetary performance of the

respondents was Rs-1 crore or more, they were called high

achievers. The sample respondents and the achievers

categories in monetary performance are given in table 4.4.

TABLE - 4.4The Achiever Categories of the Respondents

in Monetary Performance

Achievers Number of PercentageCategories Respondents

Low 99 49.5

Medium 68 34.0

High 33 16.5

200 100.0

It is evident from table 4.4 that 49.5 per cent of the

sample respondents were low achievers. The medium and high

achievers were 34 per cent and 16.5 per cent respectively.

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The individual differences among the sample agents

due to the variation in the marketing practices adopted by the

agents on the one hand and the socio-economic and

psychological factors on the other hand might have contributed

collectively to the inequality of the coverage and the monetary

performance. Hence, an attempt was made to study the

marketing practices and the marketing performance of the LIC

agents in Tirunelveli Division.

4.3 Types of MC Policies and their Popularities

The product-mix of the LIC can be grouped into the

following major policy types namely, Whole-life policies,

Endowment type policies, Money Back type policies, Pure Term

Assurance policies, Pension schemes, policies for Children and

Women, Multi-cover and Special need policies and Joint Life

policies.

In Whole Life type policies, the sum assured is paid

only to the nominee or heirs after the death of the insured.

Whole Life policy may be with or without profit and limited

payment or single premium policy. These policies differ on the

basis of premium payment. Generally, premium rates for these

Whole Life policies are low.

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In Endowment type policies, the insured himself

can get the sum assured after the completion of the contract

period. Endowment policies may be with or without profit

policies, Double Endowment policy, Limited payments or Single

premium policies, New Jana Raksha policy, and Marriage

Endowment/ Educational Annuity. Premium is higher in this

type when compared to the whole life policy type. But 'it is lower

than that of the other types of policies.

Money Back type policies provide the insured the

sum assured in two or three instalments as survival benefit at

stipulated time interval during the contracted period. Money

Back policy, New Money Back policy and Jeevan Surabhi are

the Money back type policies.

Special policies are marketed for women and

children aged one to twelve years. Jeevan Kishor, Jeevan

Sukanya and Money Back Children Assurance are to name a

few.

Exclusive pension policies are made available to

provide a source of income after the retirement of the persons.

The pension policies are Jeevan Suraksha, Jeevan Dhara and

Jeevan Akshay.

83

Multi-cover and Special need policies are focused

either on the sum assured, that is, double or triple cover or on

the special needs of health and housing. Jeevan Asha, Jeevan

Giraha, Jeevan Mitra and Asha Deep II are grouped under

Multi-cover and Special need policy types.

Joint Life type policies are designed to cover more

than one live. Jeevan Saathi and Jeevan Santa are sold in this

line and Pure Risk policies are mainly for the young people with

limited income to create an immediate asset at low cost. Bima

sandesh and Bima Kiran policies are the pure risk policies3.

Commission, the remuneration of the agents,

depends on the type of policy and the terms of contract. Agents

are given two kinds of commission. First commission is paid at

higher rates on the first year premium and a minimum rate of

renewal commission on the renewal premium collected is paid

over the terms of the policies. These two commission rates are

varying according to the policy type, term contracted and

premium paying year4 . The chart of Commission rates is given

in Appendix II. Certain types of policies are popular, even

though agents are free to practice all types of policies. The

popularity of the LIC policy types among the sample LIC agents

is presented in table 4.5.

84

TABLE - 4.5LIC Policy Types and their Popularity among the Respondents

Respondents RespondentsName of The Policy Type Practising the not practising Total

Policies the PoliciesEndowment 199(99.50) 1 (0.5) 200

Money Back 198 (99.00) 2(1) 200

Policies for Women and 171 (85.50) 29 (14.5) 200Children

Pension Policy 145 (72.50) 55 (27.5) 200

Multi-Cover and Special 137 (68.50) 63(31.5) 200Need Policies

Joint Life Policies 126 (63.00) 74(37) 200

Who Life Policies 57 (28.5) 143 (71.5) 200

Pure Risk Assurance 51(25.5) 149 (174,5) 200

i lu represeni percentages)

It is clear from table 4.5 that 99.5 per cent of the

agents had been practicing the Endowment type, which was

followed by the Money Back type, that is, 99 per cent. Further,

the policies for children and women were practised by 85.5 per

cent of the agents, which was higher than the pension policy

type of 72.5 per cent. Besides, Multi-cover and Special need as

well as Joint Life policy types were popular among 68.5 per cent

and 63 per cent of the agents studied.

85

Whole Life as well as Pure Risk type were the least

popular policies among the sample agents.

It is found that the Endowment type and Money

Back type policies are very popular among the respondents.

First commission and renewal commission rates are the highest

for endowment type policies followed by money back type. This

might be the reason for the popularity of these types of policies

among the agents. The rates of commission on various policies

were given in Appendix II.

The policies for Children and Women and Pension

plans have got the third and fourth position in the popularity of

the policy types. High cost of higher education, heavy expenses

on marriage and extended retired life due to the advanced

medical facilities have paved way for the positioning of these

policy types. Health care and Housing loan facility are the

special features of the positioning of the Multi-cover and Special

need policies.

Joint Life policy type is not so popular, since it

demands high premium in the form of extra charge and the

Whole Life and the Pure Risk policy types are found to be the

least popular policies. Whole life policies demand the payment

of premium for a very long term. Pure Risk policies are non-

86

participating or without profit and the low commission rates

deterred the agent from popularising these policy types.

It is inferred that the Endowment and Money Back

type policies were very popular among the sample LIC agents.

Whole Life policies and Pure Risk policy types were the least

popular among all the LIC policy types.

4.4 Identification of the Most Popular Life InsurancePolicies

Among the policy types, certain policies are more

often sold by the agents and also the most sought ones by the

customers. The insurance policies are either participating or

non-participating, that is, with profit or without profit. Non-

participating policies are cheaper than participating policies,

but the policyholders are not having the privilege of profit

sharing. On the contrary, the participating policies are costly

that the premium is high and there is a privilege to the

policyholders to participate in the annual profit earned by the

company. The most popular insurance policies practised by the

respondents are given in table 4.6.

87

TABLE - 4.6The Most Popular Life Insurance Policies Practised

by Respondents

Name of the Type of Policy Number of No. ofPolicies Agents Agents not Total

Practised PractisedConventional Endowment 173 (86.50) 27 (13.5) 200EndowmentPolicy

Conventional Money Back 151 (75.50) 49 (24.5) 200Money BackPolicy

New Jana Endowment 74 (37.00) 126(63) 200Raksha

New Money Money Back 74 (37.00) 126(63) 200BackJeevan Mitra Endowment 67 (33.50) 133(66-50) 200

Money BackJeevan cum Term 46 (23.00) 154(77) 200Surabhi Insurance

Bima kiran * Pure Risk 45 (22.50) 145 (77.5) 200

- Non-Participating

(Figures in parentheses indicate percentages)

It is evident from table 4.6 that in Endowment type,

the conventional Endowment had been practised by 86.5 per

cent of the agents and it was the highest among all the popular

policies identified. In Money Back type, conventional Money

Back was practised by 75.5 per cent of the agents studied and it

88

ranked second in the order of popular policies. The New Jana

Raksha and the New Money Back policy were practised by 37

per cent each and were in third place in the order of popular

policies. Further, 33.5 per cent, 23 per cent and 22.5 per cent

of the agents had practised Jeevan Mitra, Jeevan Surabhi and

Bima Kiran policies respectively.

In Endowment type, conventional Endowment

policy of the participating nature was observed to be the most

popular policy among all the policies, since Endowment policy is

the only policy that satisfies the agents with a high rate of

commission (Appendix II) and the policyholders with a

reasonable premium when compared to other participating

policies.

In Money Back type, conventional Money Back

policy with participating facility was the second popular policy

because it has the composite benefit of investment, educational

and marriage needs satisfaction to the customers and a fair rate

of commission (Appendix fl) to the agents

Similar results were observed in the studies

conducted by the National Insurance Academy (1985). Agents

had confirmed that their choice had been mostly in favour of

Endowment or Money Back policy5 . Nagammai and Nair (1991)

89

found that Endowment policy was the most popular policy

followed by Money Back policy6 . Joshi (1991) reported that

Money Back and Endowment policies sold by the LIC in 1988-

89 was 90.59 per cent of the total sale7 . Nagapandy (1994)

found that the agents gave priority for Endowment, Money Back

and New Jana Raksha policies at the time of canvassing8.

Heredia (1997) too commented that the LIC sold more

Endowment and Money Back policies rather than the Pure and

Whole Life insurance policies9.

New Jana Raksha, an endowment type and a low

cost insurance for the large sum assured, was in the third

place. It is a plan for the farmers and remains valid for 3 years

from the last due date even if the premium is not paid, provided

that two year premia have been paid 10 . The New Money Back

policy is a combination of survival benefit and the term

assurance benefit was found to be favoured by the sample

agents and the prospects next to Endowment and Money Back

policies.

Jeevan Mitra, a multi-cover policy is fourth in the

order since it has the benefits of Endowment Assurance along

with the additional insurance cover equal to the sum assured in

the event of death during the term of the policy. Besides, in the

case of accident being the cause of the death, the amount

available is further enhanced. These salient features made it

easier for the agents to position it.

Lastly the Bima Kiran, which was the seventh as

well as the last in the order of the popular policies practised by

the sample agents, is a non-participating policy where there is

no chance for the bonus sharing. This is supported by Joshi

(1991). He found that though non-participating contracts had

lower rates of premium, they were not popular with the

clients 11.

It is inferred that the conventional Endowment and

the conventional Money Back policies were very popular and

Bima Kiran was the least popular among the sample agents.

4.5 Number of Different Insurance Policies Practised andthe Marketing Performance

The sample agents were grouped into two categories

based on the number of different insurance policies practised by

them. They were agents who had practised less than the

calculated average of 5 policies and the agents who had

practised 5 policies or more. The coverage performance of these

two groups of respondents are given in table 4.7.

91

TABLE - 4.7Number of Different Insurance Policies Practised and

Coverage Performance of the Respondents

Number of Low Medium High TotalPolicies Achievers Achievers Achievers Number

Practised (<50 (50-150 (> 150 ofpolicies) policies) policies) Agents

<5 42 26 12 80Policies (52.5) (32.5) (15) (100)

>=5 38 57 25 120Policies (31.67) (47.5) (20.83) (100)

Total 1 80 83 1 37 1 200(Hgures in parentheses represent the percentages)

Calculated x2 value is 8.69Table value for 2 degrees of freedom is 5.99

It is seen from table 4.5 that 120 agents (60 per

cent) were practising more number of policies (>= 5 policies) and

only 80 agents (40 per cent) were practicing less number of

policies (<5 policies). The percentage of low achievers (52.5) was

high in the agent group, which practised less than 5 policies

whereas the percentage of medium achievers (47.5) was high in

the other group. The chi-square test was applied to test the

association between the number of different insurance policies

practised and the coverage performance.

92

Ho: Coverage performance is not associated with the number

of insurance policies practiced by LIC agents.

Ha: Coverage performance is associated with the number of

insurance policies practiced by LIC agents.

The calculated x2 value 8.69 is significant at 5 per cent level.

Hence, the null hypothesis is rejected and it is concluded that

the coverage performance is associated with the humber of

different insurance policies practised. It indicates that the

agents are in a position to attract many people to insurance

when they could comparatively offer more number of different

insurance policies to the customers according to their needs.

The number of different insurance policies practised and the

monetary performance are shown in table 4.8.

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TABLE - 4.8Number of Different Insurance Policies Practised and

Monetary Performance of the Respondentsj_____-

NurherOf

PoliciesPractised

<5Policies

LOW

Achievers(<Rs.25lakhs)

47(58.75)

• MediumAchievers(Rs.25 Iakhs

crore),23

(28.75)

hinAchievers

(>=Rs. 1crore)

10(12.5)

- dialNumber

ofAgents

80(100)

>=5 52 45 23 120Policies (43.33) (37.5) (19.17) (100)

Total 99 68 33 200(Figures in parentheses represent the percentages)

Calculated y2 value is 4.68Table value for 2 degrees of freedom is 5.99

It is observed from table 4.8 that in monetary

performance both the groups of agents had high percentages of

low achievers. The association between the number of

insurance policies practised and the monetary performance was

tested using chi-square test.

Ho: There is no significant association between the number of

different insurance policies practised by LIC agents and

the monetary performance.

Ha: There is a significant association between the number of

different insurance policies practised by LIC agents and

the monetary performance.

The calculated x2 value 4.68 is not significant at 5 per cent level

and so, the null hypothesis is accepted. Therefore, the

association between the number of different insurance policies

practised and the monetary performance is not statistically

significant. That is, the monetary performance is not influenced

by the number of different insurance policies practised by the

agents. It is because that the monetary performance is more

dependent on the ability and willingness of the prospects to buy

than the agents' appeal. It is inferred that practice of different

policies helped the agents to attract more policyholders by

appealing to their diflèrent needs. But, the same factor has not

affected the monetary performance.

4.6 Agents' Knowledge about the LIC Policies and theMarketing Performance

The agents have to educate the customers about

their needs, provide information about suitable policies

available, the special features and the ability to satisfy the

specific needs of the customers. Thus the agents must have

wholesome knowledge about the policies he is handling.

Knowledge in general gives confidence, empowerment and

enlightenment. Hence, the marketing performance of the agents

had been analysed in association with the agents' knowledge

95

about the policies. The respondents were grouped into two

categories on the basis of the average number of policies that

the agents knew. On an average the sample LIC agents knew 19

policies. Agents are categorised into agents knowing less

number of policies (<19 policies) and agents knowing more

number of policies (>=19 policies). The coverage performance of

these two categories is presented in table 4.9.

TABLE - 4.9Agents' Knowledge about the LIC Policies and the

Coverage Performance of the Respondents

Agents' Low Medium High Total

Knowledge Achievers Achievers Achievers Numberabout Policies (<50 (50-150 (> 150 of

policies) policies), policies) Agents

60 52 17 129<19 Policies (46.51) (40.31) (13.18) (100)

>19 Policies 20 31 20 71

(28.17) (43.66) . (28.17) (100)

Total 80 83 37 200(Figures in parentheses represenlirle percenages

Calculated x2 value is 9.54Table value for 2 degrees of freedom' is 5.99

It is noted from table 4.9 that 129 respondents

(64.5 per cent) had knowledge about less number of policies

(<19 policies) and only 71 agents (35.5 per cent) had knowledge

about more number of policies (>=19 policies). The agents

knowing more number of policies had high percentage of

medium achievers (43.66%) in the coverage performance

whereas the percentage of low achievers (46.51%) was high in

the agents group who knew less number of policies.

The Chi-square test was applied to test the

hypotheses:

Ho: Coverage performance is not associated with the agents'

knowledge about the LIC policies.

Ha: Coverage performance is associated with the agents'

knowledge about the LIC policies.

The calculated x2 value 9.54 is significant at 5 per cent level.

Hence, the null hypothesis is rejected and found that there is a

significant association between the agents' knowledge about the

LIC policies and the coverage performance. The agents'

knowledge about the LIC policies and the monetary performance

of the respondents is given in table 4.10.

97

TABLE -4.10Agents' Knowledge about the LIC Policies and the

Monetary Performance of the Respondents

Low Medium High TotalAgents' Achievers Achievers Achievers Number

knowledge (<Rs.25 (Rs.25 lakhs (>=Rs.] ofabout Policies lqkhs) - 1 crore) crore) Agents

<19 Policies 74 42 13 129(57.36) (32.56) (10.08) (100)

>= 19 Policies 25 26 20 71(35.21) (36.62) (28.17) (100)

Total 1 99 68 33 200(Figures in parentheses represent the percentages)

Calculated X2 value is 6.29Table value for 2 degrees of freedom is 5.99

It is seen from table 4.6 that the agents who had

knowledge about more policies than the average number of

policies had 28.17 per cent high achievers in monetary

performance when compared to 10.08 per cent in the agents

group who had knowledge about less number of policies than

the average number of policies. The percentage of low achievers

(57.36%) was high in the agents group knowing less policies

than average number of policies.

The Chi-square test was used to test the

hypotheses:

98

Ho: The monetary performance is not associated with the

agents' knowledge about the LIC policies.

Ha: The monetary performance is associated with the

agents' knowledge about the LIC policies.

The calculated x 2 value 6.29 is significant at 5 per cent level and

hence, the null hypothesis is rejected. Therefore, it is concluded

that there is a significant association between the monetary

performance and the agents' knowledge about LIC policies.

The foregoing analysis revealed that the agents who

had knowledge about more number of policies (> = 19 policies)

had comparatively high percentage of medium and high

achievers in both the coverage and the monetary performance.

The chi square tests have also proved that there is a significant

association between the marketing performance and the agents'

knowledge about the LIC policies in both the coverage and the

monetary performance.

4.7 Major Sources of Prospect Identification

The first step in demand creation is the

identification of prospects. More prospecting leads to more

sales. The prospecting is vital only when 22 per cent of the

potential insurable population including a 28 percentage of the

income-tax payers 12 is covered so far. Successful prospecting

needs information about the prospects. Ten easily available and

commonly accessible sources of information to the agents were

listed and the number of agents using that sources were

enumerated. The major sources of prospect identification used

by the respondents are presented in table 4.11.

TABLE-4.11Major Sources of Prospect Identification used

by the Respondents

Agents using Agents notName of Sources the Sources using the Total

SourcesPolicy Holders 170 (85.0) 30(15) 200(Clients)

Relatives 148 (74.0) 52(26) 200

Neighbours 145(72-5) 55 (27.5) 200

Social Functions and 119(59-5) 81(40.5) 200Cultural Festivals

Friends 101 (50.5) 99 (49.5) 200

Self Approaching 91(45.5) 109 (54.5) 200Prospects

Co-Passengers 69 (34.5) 131 (65.5) 200

Professional 59 (29.5) 141 (70.5) 200Directories

Telephone Directories 26(13) 174(87) 200

Newspaper 17(8.5) 183(91-5) 200Advertisements

(Hgures in parentheses indicate the percentage)

100

Table 4.11 exhibits that 85 per cent of the

respondents were using the existing policyholders' lead which

was the first in the sources of identification of new prospects.

The second popularly used source of prospect identification was

the relatives, which was followed by the neighbours. They were

used by 74 per cent and 72.5 per cent respectively. Further,

social functions and cultural festivals were used by around 60

per cent, which was followed by friends, that is, 50.5 per cent.

It is seen that 45.5 per cent of them were contacted by the

prospects themselves and the co-passengers were used by 34.5

per cent of the agents. But, the most well organized sources of

information like the professional and telephone directories as

well as the newspaper advertisements were used only by a

minority of the agents, that is, 29.5 per cent, 13 per cent and

8.5 per cent of the agents respectively.

The existing policyholders are the first and the

foremost sources of prospect identification because the

policyholders who are satisfied with the services of the agents

either recommend the agents to their relatives and friends or

give their addresses to the agents. This is supported by the

views of Joshi (1991). He said that satisfied client was able to

give a few leads to the agents of his friends, relatives, colleagues

101

etc. 13 Mishra (1991) stated that the LIC had depended on the

existing policyholders for the expansion of its business'. The

other commonly used sources of prospect identification are

found to be the relatives, neighbours, social functions and

cultural festivals and friends. This may be due to the fact that

familiarity counts more in selling insurance service. This is in

line with the findings of the study of Allan (1998) who concluded

that non-cold call prospecting method significantly led to higher

level of sales performance. Cold call prospecting, that is,

initiating contact with a person that is not expected to receive

such a contact, had no significant impact on the sales

performance 15•

It is found that existing policyholders were the most

popularly used sources of prospect identification.

4.8 Time Spent towards New Prospects and the MarketingPerformance

The agents who determined to succeed have to

spend their time wisely and profitably in the presence of the

buyers. The most precious time is that time which is spent for

helping the prospects to buy the LIC policies. Sonnentag and

Kleine (2000) found that the amount of current time spent on

deliberate practice was significantly related to the supervisory

102

ratings of the insurance agents' performance 16 . Some agents

spent more time on servicing the old customers and less on new

prospects or vice versa. The average time spent by the

respondents for the prospects was found to be 3.24 hours per

day. Thus, the agents under study were grouped into two

categories for this analysis as agents spending less than the

average time and agents spending the average or more time per

day. The coverage performance of these two groups of the

respondents is shown in table 4.12.

TABLE - 4.12Time Spent for New Prospects and the Coverage

Performance of the Respondents

Low Medium High Total

Time Achievers Achievers Achievers Number

Spent (<50 (50-150 (>= 150 ofpolicies) policies) policies) Agents

<3.24Hours per 59 48 17 124

Day (47.58) (38.71) (13.71) (100)

>=3.24 21 35 20 76Hours per (27.63) (46.05) (26.32) (100)

Day

Total 1 80 83 37 200(1-Igures In parentheses represent the percentages)

Calculated X2 value is 9.34Table value for 2 degrees of freedom is 5.99

It is evident from table 4.12 that 124 respondents

representing 62 per cent were spending less time (< 3.24 hours

103

per day) for new prospects and only 76 respondents, that is, 38

per cent were spending more time (>=3.24 hours per day). More

than one fourth (26.32 per cent) of the agents who had spent

more time (>=3.24 hours per day) were high achievers along

with a 46.05 per cent medium achievers in the coverage

performance. But only 13.71 per cent and 38.71 per cent

respectively were high and medium achievers respectively in the

agents group who had spent less time (3.24 hours per day).

Chi-square test was used to test the hypotheses:

Ho: The coverage performance is not associated with the

time spent by the LIC agents towards new prospects.

Ha: The coverage performance is associated with the

time spent by the LIC agents towards new prospects.

The calculated x2 value 9.34 is significant at 5 per cent level and

hence the null hypothesis is rejected. Therefore there is a

significant association between the coverage performance and

time spent by the agents towards new prospects. This is

because the agents, who are spending more time for new

prospects are able to meet more persons, do wide prospecting

and thus, can sell more number of policies than that of their

counterparts. The monetary performance and the time spent by

104

the sample LIC agents towards new prospects are given in table

4.13.

TABLE-4.13Time Spent for New Prospects and the Monetary

Performance of the Respondents

Low Medium High TotalTime Spent Achievers Achievers Achievers Number

(<Rs.25 (Rs.25 lakhs (>=Rs.1 oflakhs) - 1 crore) crore) Agents

<3.24Hours per 67 38 19 124

Day (54.03) (30.65) (15.32) (100)

>=3.24 32 30 14 76Hours per (42.11) (39.47) (18.42) (100)

DayTotal 99 68 33 200

(Figures in parentheses represent the percentages)

Calculated X2 value is 2.71Table value for 2 degrees of freedom is 5.99

It is clear from table 4.11 that majority of the

sample LIC agents irrespective of the time spent towards new

prospects were low achievers followed by medium achievers in

monetary performance.

The Chi-square test was used to test the

hypotheses:

Ho: There is no significant association between the time spent

by the LIC agents towards new prospects and the

monetary performance.

105

Ha: There is a significant association between the time spent

by the LIC agents towards new prospects and the

monetary performance.

The calculated x2 value 2.71 is not significant at 5 per cent level

of significance. Hence, the null hypothesis is accepted and it is

inferred that there is no significant association between the time

spent towards new prospect and the monetary performance.

This is because the monetary performance depends more on the

purchasing power, liquidity and expected return on the

investment rather than the agents' appeal.

The analysis indicates that there is a statistically

significant association between the coverage performance and

the time spent towards new prospects. But there is no

significant association between the monetary performance and

the time spent towards new prospects.

4.9 Time Spent on Servicing the Old Customers andthe Marketing Performance

Service is the hallmark of the high performers. Life

insurance transaction is not a sell and forget affair for two

reasons. All insured persons are not having insurance to the

expected family requirements or financial capacity of the

106

persons and thereby opportunities for further sale are ever

waiting at the doors of their clients. Again satisfied clients can

drive many new prospects towards the well servicing agents.

Meeting the policyholders again and again and making himself

available for the service to the policyholders at their need are

the foundation for strengthening the marketing relationship,

which automatically leads to high performance. The calculated

average time spent on servicing the old customers was found to

be 2.43 hours per day. The agents were grouped into two

categories as agents spending less than 2.43 hours (less time)

and agents spending 2.43 hours or more (more time) per day.

The marketing performance of these two groups was analysed.

The coverage performance of these two groups is given in table

4.14.

107

TABLE - 4.14Time Spent for Servicing the Old Customers and the

Coverage Performance of the Respondents

Low Medium High TotalTime Spent Achievers Achievers Achievers Number

(<50 (50-150 (>= 150 ofpolicies) policies) policies) Agents

<2.43 Hours 56 36 18per Day (50.91) (32.73) (16.36) 110

(100)>=2.43 Hours 24 47 19 90

per Day (26.67) (52.22) (21 .1 1) (100)

Total 80 83 37 200(Figures in parentheses represent the percentages)

Calculated X2 value is 12.41Table value for 2 degrees of freedom is 5.99

It is noted from table 4.14 that 110 agents (55 per

cent) were spending less time than the average time per day on

servicing the old customers and only 90 agents (45 per cent)

were spending the average or more time per day.

Moreover, the agents who had spent the average or

more time per day on servicing the old customers were found to

be better performers when compared to their counterparts, that

is, 52.22 per cent and 21.11 per cent of the sample LIC agents

who spend the average or more time per day on servicing the old

customers were medium and high achievers respectively in the

coverage performance. Only 32.73 percent and 16.36 per cent

108

of the other groups were the medium and high achievers

respectively.

The Chi-square test was applied to test the

hypotheses:

Ho: There is no significant association between the time spent

on servicing the old customers and the coverage

performance of the respondents.

Ha: There is a significant association between the time spent

on servicing the old customers and the coverage

performance of the respondents.

The calculated x2 value 12.41 is significant at 5 per cent level of

significance. Thus, the null hypothesis is rejected and it is

found that there is a significant association between the

coverage performance and time spent on servicing the old

customers. The time spent by the sample LIC agents on

servicing the old customers and the monetary performance are

presented in table 4.15.

109

TABLE - 4.15Time Spent for Servicing the Old Customers andthe Monetary Performance of the Respondents

Low Medium High TotalTime Spent Achievers Achievers Achievers Number

(<Rs.25 (Rs.25 lakhs (>=Rs.1 of

lakhs) - crore) crore) Agents<2.43 Hours 64 27 19 110

per Day (58.18) (24.55) (17.27) (100)

<2.43 Hours 35 41 14 90per Day (38.88) (45.56) (15.56) (100)

Total 99 68 33 200(Figures in parentheses represent me per i iuYt:.-Z')

Calculated x2 value is 10.24Table value for the degrees of freedom 2 is 5.99

Similar trend as that of the coverage performance

had been observed in the monetary performance too, that is,

45.56 per cent of the agents who had spent the average or more

time per day were medium achievers along with a 15.56 per cent

high achievers. Only 24.55 per cent and 17.27 per cent of the

other group were medium and high achievers respectively.

The Chi-square test was applied to test the

hypotheses:

Ho: There is no significant association between the monetary

performance and the time spent on servicing the old

customers.

110

Ha: There is a significant association between the monetary

performance and the time spent on servicing the old

customers.

The calculated x2 value 10.24 is significant at 5 per cent level

and so, the null hypothesis is rejected. Therefore, it is found

that there is a significant association between the monetary

performance and the time spent on servicing the old customers.

The marketing performance analysis showed that

comparatively more percentage of medium and high achievers

among the agents who are spending the average or more time

per day on servicing the old customers are found in both the

coverage and the monetary performance. Again the chi square

tests have also confirmed that the marketing performance in

terms of both the coverage and the monetary performance is

associated with the time spent on servicing the old customers.

4.10 Targetted Market Segments

Agents have different target customers according to

their capacity, confidence, character, willingness to work,

product knowledge and their awareness in their marketing field.

The occupation-wise market targeting of the respondents are

shown in table 4.16.

111

TABLE -4.16Occupation-wise Market Targeting of the Respondents

Number of Number ofS.No. Occupational Segments Agents Agents Total

Groups Targeting Not AgentsTargeting

1. Managerial or I 132 (66.0) 68(34) 200ExecutivesGroup

2. Regular Income II 151 (75.5) 49(24.5) 200Group

3 Self-Employed III 94 (47.0) 106(53) 200Group

4. Agriculture and IV 96 (48.0) 104(52) 200Allied LabourGroup

(Figures in paranthesis represented percentages)

It is understood from table 4.16 that 75.5 per cent

of the agents studied had concentrated on regular income group

(segment II), which was followed by the managerial or executive

group, that is, 66 per cent. Lastly the agriculture and allied

labour as well as the self-employed group were targeted by an

approximately equal number of agents and they were 48 per

cent and 47 per cent respectively.

Segment II is found to be the first in the

occupation-wise market targeting, since it being a middle

income group is large in number and prefers safety and security

on the investments rather than the return. Insurance policy is

112

a secured avenue of investment and thus customers are easily

convinced by the agents.

The study has coincided with the results of Mishra

(1991). He found that the LIC business had increased mainly

on account of insurance to salaried people 17 (regular income

group) Naganimai and Nair (1991) found that insurance

constituted an important financial asset option of the middle

income group. Next to gold, their most preferred investment

was on insurance policies 18 . The National CouncilE Applied

Economic Research (1979) ascertained that the LIC agents were

concentrating on salary earning households 19

Managerial or executive group (segment I) has been

the second most targeted group because the income-tax benefit

prompted them to opt for insurance, even though the return is

less. The agriculture and allied labour and the self-employed

groups are found to be the least targeted groups, since segment

III and IV are the most irregular as well as low income group

when compared to segment I and II and that might be the /

reason behind the low concentration or less targeting. The

findings are corroborated with the studies - Nagapandy (1994)

who found that high potential was tapped in managerial group

and low potential was tapped in the agricultural group in

113

Madurai Division 20 . The National Councilfb!i Applied Economic

Research (1979) found that agents were concentrating more on

affluent people than on the poor21

It is inferred that the regular income and the

managerial or executive groups are the first two categories most

targeted by the agents and the agriculture and allied labour and

self-employed groups are the least targeted groups.

4.11 Positioning of the LIC Policies

The process of positioning the LIC policies in the

minds of the customers or the buyers by stressing the special

features, utility and superior advantages over other investment

avenues is named positioning of the LIC policies. An efficient

market positioning breeds brand loyalty and brand preference.

In insurance, every policy is designed with a special positioning

effect along with the basic risk coverage, a universal advantage

and the unique feature of the LIC policies. Income-tax benefit,

pension provision, education and marriage need provision,

investment (periodical survival benefit) and housing loan

facilities are the major positioning features of the LIC policies.

The practice of policy positioning strategy of the respondents is

presented in table 4.17.

114

TABLE -4.17The Practice of Policy Positioning Strategy of the Respondents

Number of Number of TotalS.No. Marketing Strategies Agents Agents Not Agents

Practising Practising1. Risk Coverage 89 (94.5) 11(5.5) 200

2. Income Tax Benefits 182(91-0) 18(9) 200

3. Pension Provision 175 (87.5) 25 (12.5) 200

4. Education and 161 (80.5) 39 (19.5) 200Marriage NeedProvision

5. Investment 151 (75.5) 49 (24.5) 200

6. Housing Loan Purpose 138 (69.0) 62(31) 200

(Figures in parenthesis indicale perceniages

Risk coverage, the unique feature of insurance and

universal advantage of the insurance is found to be used as the

first and the foremost positioning strategy of the sample agents.

The results of the study coincide with the studies by the

National Council ffi Applied Economic Research

(1979)22, Singh et.al (1988)2 3 , and the Indian Institute of Public

Opinion (1992) 24 . According to these studies that majority of

the respondents had bought the LIC policies because of their

risk coverage benefit.

Moreover, the income-tax benefit is the second

popular positioning strategy practised by the agents, since both

the high and the tax paying middle income groups are opting for

115

insurance mainly for income-tax benefits. This result is in

corroboration with the results of the National Council for

Applied Economic Research (1979)25, Singh et al (1988)26 and

the Institute of Public Opinion (1992)27 where the second major

reason cited for buying the LIC policies was the tax benefits.

Pension provision is found to be the third major

positioning strategy of the sample agents. The employees in the

private sector undertakings are mostly non-pensioners and the

longevity of the retired life due to the advanced medical facilities

paved the way for the agents to practise this strategy. The

education or marriage need provision is found to be in the

fourth place in the order of the positioning strategies. The

combined effect of the cost of higher education and the marriage

expenditure due to the ever-increasing , cost of living has given a

lead to the agents. A significant majority of the agents have

proclaimed the investment motive as the policy positioning

strategy. Even though insurance is not a pure investment

proposal, the risk coverage and the periodical survival benefits

once in 4 or 5 years during the policy period made the prospects

favour the LIC policy. The housing loan is observed to be the

last feature among all the positioning strategies of the sample

agents, since it is specialized and cumbersome.

116

4.12 Conclusion

The analysis revealed that the Endowment and

Money Back type policies in general and the conventional

Endowment and conventional Money Back policies in particular

are the most popular policies among the sample agents. The

knowledge about the policies has affected significantly the

performance of the agents in both the monetary and the

coverage performance. The time spent towards the new

prospects has significant impact on the coverage performance.

But the time spent for servicing the old customers has

associated significantly with both the coverage and the

monetary performance. In the positioning of the LIC policies,

most of the agents have used the risk coverage and the income-

tax benefits. Further, it is found that much concentration is

given to the regular income (segment II) and managerial groups

(segment I) when compared to the agriculture and allied labour

(segment IV) as well as self-employed groups (segment III). This

marketing practice of the agents is determined by the external,

the socio-economic factors and the internal, the attitude and the

personality traits. These factors are analysed at a micro level in

the forthcoming chapters.

117

Foot Notes

1. Jim Connolly, "Agency Profitability - Its there if you know

where to look", Watson Wyatt Asia Pacific Insurance

Review, July 2001, PP.1 & 2.

2. P.S.Grewal; Numerical Methods of Statistical

Analysis, Sterling Publishers Pvt. Ltd, 1987, P.290.

3. LIC of India, Marketing (Research & Training)

Training material for Agents Licensing Course under

IRDA Rules, (Part one), Central Office, Mumbai, 2000,

pp.2 10-230.

4. Manual for agents, 1995, P.241.

5. National Insurance Academy, "Opinion of Life Insurance

Agents (Survey)", DNYANAJYOTI, Vol.2, June 1985, P.47.

6. R.M.Nagammai and S.Latha Nair, "Insurance pattern of

middle income group", Varthaga Department of

Commerce, Lady Doak College, Madurai, 1991, pp. 1-5.

7. R.J.Joshi, "Life Insurance in India - A Rambling

Analysis", D.NYANAJYOTI, Vol.8, December 1991, P.711.

8. Nagapandy, "Performance Evaluation of Life Insurance

Corporation - Madurai Division", unpublished M.Phil.

thesis submitted to Department of Commerce, N.M.S.S.

Vellaichamy Nadar College, Madurai, 1994.

118

9. F.R.Heredia, "Insurance is just waking up", The

Insurance Times, Vol. 17, Jan 1997, P.24.

10. LIC of India, "Spreading the Light", Yogakshema; Vol.44

No.5, May 2000, P.24.

11. R.J.Joshi (1991), op.cit, P.5.

12. S.C.Sahoo, "Life Insurance in India Vision 2000 - the

strategic perspectives", The Insurance Times, Vol.18,

Feb 1998, P.13.

13. R.J.Joshi, op.cit, P.25.

14. M.N.Mishra, LIC of India - A study of working and

performance, RBSA Publishers, Jaipur, 1991, PP.140 -

141.

15. Green Sham Allan, "The effect of prospect general

methods goal setting and call reluctance on real estate

sales performance", The Humanities and Social

Science International Dissertation Abstracts, Vol.59,

No.5, 1998.

16. Sabine Sonnentag, and Barbara M. Kleine, "Deliberate

Practice at Work - A study with Insurance Agents",

Journal of Occupational and Organizational

Psychology, 73, 2000, P.97.

17. M.N.Mishra, op.cit, P.168.

119.

18. R.M.Nagammai, and S.Latha Nair, op.cit, P.2.

19. National Council for Applied Economic Research,

Attitude towards Life Insurance Cover, NCAER

Publication, New Delhi, 1979, P.72.

20. Nagapandy (1994), op.cit.

21. National Council for Applied Economic Research, op.cit,

P.7 1.

22. Ibid, P.76.

23. Raghbir Singh, Radha * Sharn Arora, and Sanjine Mehra,

"What the professionals think about Life Insurance

Corporation policies", The Insurance Times, Vol.18,

September 1988, P.12.

24. Indian Institute of Public Opinon (1992) cited by Satpal

Singh, "Mobilisation of Household savings by LIC, The

Insurance Times, Vol. 15, Dec 1995, P.13.

25. National Council for Applied Economic Research (1979),

op.clt, 76.

26. Raghbir Singh, Radha Sharn Arora, and Satpal Mehra,

(1998), op.clt, 12.

27. Institute of Public Opinion (1992), op.clt, P.13.

120