CHAPTER - V ANALYSIS FOR FINDING PSYCHOGRAPHIC...

100

CHAPTER - V

ANALYSIS FOR FINDING PSYCHOGRAPHIC

SEGMENTATION

5.1 DEMOGRAPHIC PROFILE OF THE RESPONDENTS

In this chapter an attempt was made to identify the psychographic profile of

the organised food and grocery customers in Coimbatore city. For this purpose, a

field survey method was employed to collect firsthand information from 750

sample respondents. The respondents were chosen from various retail outlets in

different parts of the Coimbatore city. The data thus collected were arranged into

simple tabular form.

In this section percentage analysis was employed to determine the

demographic profile of the respondents and the details are furnished as follows.

5.1.1 AGE

On the subject of preference and satisfaction regarding food and grocery

stores, age of the respondents is very necessary to examine their level of

satisfaction. For this purpose, the age of the respondents has been classified into

four categories viz., upto 20 yrs, 21-30 yrs, 31-40 yrs and above 40 yrs. The

details are given in the following table.

Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.

101

TABLE NO: 5.1

AGE OF THE RESPONDENTS

S.No. Age No. of respondents Percentage

1. Upto 20 yrs. 114 15.2

2. 21-30 yrs. 364 48.5

3. 31-40 yrs. 174 23.2

4. Above 40 yrs. 98 13.1

Total 750 100.0

It could be inferred from the above table that 15.2 percent of the

respondents belong to the age group of upto 20 years, 48.5 percent of the

respondents belong to the age group between 21 and 30 years, 23.2 percent of the

respondents belong to the age group between 31 and 40 years and 13.1 percent of

the respondents belong to the age group of above 40 years.

5.1.2 GENDER

Gender is a prominent factor to identify the preference towards food and

grocery stores. For this purpose, the gender of the respondents has been classified

into two categories viz., male and female. The details are given in the following

table.

TABLE NO: 5.2

GENDER OF THE RESPONDENTS

S. No. Gender No. of respondents Percentage

1. Female 313 41.7

2. Male 437 58.3

Total 750 100.0


102


respondents belong to female category and 58.3 percent of the respondents belong

to male category.

Figure No. 5.1

Gender of the Respondents

5.1.3 EDUCATIONAL QUALIFICATION

According to the respondents‘ educational qualification, their preference

level towards food and grocery stores may vary. For this purpose, the educational

qualification of the respondents has been classified into three categories viz., upto

HSC, UG and PG. The details are furnished in the following table.


103

TABLE NO: 5.3

EDUCATIONAL QUALIFICATION OF THE RESPONDENTS

S.

No. Educational qualification No. of respondents Percentage

1. Upto HSC 145 19.3

2. UG 350 46.7

3. PG 255 34.0

Total 750 100.0

It could be obtained from the above table that 19.3 percent of the

respondents are qualified upto HSC, 46.7 percent of the respondents are qualified

UG degree and 34.0 percent of the respondents are qualified PG degree

Figure No : 5.2

Educational Qualification of the Respondents


104

5.1.4 OCCUPATION

According to the occupation of the respondents, their satisfaction level of

food and grocery stores may vary. For this purpose, the occupation of the

respondents has been classified into five categories viz., Salaried, Self-employed,

Professional, Home maker and others like Students, Retired etc. The details are

furnished in the following table.

TABLE NO: 5.4

OCCUPATION OF THE RESPONDENTS

S.

No. Occupation No. of respondents Percentage

1. Employed 200 26.7

2. Self-employed 167 22.3

3. Professional 106 14.1

4. Home maker 143 19.1

5. Others (Students, Retired, etc.) 134 17.9

Total 750 100.0

It is found table that 26.7 percent of the respondents are employed, 22.3

percent of the respondents are self-employed, 14.1 percent of the respondents are

professionals, 19.1 percent of the respondents are home makers and 17.9 percent

of the respondents are students, retired persons, etc.


105

Figure No : 5.3

Occupation of the Respondents

5.1.5 INCOME (PER MONTH)

The respondent‘s satisfaction level of food and grocery stores would be

different according to their monthly income. For this purpose, the monthly income

of the respondents has been classified into four categories viz., upto Rs.10000,

Rs.10001-20000, Rs.20001-30000 and above Rs.30000. The details are furnished

in the following table.

TABLE NO: 5.5

INCOME (PER MONTH) OF THE RESPONDENTS

S.No. Income per month No. of respondents Percentage

1. Upto Rs.10000 150 20.0

2. Rs.10001-20000 300 40.0

3. Rs.20001-30000 163 21.7

4. Above Rs.30000 137 18.3

Total 750 100.0


106


respondents are earning upto Rs.10000 as their monthly income, 40.0 percent of

the respondents are earning Rs.10001-20000 , 21.7 percent of the respondents are

earning Rs.20001-30000and 18.3 percent of the respondents are earning above

Rs.30000.

Figure No : 5.4

Monthly Income of the Respondents

5.1.6 RESIDENTIAL STATUS

The residential status of the respondents is an important factor that may

influence their satisfaction level of food and grocery stores. For this purpose, the

residential status of the respondents has been classified into two categories viz.,

own house and rental house. The details are furnished in the following table.


107

TABLE NO: 5.6

RESIDENTIAL STATUS

S.No. Living in No. of respondents Percentage

1. Own house 562 74.9

2. Rental house 188 25.1

Total 750 100.0

It could be indicated from the above table that 74.9 percent of the

respondents are living in their own house and 25.1 percent of the respondents are

living in rental houses.

5.1.7 MARITAL STATUS

The marital status of the respondents is very essential to examine their

satisfaction level of food and grocery stores. For this purpose, the marital status of

the respondents has been classified into three categories viz., Unmarried, married,

and others (widowed and divorced). The details are furnished in the following

table.

TABLE NO: 5.7

MARITAL STATUS OF THE RESPONDENTS

S.

No. Marital status No. of respondents Percentage

1. Unmarried 342 45.6

2. Married 373 49.7

3. Others 35 4.7

Total 750 100.0


108


respondents are unmarried, 49.7 percent of the respondents are married and 4.7

percent of the respondents are categorised as others (widowed and divorced).

5.1.8 TYPE OF FAMILY

The respondents‘ preference towards food and grocery is varied according

to their family. For this purpose, the type of family of the respondents has been

classified into two categories viz., Nuclear family and Joint family. The details

are furnished in the following table.

TABLE NO: 5.8

TYPE OF FAMILY OF THE RESPONDENTS

S.No. Type of family No. of respondents Percentage

1. Nuclear family 554 73.9

2. Joint family 196 26.1

Total 750 100.0

It could be observed from the above table that 73.9 percent of the

respondents belong to nuclear family and 26.1 percent of the respondents belong

to joint family.

5.1.9 NUMBER OF MEMBERS IN THE FAMILY

According to the number of members in the family, the satisfaction towards

food and grocery stores may vary. For this purpose, the number of members in the

family of the respondents has been classified into three categories viz., Upto 3

members, 4-5 members and above 5 members. The details are furnished in the

following table.


109

TABLE NO: 5.9

NUMBER OF MEMBERS IN THE FAMILY

S.

No. No. of members No. of respondents Percentage

1. Upto 3 members 172 22.9

2. 4-5 members 448 59.7

3. Above 5 members 130 17.3

Total 750 100.0


respondents have upto 3 members in their family, 59.7 percent of the respondents

have 4-5 members in their family and 17.3 percent of the respondents have above

5 members in their family.

5.1.10 NUMBER OF EARNING MEMBERS

In every family, the member‘s earning helps a lot and support the family in

a better way. The number of earning members in the family of the respondents has

been classified into three categories viz., 1 member, 2 members and more than 2

members. The details are furnished in the following table.

TABLE NO: 5.10

NUMBER OF EARNING MEMBERS

S.

No. No. of earning members No. of respondents Percentage

1. 1 Member 249 33.2

2. 2 Members 366 48.8

3. More than 2 members 135 18.0

Total 750 100.0


110

It could be stated from the above table that 33.2 percent of the respondents

have one earning member in the family, 48.8 percent of the respondents have two

earning members in the family and 18.0 percent of the respondents have more than

two earning members in the family

5.2 STORE CHOICE PROFILE

5.2.1 NUMBER OF STORES VISIT TO BUY THE GROCERY ITEMS IN

A MONTH

The respondents are visiting more stores to purchase their grocery items.

For this purpose, the number of stores visited to buy the grocery items has been

classified into three categories viz., 2 stores, 3-4 stores and above 4 stores. The

details are furnished in the following table.

TABLE NO: 5.11

NUMBER OF STORES VISIT TO BUY THE GROCERY

ITEMS IN A MONTH

S.

No. No. of stores No. of respondents Percentage

1. Upto 2 stores 339 45.2

2. 3-4 stores 296 39.5

3. Above 4 stores 115 15.3

Total 750 100.0

It could be indicated from the above table that 45.2 percent of the

respondents visited upto 2 stores to buy the grocery items in a month, 39.5 percent

of the respondents visited 3-4 stores to buy the grocery items in a month and

15.3 percent of the respondents visited above 4 stores to buy the grocery items in a

month.


111

5.2.2 FREQUENCY OF SHOPPING IN A MONTH

Every month, the customer purchase grocery items in their favourable

stores. The frequency of shopping by the customers in a month to buy the grocery

items has been classified into three categories viz., 2 times, 3-4 times and above 4

times. The details are furnished in the following table.

TABLE NO: 5.12

FREQUENCY OF SHOPPING IN A MONTH

S.

No. Frequency of shopping No. of respondents Percentage

1. Upto 2 times 392 52.3

2. 3-4 times 218 29.1

3. Above 4 times 140 18.7

Total 750 100.0


respondents are purchasing the grocery items upto two times in a month, 29.1

percent of the respondents are purchasing the grocery items 3-4 times in a month

and18.7 percent of the respondents are purchasing the grocery items above 4 times

in a month.

5.2.3 RANGE OF PURCHASING

Everybody has the variance in range of purchasing. For this purpose, the

purchasing range of the grocery items has been classified into three categories viz.,

Upto Rs.1000, Rs.1001-2000 and above Rs.2000. The details are furnished in the

following table.


112

TABLE NO: 5.13

RANGE OF PURCHASING

S.No. Purchase range No. of respondents Percentage

1. Upto Rs.1000 223 29.7

2. Rs.1001-2000 202 26.9

3. Above Rs.2000 325 43.3

Total 750 100.0


respondents are purchasing the grocery items for upto Rs.1000, 26.9 percent of

the respondents are purchasing the grocery items for Rs.1001-2000 and 43.3

percent of the respondents are purchasing the grocery items for above Rs.2000.

5.2.4 FAVOURITE SHOPPING DAYS

Everyone has their own favourite days for shopping the grocery items from

the shop. For this purpose, the favourite shopping days of purchasing the grocery

items has been classified into three categories viz., Week days (Mon-Friday),

Weekend (Sat & Sunday) and any day based on convenience. The details are


TABLE NO: 5.14

FAVOURITE SHOPPING DAYS

S.

No. Days

No. of

respondents Percentage

1. Week days (Mon-Friday) 55 7.3

2. Weekend (Sat & Sunday) 443 59.1

3. Any day based on convenience 252 33.6

Total 750 100.0


113


respondents are purchasing the grocery items in weekdays (Mon-Friday),

59.1percent of the respondents are purchasing the grocery items in the Weekend

(Saturday & Sunday) and 33.6 percent of the respondents are purchasing the

grocery items on any day based on their convenience. It is found from the analysis

that majority (59.1%) of the respondents are purchasing the grocery items in the

Weekend (Saturday & Sunday).

5.2.5 PREFERRED SHOPPING HOURS

The preferred timing for shopping their needed food and grocery items

from the shop is noted. For this purpose, the preferred shopping hours of

purchasing the grocery items has been classified into four categories viz., Morning

time, Afternoon time, Evening time and any time/ based on convenience. The

details are furnished in the following table.

TABLE NO: 5.15

PREFERRED SHOPPING HOURS

S.

No. Shopping hours No. of respondents Percentage

1. Morning 46 6.1

2. After noon 85 11.3

3. Evening 454 60.5

4. Any time / based on

convenience

165 22.0

Total 750 100.0

It could be observed from the above table that 6.1percent of the respondents

preferred morning time for purchasing the grocery items, 11.3percent of the

respondents preferred afternoon time for purchasing the grocery items, 60.5

percent of the respondents preferred evening time for purchasing the grocery items


114

and 22.0 percent of the respondents preferred any time / based on convenience for

purchasing the grocery items. It is found from the analysis that majority (60.5%)

of the respondents preferred evening time for purchasing the grocery items.

5.2.6 PREFERRED COMPANION FOR SHOPPING

Shopping will be very enjoyable in the company of one or two persons at

the time of purchasing. For this purpose, the preferred person for shopping has

been classified into four categories viz., alone, family members, friends,

neighbours and colleagues. The details are furnished in the following table.

TABLE NO: 5.16

PREFERRED COMPANION

S.

No. Preferred Companion No. of respondents Percentage

1. Alone 139 18.5

2. Family members 364 48.5

3. Friends 192 25.6

4. Neighbours 32 4.3

5. Colleagues 23 3.1

Total 750 100.0

It could be determined from the above table that 18.5 percent of the

respondents preferred to go alone for purchasing the grocery items, 48.5 percent of

the respondents preferred their family members, 25.6 percent of the respondents

preferred their friends, 4.3 percent of the respondents preferred their neighbours

and 3.1 percent of the respondents preferred their colleagues.


115

5.2.7 KNOWLEDGE ABOUT THE STORE

The customer knows about a store through some friends, advertisement,

relatives etc. For this purpose, the source of introduction about the store has been

classified into six categories viz., advertisements, promotion, friends, self interest,

relatives and others (co-workers, shop owners, etc.). The details are furnished in

the following table.

TABLE NO: 5.17

KNOWLEDGE ABOUT THE STORE

S.

No. Sources No. of respondents Percentage

1. Advertisements 298 39.7

2. Promotion 94 12.5

3. Friends 199 26.5

4. Self Interest 63 8.4

5. Relatives 73 9.7

6. Others (Co-workers, Shop

Owners, etc.) 23 3.1

Total 750 100.0


respondents are aware about the store through advertisements,12.5 percent of the

respondents are aware about the store through promotion, 26.5 percent of the

respondents are aware about the store from their friends, 8.4 percent of the

respondents are aware about the store through their self interest, 9.7 percent of the

respondents are aware about the store through their relatives and 3.1 percent of the

respondents are aware about the store through others like co-workers, shop

owners, etc. for purchasing the grocery items.


116

5.2.8 DISTANCE BETWEEN THE HOUSE AND THIS SHOP

The travelling distance between the house and the shop is noted. For this

purpose, the distance between the house and the shop has been classified into three

categories viz., upto 5 Km, 6-10 Km and above 10 Km. The details are furnished


TABLE NO: 5.18

DISTANCE BETWEEN THE HOUSE AND THIS SHOP

S.

No. Distance No. of respondents Percentage

1. Upto 5 Km. 452 60.3

2. 6-10 Km. 170 22.7

3. Above 10 Km. 128 17.1

Total 750 100.0

It could be noted from the above table that 60.3 percent of the respondents

travel upto 5 Km distance between the house and the shop, 22.7 percent of the

respondents travel 6-10 Km distance between the house and the shop and 17.1

percent of the respondents travel above 10 Km distance between the house and the

shop.

5.2.9 MODES OF TRANSPORT

People use different modes of transport to travel the distance. For this

purpose, the modes of transport used by the respondents are classified into four

categories viz., two wheeler, car, public transport and by walk. The details are



117

TABLE NO: 5.19

MODES OF TRANSPORT

S.

No. Mode No. of respondents Percentage

1. Two wheeler 346 46.1

2. Car 292 38.9

3. Public transport 68 9.1

4. By walk 44 5.9

Total 750 100.0


respondents are using two- wheeler, 38.9 percent of the respondents are using car,

9.1 percent of the respondents are using public transport for shopping and 5.9

percent of the respondents visit the shops by walk.

5.2.10 RESPONDENTS REACTION TOWARDS STOCK-OUT

SITUATION

The customers normally are purchase the other brands if the brand they opt

for is not available. To ascertain this the behaviour of respondents has been

classified into three categories viz., ‗wait and buy it later in the same shop‘, ‗buy

the product available in a different brand‘ and ‗buy it from the different outlet

immediately‘. The details are furnished in the following table.


118

TABLE NO: 5.20

RESPONDENTS REACTION TOWARDS STOCK-OUT SITUATION

S.

No. Behaviour

No. of


1. Wait and buy it later in the same

shop 230 30.7

2. Buy the product available in a

different brand 287 38.3

3. Buy it from the different outlet

immediately 233 31.1

Total 750 100.0


respondents wait and buy the product later in the same shop, 38.3 percent of the

respondents buy the product available in a different brand and 31.1 percent of the

respondents buy the brand from the different outlet immediately.

5.2.11 RESPONDENTS WILLINGNESS TO PAY EXTRA TO BUY

BRANDED PRODUCT

The customers will not hesitate to pay extra money to get their preferred

brand. The behaviour of the respondents when the brand is not available is

categorised viz., ‗willing extra money to pay‘ and ‗not willing to pay extra

money‘. The details are furnished in the following table.

TABLE NO: 5.21

RESPONDENTS WILLINGNESS TO PAY EXTRA TO BUY

BRANDED PRODUCT

S.

No. Opinion No. of respondents Percentage

1. Willing to pay 443 59.1

2. Not willing to pay 307 40.9

Total 750 100.0


119


respondents are willing to pay extra money to buy the branded product and 40.9

percent of the respondents are not willing to pay extra money to buy the branded

product.

5.2.12 SOURCES OF INFLUENCE ON PURCHASE DECISION

The customers normally take decisions on their own and some time they

consider others ideas at the time of purchasing. For this purpose, source of

influence on purchase decision has been classified into five categories viz., spouse,

parents, children, friends and others like neighbours, etc,. The details are furnished


TABLE NO: 5.22

SOURCES OF INFLUENCE ON PURCHASE DECISION

S.


1. Spouse 138 18.4

2. Parents 210 28.0

3. Children 114 15.2

4. Friends 262 34.9

5. Others (neighbours, etc,.) 26 3.5

Total 750 100.0


are influenced by the spouse, 28.0 percent of the respondents are influenced by the

parents, 15.2 percent of the respondents are influenced by the children, 34.9

percent of the respondents are influenced by the friends and 3.5 percent of the

respondents are influenced by others (neighbours, etc,.) at the time of purchase.


120

5.2.13 PERIOD OF ASSOCIATION WITH THIS STORE

The customers frequently visit their favourable grocery stores according to

their interest. For this purpose, the respondents are classified on the basis of their

association with the shop viz., First time, Less than 3 months, 3 months to 5

months, 6 months to 10 months and More than 10 months. The details are


TABLE NO: 5.23

PERIOD OF ASSOCIATION WITH THIS STORE

S.


1. First time 86 11.5

2. Less than 3 months 203 27.1

3. 3 months to 5 months 216 28.8

4. 6 months to 10 months 96 12.8

5. More than 10 months 149 19.9

Total 750 100.0


are visiting their favourable store for first time, 27.1 percent of the respondents are

visiting their favourable store for less than 3 months, 28.8 percent of the

respondents are visiting their favourable store for 3 months to 5 months, 12.8

percent of the respondents are visiting their favourable store for 6 months to 10

months and 19.9 percent of the respondents are visiting their favourable store for

more than 10 months


121

5.2.14 WILLINGNESS TO RECOMMEND THIS STORE TO OTHERS

Feedback about the stores is very important and it easily reaches other

people. For this purpose, the respondents were asked whether they would

recommend the stores to others. The details are furnished in the following table.

TABLE NO: 5.24

WILLINGNESS TO RECOMMEND THIS STORE TO OTHERS

S.

No. Opinion

No. of


1. Definitely will recommend 302 40.3

2. Probably will recommend 245 32.7

3. Not sure 157 20.9

4. Probably will not recommend 28 3.7

5. Definitely will not recommend 18 2.4

Total 750 100.0


respondents say that they will definitely recommend about the stores to others,

32.7 percent of the respondents say that they will probably recommend about the

stores to others, 20.9 percent of the respondents are not sure to recommend about

the stores to others, 3.7 percent of the respondents will not probably recommend

about the stores to others and 2.4 percent of the respondents will not definitely

recommend about the stores to others.

5.2.15 COMPARISON WITH OTHER STORES

Normally the customers compare their favourite store with other stores. The

comparison details are furnished in the following table.


122

TABLE NO: 5.25

COMPARISON WITH OTHER STORES

S.


1. Much better 332 44.3

2. Somewhat better 257 34.3

3. About the same 70 9.3

4. Somewhat worse 36 4.8

5. Much worse 28 3.7

6. Don‘t know 27 3.6

Total 750 100.0

It could be determined from the above table that 44.3 percent of the

respondents opined that their favourite store is much better than other stores, 34.3

percent of the respondents opined that their favourite store is somewhat better than

other stores, 9.3 percent of the respondents opined that the favourite store is the

same as the other stores, 4.8 percent of the respondents opined the purchasing

store is somewhat worse than other stores, 3.7 percent of the respondents opined

that their favourite store is much worse than other stores and 3.6 percent of the

respondents don‘t know about the other stores.

5.2.16 RESPONDENTS‟ WILLINGNESS TO BUY PRODUCTS AGAIN IN

THE SAME STORE

At the time of purchasing, if the customer who visit the store satisfied then

they think about visiting the store again. Below table gives detail about customer

opinion regarding visiting the store again.


123

TABLE NO: 5.26

RESPONDENTS‟ WILLINGNESS TO BUY PRODUCTS AGAIN IN THE

SAME STORE

S.


1. Definitely will 289 38.5

2. Probably will 261 34.8

3. Not sure 151 20.2

4. Probably will not 39 5.2

5. Definitely will not 10 1.3

Total 750 100.0


will definitely purchase the groceries in the same store, 34.8 percent of the

respondents will probably purchase the groceries in the same store, 20.1 percent of

the respondents are not sure to purchase the groceries in the same store, 5.2

percent of the respondents will not probably purchase the groceries in the same

store and 1.3 percent of the respondents will not definitely purchase the groceries

in the same store

5.3 FACTORS INFLUENCING STORE CHOICE OF THE

RESPONDENTS

Normally a typical customer chooses some factors as a basis to select the

retail outlet. For this purpose of the study, the 11 factors are selected like

Convenience of location & Time, Availability of store brand & Variety of

branded, products, Value for money, Parking facility, Services (Return policy,

Home Delivery, Bagging, etc.), Clean and serene ambience, Friendly staff, One

stop shopping, Loyalty card, Promotion and offer and Quality of Product and

ranked by the selected respondents which discussed in the following table.


124

TABLE NO: 5.27

FACTORS INFLUENCING STORE CHOICE OF THE RESPONDENTS

S.

No. Factors

Total

Score

Mean

Score Rank

1 Convenience of location & Time 48557 64.7 I

2 Availability of store brand & Variety of

branded products 46237 61.6 III

3 Value for money 47529 63.4 II

4 Parking facility 39413 52.6 V

5 Services (Return policy, Home Delivery,

Bagging, etc.) 40383 53.8 IV

6 Clean and serene ambience 36425 48.6 VI

7 Friendly staff 33532 44.7 VII

8 One stop shopping 33365 44.5 VIII

9 Loyalty card 29141 38.9 X

10 Promotion and offer 27298 36.4 XI

11 Quality of Product 30620 40.8 IX

Refer Appendix II for frequency.

It is observed from the table that the considerable number of the

respondents preferred the good and grocery store because of its ‗convenience

location and time‘ which ranked first by them with the Garrett score of ‗48557‘

points. It is followed by the second, third and fourth ranks were given to the

factors ‗value for money‘, ‗Availability of store brand & Variety of branded

products‘ and ‗Services (Return policy, Home Delivery, Bagging, etc.)‘ with the

Garrett score of 47529, 46237 and 40383 points. The fifth, sixth and seventh

ranks are ‗Parking facility‘, ‗Clean and serene ambience‘ and ‗Friendly staff‘ with

the Garrett score of 39413, 36425 and 33532 points. The eighth, ninth, tenth and

eleventh ranks occupied by the factors ‗One stop shopping‘, ‗Quality of product‘,

‗Loyalty card‘ and ‗Promotion and offer‘ with the Garrett score of 33365, 30620,

29141 and 27298 points.


125

5.4 IDENTIFYING PSYCHOGRAPHIC SEGMENTATION OF THE

CUSTOMERS

The researcher have adopted psychographic segmentation method outlined

by Vincent-Wayne Mitchell (1994) in his article and which is discussed by using

factor analysis, discriminant analysis and cluster analysis in the following.

All the selected 73 statements are categorised into 26 main category viz.,

Innovator, Fashion-conscious, Family orientation, Gender compatibility, Party

lover, Pro-politics, Leader, Narrow interests, Destiny believer, Intellectual,

Variety-seeker, Religious, Decision-dependent, Religious-ritual practiser,

Politically-disillusioned, Compulsive housekeeper, Child oriented, Homebody,

Community minded, Sports spectator, Cook, Self-designated opinion leader,

Information seeker, New brand tryer, Arts enthusiast and Dislikes housekeeping

were selected for factor analysis by using principle component extraction with

varimax rotation. The number of factors is unconstrained. For the sake of

convergent validity, 0.50 was used as a factor loading cut-off point.

The factor matrix is a matrix of loading and correlations between the

variable and factors. Pure variables have loading of 0.5 and greater or only one

factor. Complex variables may have high loading on more than one factor and

they make the interpretation of the output difficulty. The researcher rotated the

components 15 times to get the significant variables under 7 factors.

5.5 VALUES RELEVANT TO IDENTIFY PSYCHOGRAPHIC

SEGMENTATION

Table 5.28 shows the reliability statistics and proves the data could support

85.6 percentage reliable to do this analysis. Table 5.29 indicates that the Kaiser-

Meyer-Olkin (KMO) measures of sampling adequacy in the study is 0.87. This is


126

good result, as it exceeds 0.5 Bartlett‘s Test of Sphericity which is 0.000, meaning

that factors that form the variables are adequate.

TABLE NO: 5.28

RELIABILITY STATISTICS

Cronbach's

Alpha

N of

Items

0.856 26

TABLE NO: 5.29

KMO AND BARTLETT‟S TEST

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.87

Bartlett's Test of Sphericity Approx. Chi-Square 4162.77

DF 325

Sig. 0.00

5.5.1 Total Variance Explained

Table 5.30 depicts the total variance explained. Total variance is explained

with rotation, the Eigen values are different for factor 1,2,3,4,5, 6 and 7. The

Eigen values for factor 1, 2, 3, 4, 5, 6 and 7 are 5.87, 1.68, 1.35, 1.31, 1.16, 1.07

and 1.03. The percentage of variance for factor 1,2,3,4,5, 6 and 7 are 22.59, 6.48,

5.20, 5.04, 4.45, 4.13 and 3.95 respectively. It indicates that seven factors extract

from 26 factors have cumulative percentage upto 51.84% of the total variance.


127

TABLE NO: 5.30

TOTAL VARIANCE EXPLAINED

Compo-

nent

Initial Eigenvalues Extraction Sums of Squared

Loadings

Rotation Sums of Squared

Loadings

Total % of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 5.87 22.59 22.59 5.87 22.59 22.59 3.07 11.79 11.79

2 1.68 6.48 29.07 1.68 6.48 29.07 2.14 8.21 20.00

3 1.35 5.20 34.27 1.35 5.20 34.27 2.10 8.09 28.10

4 1.31 5.04 39.31 1.31 5.04 39.31 1.75 6.72 34.81

5 1.16 4.45 43.77 1.16 4.45 43.77 1.55 5.96 40.77

6 1.07 4.13 47.89 1.07 4.13 47.89 1.44 5.55 46.32

7 1.03 3.95 51.84 1.03 3.95 51.84 1.43 5.52 51.84

8 1.00 3.83 55.67

9 0.95 3.65 59.32

10 0.88 3.38 62.70

11 0.83 3.18 65.89

12 0.82 3.16 69.05

13 0.76 2.93 71.98

14 0.73 2.82 74.79

15 0.72 2.76 77.55

16 0.69 2.65 80.20

17 0.64 2.45 82.65

18 0.61 2.33 84.98

19 0.59 2.27 87.26

20 0.58 2.25 89.50

21 0.57 2.19 91.70

22 0.54 2.07 93.76

23 0.47 1.81 95.58

24 0.45 1.73 97.30

25 0.41 1.58 98.88

26 0.29 1.12 100.00

Extraction Method: Principal Component Analysis


128

5.5.2 Rotated Component Matrix

The rotated component matrix is discussed in the following table. After a

factor solution has been obtained, in which all variables have a significant loading

on a factor, the researchers attempted to assign some meaning to the pattern of

factor loadings. Variables with higher loadings are considered more important and

have greater influence on the name or label selected to represent a factor.

Researchers examined all the underlined variables for a particular factor and

placed greater emphasis on those variables with higher loadings to assign a name

or label to a factor that accurately reflected the variables loading on that factor.

The names or labels are not derived or assigned by the factor analysis computer

programme; rather, the label is intuitively developed by the factor analyst based on

its appropriateness for representing the underlying dimension of a particular

factor. All seven factors have given appropriate names on the basis of the variable

represented in each case.


129

TABLE NO: 5.31

ROTATED COMPONENT MATRIX

No. Factors

Component

Innovator Variety

Seeker Religious Homebody

Sports

Spectator

Opinion

Leader

Risk

Taker

1 Innovator 0.775

2 Fashion-conscious 0.759

3 Family orientation 0.543

4 Gender compatibility 0.531

5 Party lover 0.520

6 Destiny believer 0.694

7 Intellectual 0.667

8 Variety-seeker 0.572

9 Religious 0.625

10 Decision-dependent 0.624

11 Religious-ritual practiser 0.549

12 Child oriented 0.687

13 Homebody 0.551

14 Sports spectator 0.824

15 Cook 0.554

16 Self-designated opinion leader 0.782

17 Information seeker 0.609

18 New brand tryer 0.580

19 Arts enthusiast 0.578

Extraction Method : Principal Component Analysis. Rotation Method : Varimax with Kaiser Normalization.

Rotation converged in 15 iterations.


130

The above table shows the rotated component matrix, in which the

extracted factors are assigning a new naming related together.

a). Factor 1 is the most important factor which explained 11.79% of the

variation. The factors as Innovator (0.775), Fashion-conscious (0.759),

Family orientation (0.543), Gender compatibility (0.531) and Party lover

(0.520) are highly correlated with each other. The factors like Pro-politics,

Leader and Narrow interests are rejected from the analysis due to that of

values less than 0.5 cut-off point. These factors are focused upon the

innovative concept of the consumers. Hence it was labelled as „Innovator‟.

b). The second kind of factors explained 8.21% of the variances. In this

segment, the researchers took the three important variables such as Destiny

believer (0.694), Intellectual (0.667) and Variety-seeker (0.572) are having

highly correlated with each other. In this segment, customer seeks different

varieties of products in their retail shop. Hence, the name of the factor was

„Variety Seeker‟.

c). The third factors explained 8.09% of the variances. In this segment, the

researcher took the five variables such as Religious (0.625), Decision-

dependent (0.624), Religious-ritual practiser (0.549) are highly correlated

with each other. Among the five variables the two variables Politically-

disillusioned and Compulsive housekeeper are rejected from the analysis

due to that of less than the cut off point. Considering upon the three

variables, customers are having religious sense. Hence, it was decided to

use the name „Religious‟.


131

d). The fourth factors explained 6.72% of the variances. In this segment, the

researcher took the three variables such as Child oriented (0.687) and

Homebody (0.551) are highly correlated with each other. Among the three

variables, one variable community minded is rejected from the analysis for

the reason of less than the cut off point. For considering the two variables

the researcher named the segment of the respondents as „Homebody‟.

e). The fifth factors explained 5.96% of the variances. In this segment, the

researcher took the two variables such as Sports spectator (0.824) and Cook

(0.554) are highly correlated with each other. For viewing the two

variables, it was given as „Sports spectator‟.

f). The sixth factors explained 5.55% of the variances. In this segment, the

researcher took the two variables such as Self-designated opinion leader

(0.782) and Information seeker (0.609). For considering the two variables,

it was decided to coin the name „Opinion Leader‟.

g). The seventh factors explained 5.52% of the variances. In this segment, the

researcher took the three variables such as New brand tryer (0.580) and

Arts enthusiast (0.578). Among the three variables, dislikes housekeeping

is rejected due to less than the cut off point. For viewing the two variables,

it was labelled as „Risk taker‟.

5.6 DIFFERENCE OF OPINION OF THE RESPONDENTS ACROSS

VARIOUS SEGMENTS

Opinions of customers towards store performance according to their

experience were collected. In the study area 750 respondents were divided into

two groups, one showing favourable opinion of customers and the other showing

unfavourable opinion of customers. The difference of opinion of the respondents


132

in one group with the other was studied with the help of discriminant function

analysis. For the purpose of the study fifteen variables were selected.

1. Age

2. Gender

3. Educational Qualification

4. Occupation

5. Income per month

6. Marital Status

7. Type of Family

8. Family size

9. Preferred Shopping Outlet

10. Frequency of Shopping

11. Purchase Range

12. Favourite Shopping Days

13. Preferred Shopping Hours

14. Period of association

15. Like to recommend

The discriminant function analysis made an attempt to construct a function

with these and other variables, so that the respondents belonging to these two

groups are differentiated at the maximum. The linear combination of variables is

known as discriminant function and its parameters are called discriminant function

coefficients. In constructing this discriminant function, all the variables which

contribute more to differentiate these two groups were examined.

Mahalanobis minimum D2 method is based on the generalised squared

Euclidean distance that adjusts for unequal variances in the variables. The major

advantage of this procedure is that it is computed in the original space of the


133

predictor (independent) variables rather than as a collapsed version which is used

in the other method.

Generally, all the variables selected will not contribute to explain the

maximum discriminatory power of the function. So a selection rule is applied

based on certain criteria to include those variables which best discriminate.

Stepwise selection method was applied in constructing discriminant function

which selects one variable at a time to include in the function. Before entering into

the function, the variables are examined for inclusion in the function.

The variables which have maximum D2 value, if entered into the function is

selected for inclusion in the function. Once entered, any variable already in the

equation is again considered for removal based on certain removal criteria.

Likewise, at each step, the next best discriminating variable is selected and

included in the function and any variable already included in the function is

considered for removal, based on the selection and removal criteria respectively.

Since discriminant function analysis involved classification problem also,

to ascertain the efficiency of the discriminant function analysis all the variables

which satisfy the entry and removal criteria were entered into the function.

Normally, the criteria used to select the variables for inclusion in the function is

minimum ‗F‘, to enter into the equation (i.e) F statistic calculated for the qualified

variable to enter into the function is fixed as 1.

Similarly, any variable entered in the equation will be removed from the

function if ‗F‘ statistic for the variable calculated is <1. The two groups are

defined as

Group 1 - Favorable

Group 2 - Unfavourable


134

The mean and standard deviation for these groups and for the entire

samples are given for each variable considered in the analysis.

TABLE NO: 5.32

GROUP MEANS

(BETWEEN FAVOURABLE AND UNFAVOURABLE GROUPS)

S.

No. Factor

Favourable Unfavourable TOTAL

Mean SD Mean SD Mean SD

1 Age* 2.259 0.850 2.411 0.917 2.341 0.890

2 Gender 1.608 0.489 1.562 0.497 1.583 0.493

3 Educational Qualification 2.142 0.708 2.150 0.723 2.147 0.716

4 Occupation 2.808 1.484 2.778 1.456 2.792 1.468

5 Monthly Income 2.355 1.034 2.406 0.974 2.383 1.001

6 Marital Status 1.564 0.612 1.613 0.549 1.591 0.579

7 Type of family 1.259 0.439 1.264 0.441 1.261 0.440

8 Family Size 2.006 0.625 1.892 0.635 1.944 0.633

9 Preferred Shopping 2.015 0.842 1.988 0.797 2.000 0.817

10 Frequency of Shopping* 1.753 0.786 1.589 0.754 1.664 0.773

11 Purchase Range 2.134 0.857 2.138 0.835 2.136 0.844

12 Favourite Shopping

Days* 2.215 0.592 2.303 0.575 2.263 0.584

13 Preferred Shopping Hours 2.956 0.764 3.007 0.758 2.984 0.761

14 Period of Association 2.927 1.295 3.108 1.274 3.025 1.286

15 Recommendation* 2.108 1.048 1.823 0.915 1.953 0.988

The overall step wise D.F.A. results after all significant discriminators have

been included in the estimation of discriminated function is given in the following

table.


135

TABLE NO: 5.33

SUMMARY TABLE BETWEEN FAVOURABLE AND

UNFAVOURABLE GROUPS

Step Variable entered Wilk’s

lambda

Minimum

D2

Significance

1. Recommendation 0.979 0.085 1% Level

2. Frequency of Visiting the Shop 0.969 0.129 1% Level

3. Age 0.961 0.161 1% Level

4. Favourite Shopping Days 0.956 0.186 1% Level

* Significant at 1% level

The summary table indicated that the variable like to recommend entered in

step 1, frequency of visiting the shop entered in step 2, age entered in step 3 and

Favourite shopping days entered in the step 4. The variables Like to Recommend,

Frequency of Visiting the Shop, Age and Favourite Shopping Days are significant

at 1% level. All the variables are significant discriminator‘s based on their Wilk‘s

Lambda and D2 value. The multivariate aspect of the model is given in the

following table.

TABLE NO: 5.34

CANONICAL DISCRIMINANT FUNCTION


Canonical

correlation

Wilks

Lambda Chi-square D.F. Sig

0.211 0.956 33.850 4 Significant at

1% level

The canonical correlation is 0.211 when squared is 0.044 that is 4.4% of the

variance in the discriminant group can be accounted for by this model, Wilk‘s

Lambda and chi-square value suggested that D.F. is significant at 1% level.


136

The variables given above are identified finally by the D.F.A. as the

eligible discriminating variables. Based on the selected variables, the

corresponding D.F. coefficients are calculated. They are given in the following

table.

TABLE NO: 5.35

DISCRIMINANT FUNCTION COEFFICIENTS


Age (X1) -0.464

Frequency of Visiting the Shop (X2) 0.652

Favourite Shopping Days (X3) -0.636

Recommendation (X4) 0.695

Constant 0.081

Z = 0.081 – 0.464 (X1) + 0.652 (X2) – 0.636 (X3) + 0.695 (X4)

Using this D.F. coefficients and variables, discriminating scores for 2

groups are found out which are called group centroids or group means.

For favourable opinion (Z1) it is – 0.198

For unfavourable opinion (Z2) it is + 0.234

Discriminating factor is the weighted average of Z1 and Z2.

(344 × Z1) + (406 × Z2 )

(ie.) Z =

344 + 406


137

If it is represented diagrammatically it will be

Thus, to classify any respondents as to low or high level of store

performance respondents, the Z score for the respondents is found out by using the

equation. If the score found out for any respondents is Z0 and if the value is >Z

(i.e. Z0> Z ) then it is classified into high store performance and if Z0<Z then

(i.e. Z0< Z ) it is classified in the low store performance.

Now the questions remain to be answered are

1. How efficient are the discriminating variables in the D.F.A.?

2. How efficient the D.F. itself is?

The first question cannot be answered directly however, the discriminating

power or the contribution of each variable to the function can sufficiently answer

the question. For this, the following table is considered.

Z1 Z Z2

-0.198

0 +0.234

Favourable Unfavourable


138

TABLE NO: 5.36

RELATIVE DISCRIMINATING INDEX


Variables Group 1

Mean X1

Group 2

Mean X2

Unstandardised

dic. Coeff. (kj)

Ij = ABS

(Kj)

Mean

(Xjo – x ji)

Rj = Ij /

sum

Ij j*100

X1 2.259 2.411 -0.464 0.199 16.23

X2 1.753 1.589 0.652 0.390 31.88

X3 2.215 2.303 -0.636 0.282 23.00

X4 2.108 1.823 0.695 0.354 28.89

Total 1.225 100.00

5.6.1 Relative Discriminating Index

For each variable, the respective D.F. co-efficient, its mean for each group

and Rj are given. Rj called relative discriminating index is calculated from the

discriminant function coefficient and group means. Rj tells how much each

variable is contributing (%) to the function. By looking at this column it is found

that ‗Frequency of visiting the shop (X2)‘ is maximum discriminating variable and

‗Age (X1)‘ is the least discriminating variable.

The second question is answered by reclassifying the already grouped

individuals into low or high level store performer the D.F.(Z) defined in the

equation. This reclassification is called predictor group membership. In short, the

efficiency of the D.F. is how correctly it predicts the respondents into respective

groups.


139

TABLE NO: 5.37

CLASSIFICATION RESULTS


Actual group No. Of cases Predicted group membership

Group I Group II

Group I (Favourable) 344 177

(51.45%)

167

(48.55%)

Group 2 (Unfavourable) 406 144

(35.47%)

262

(64.53%)

Percent of grouped cases correctly classified : 58.5%.

The above table gives the results of the reclassification. The function,

using the variables selected in the analysis classified 58.5% of the cases correctly

in the respective groups.

Discriminate Function Analysis was applied to the respondents based on

the low and high store performance. The following factors significantly

discriminate the two groups. They are

1. Age ( at 1% level)

2. Frequency of Visiting the Shop (at 1% level)

3. Favourite Shopping Days (at 1% level)

4. Like to Recommend (at 1% level)

5.7 CLASSIFYING SEGMENTS

Cluster analysis is a multivariate statistical technique which groups

unknown number of persons / objects / occasions into groups such that the

members of each group are having similar characteristics/ attributes (Donald R.

Cooper, 2003). The primary objective of Cluster Analysis is to define the structure


140

of the data and identifying the most similar observations to place them into groups.

The different groups to be determined in Cluster Analysis is not pre-defined as in

Discriminate Analysis. This analysis is ideally suited to segmentation applications

in marketing research like consumer attitude, understanding buyer behaviour,

market segmentation, etc. The method of clustering may be either hierarchical or

non-hierarchical or both. The outcome of this analysis is much superior when the

results from the hierarchical order are used for the analysis along with the non-

hierarchical. Thus hierarchical and non-hierarchical techniques should be viewed

as complementary clustering techniques rather than as competing techniques

(Sharma, 1996). In this study the researcher have used both hierarchical and non

hierarchical clustering techniques.

Cluster analysis is typically applied to data recorded on interval scale or

continuous scaled variables. This analysis is applied to a large set of data which

may consist of many variables. Cluster analysis determines internal homogeneity.

i.e., similarities exist among the respondents or items and external heterogeneity

i.e. the differences exist across different groups of respondents or items. This

analysis helps in grouping the objects or persons based on the variables considered

in an analysis or research.

5.7.1 Procedures followed to classify segments

The interval scaled data (five point scaling: 5-strongly agree, 4-agree,

3-neither agree nor disagree, 2-disagree, 1-strongly disagree) collected from 750

respondents on various demographic characteristics were analysed in 6 stages.


141

Step : 1

The sample selected for cluster analysis included the people who the

respondents utilising the services are offered by food and grocery retail stores. The

researcher took the sample of 750 respondents with various demographic

characteristics in Coimbatore city.

Step -2

The most important part in the clustering problem is selecting the variables

on which the clustering is based. The researcher selected the different retail outlet

of Food and Grocery stores as the variables which included Innovator, Fashion-

conscious, Family orientation, Leader, Narrow interests, Religious-ritual practiser,

etc.

Step -3

The similarities among the cases / entities were computed either through

correlations, distance measures and other techniques. Among the various distances

measures Squared Euclidean distance measure was adopted to compute the

similarity between 2 cases in this study.

Step-4

In the clustering procedure hierarchical clustering method was adopted for

the I stage. In this method, agglomerative method was used with average linkage

between groups method. As the agglomeration schedule for 750 was very large,

the values from last 20 cases were given in the table and the remaining were listed

in the Appendix IV.


142

TABLE NO: 5.38

AGGLOMERATION SCHEDULE

Stage Cluster combined

Coefficients

Stage cluster first

appears Next

stage Cluster 1 Cluster 2 Cluster 1 Cluster 2

730 18 178 69570.884 700 681 740

731 16 17 70309.979 711 708 741

732 1 27 71050.972 721 727 741

733 37 146 71792.208 705 101 746

734 9 115 72591.500 714 429 739

735 32 49 73496.889 722 712 742

736 6 42 74409.884 726 729 737

737 5 6 75416.308 718 736 748

738 4 29 76527.204 719 706 742

739 2 9 77666.432 723 734 745

740 15 18 78809.030 728 730 744

741 1 16 80221.714 732 731 743

742 4 32 81827.172 738 735 744

743 1 3 83547.964 741 716 745

744 4 15 85587.977 742 740 746

745 1 2 87990.675 743 739 749

746 4 37 90530.731 744 733 747

747 4 35 94181.828 746 725 748

748 4 5 98672.079 747 737 749

749 1 4 118459.172 745 748 0

(The first part of the agglomeration schedule from cases 1 to 729 is given in the Appendix

IV)

Custer method: Average linkage between groups method (Hierarchical Clustering

Method)

Distance method: Squared Euclidean Distance measure


143

In the above agglomeration schedule, the figures from top to bottom (stage

1 to 749) indicates the sequence in which the cases get combined with other until

all 750 cases are combined together in one cluster at the last stage (stage 749). To

identify the number of clusters, the co-efficient values (i.e. difference between

rows) in column 4 is considered. The figures of co-efficient values were seen from

the last row upwards to have the lowest possible number of clusters for

interpretation. The difference in the value of co-efficients from stage 19 and stage

18 is 19787.093 (118459.172- 98672.07) indicating the 1st cluster. The procedure

is continued till the differences between the 2 stages gets reduced in order to

identify the number of clusters. In the next stage the difference between stage 18

and 17 is 4490.24 (98672.07 – 94181.82) which is low but again the difference

between 17 and 16 is 3651.097 (94181.82 – 90530.73) indicating the increasing

trend with more difference. But the difference between stages 16 and 15 is

2540.05 (90530.73 – 87990.67), stages 15 and 14 is 2402.69 (87990.67 –

85587.97) and in stages 14 and 13 is 2040.13 (85587.97 – 83547.96) showing a

little decrease. Hence, it is better to stop with the stage 15 and 14 with the

difference of 2402.69 indicating a 5 cluster solution with maximum differences in

the value of co-efficients. It was decided consequently to have 5 clusters from the

agglomeration schedule.

Step -5

After deciding the number of clusters as 5, the non-hierarchical

k-means (quick clustering) clustering method was used to find out the

psychographic variables in each cluster. The output initial cluster centers, final

cluster centers and Anova tables are interpreted to decide the variables in each

cluster.


144

TABLE NO: 5.39

INITIAL CLUSTER CENTRES

S.No. Variables Cluster

1 2 3 4 5

1 Innovator 18.0 16.0 4.0 10.0 18.0

2 Fashion-conscious 8.0 11.0 8.0 4.0 11.0

3 Family orientation 7.0 12.0 4.0 9.0 10.0

4 Gender compatibility 4.0 5.0 6.0 3.0 6.0

5 Party lover 4.0 6.0 3.0 7.0 7.0

6 Pro-politics 3.0 14.0 7.0 4.0 11.0

7 Leader 9.0 24.0 8.0 12.0 22.0

8 Narrow interests 11.0 9.0 9.0 10.0 7.0

9 Destiny believer 4.0 9.0 8.0 4.0 5.0

10 Intellectual 4.0 4.0 5.0 3.0 8.0

11 Variety-seeker 6.0 10.0 2.0 4.0 10.0

12 Religious 3.0 4.0 1.0 1.0 1.0

13 Decision-dependent 1.0 2.0 1.0 4.0 1.0

14 Religious-ritual practiser 9.0 11.0 3.0 9.0 8.0

15 Politically-disillusioned 3.0 4.0 1.0 3.0 5.0

16 Compulsive Housekeeper 16.0 16.0 4.0 15.0 9.0

17 Child Oriented 20.0 5.0 4.0 14.0 14.0

18 Home Body 8.0 4.0 2.0 2.0 6.0

19 Community Minded 12.0 20.0 5.0 7.0 8.0

20 Sports Spectator 15.0 20.0 8.0 13.0 4.0

21 Cook 18.0 17.0 4.0 9.0 11.0

22 Self-Designated Opinion Leader 15.0 11.0 7.0 3.0 8.0

23 Information Seeker 13.0 10.0 13.0 3.0 12.0

24 New Brand Tryer 6.0 2.0 8.0 4.0 9.0

25 Arts Enthusiast 9.0 6.0 3.0 3.0 15.0

26 Dislikes Housekeeping 12.0 9.0 4.0 12.0 14.0

The above table shows the initial cluster formations for 26 variables

selected with their mean scores.


150

TABLE NO: 5.43

ANOVA FOR PSYCHOGRAPHIC VARIABLES - CLUSTER

S.No Variables

Cluster Error

F Sig. Mean

square df

Mean

square df

1 Innovator 1047.84 4 6.80 745 154.05 1%

2 Fashion-conscious 200.45 4 5.43 745 36.94 1%

3 Family orientation 227.62 4 4.99 745 45.58 1%

4 Gender compatibility 55.12 4 2.88 745 19.14 1%

5 Party lover 63.36 4 2.62 745 24.15 1%

6 Pro-politics 206.29 4 4.70 745 43.89 1%

7 Leader 638.26 4 6.58 745 96.94 1%

8 Narrow interests 227.70 4 4.40 745 51.69 1%

9 Destiny believer 67.47 4 3.00 745 22.48 1%

10 Intellectual 66.10 4 3.04 745 21.74 1%

11 Variety-seeker 106.90 4 2.84 745 37.68 1%

12 Religious 8.07 4 1.44 745 5.59 1%

13 Decision-dependent 9.19 4 1.27 745 7.21 1%

14 Religious-ritual practiser 289.54 4 3.76 745 77.10 1%

15 Politically-disillusioned 59.26 4 1.23 745 48.10 1%

16 Compulsive Housekeeper 647.30 4 5.96 745 108.62 1%

17 Child Oriented 811.78 4 7.58 745 107.16 1%

18 Home Body 94.03 4 2.65 745 35.42 1%

19 Community Minded 644.39 4 5.92 745 108.89 1%

20 Sports Spectator 1156.93 4 6.54 745 176.88 1%

21 Cook 826.70 4 7.37 745 112.13 1%

22 Self-Designated Opinion Leader 155.15 4 4.53 745 34.24 1%

23 Information Seeker 129.04 4 4.84 745 26.65 1%

24 New Brand Tryer 60.86 4 3.15 745 19.31 1%

25 Arts Enthusiast 176.66 4 5.15 745 34.27 1%

26 Dislikes Housekeeping 340.66 4 5.65 745 60.27 1%


151

The Anova table helped in identifying which of the 26 variables were

significant across the 5 clusters. The last column in the table indicates that all the

variables are significant at the 1 percent level.

The validity and stability of the clusters were checked by splitting the

sample into two halves of 375 each and repeating the same procedure of cluster

analysis in 2 stages (hierarchical and non-hierarchical). The result shows the 5

cluster solution on both the samples.

5.7.2 Demographic profile of the respondents across segments

Respondents in each cluster were segregated based on their demographic

characteristics like Age, Gender, Educational status, Occupation, Monthly Income,

Marital Status, Type of family, Family size, preferred shopping market types,

frequency of market per month, purchasing range, favourite shopping days and

preferred shopping hours by using the table of cluster case listing of membership.

Respondents in cluster I, II, III, IV and V were identified based on their above

demographic characteristics as shown in the following table.


152

TABLE NO: 5.44

CLUSTER WISE DEMOGRAPHIC CHARACTERISTICS OF SAMPLE RESPONDENTS

Characteristics

Cluster /

Segment 1

(119)

Cluster /

Segment 2

(159)

Cluster /

Segment 3

(79)

Cluster /

Segment 4

(249)

Cluster /

Segment 5

(144) Total

No. of

Respondents

(Percent)

No. of

Respondents

(Percent)

No. of

Respondents

(Percent)

No. of

Respondents

(Percent)

No. of

Respondents

(Percent)

Age (Ye


155

Characteristics

Cluster /

Segment 1

(119)

Cluster /

Segment 2

(159)

Cluster /

Segment 3

(79)

Cluster /

Segment 4

(249)

Cluster /

Segment 5

(144) Total

No. of

Respondents

(Percent)

No. of

Respondents

(Percent)

No. of

Respondents

(Percent)

No. of

Respondents

(Percent)

No. of

Respondents

(Percent)

Purchase range

Upto Rs.1000 38 (17.0) 49 (22.0) 19 (8.5) 75 (33.6) 42 (18.8) 223

Rs.1001-2000 30 (14.9) 45 (22.3) 18 (8.9) 67 (33.2) 42 (20.8) 202

Above Rs.2000 51 (15.7) 65 (20.0) 42 (12.9) 107 (32.9) 60 (18.5) 325

Total 119 159 79 249 144 750

Favourite shopping days

Week days (Mon-Friday) 4 (7.3) 11 (20.0) 8 (14.5) 15 (27.3) 17 (30.9) 55

Weekend (Sat & Sunday) 83 (18.7) 89 (20.1) 45 (10.2) 142 (32.1) 84 (19.0) 443

Any day based on convenience 32 (12.7) 59 (23.4) 26 (10.3) 92 (36.5) 43 (17.1) 252

Total 119 159 79 249 144 750

Preferred shopping hours

Morning 4 (8.7) 14 (30.4) 3 (6.5) 16 (34.8) 9 (19.6) 46

After noon 14 (16.5) 18 (21.2) 10 (11.8) 24 (28.2) 19 (22.4) 85

Evening 78 (17.2) 93 (20.5) 52 (11.5) 139 (30.6) 92 (20.3) 454

Any time / based on

convenience 23 (13.9) 34 (20.6) 14 (8.5) 70 (42.4) 24 (14.5) 165

Total 119 159 79 249 144 750

Note : Figures in parenthesis is percentage


156

TABLE NO: 5.45

RELIABILITY TEST OF THE FIVE CLUSTERS

Cluster 1 0.8594

Cluster 2 0.8483

Cluster 3 0.8713

Cluster 4 0.8495

Cluster 5 0.8633

TABLE NO: 5.46

STORE LOYALTY OF THE FIVE SEGMENTS

Segment Cognitive Affective Conative Action

Value seeker 16.1 15.4 14.9 16.7

Leader 20.8 21.8 21.6 22.0

Go Grabber 11.0 9.9 9.5 9.6

Venturesome 33.1 32.9 34.4 33.9

Opinion former 19.1 19.9 19.6 17.9

Note : Figures in the cell is percentage

From the analysis, it is evident that the respondents were grouped in 5

heterogeneous groups / clusters. The I cluster segment was with 119 respondents

II cluster with 159 respondents, III cluster with 79 respondents, IV cluster with

249 respondents and V cluster with 144 respondents.

The corresponding variables were stratified into thirteen characters namely

Age, Gender, Educational status, Occupation, Monthly Income, Marital Status,

Type of family, Family size, preferred shopping market types, frequency of market

per month, purchasing range, favourite shopping days and preferred shopping

hours.


157

5.8 CHARACTERISTICS OF THE VARIOUS SEGMENTS

Segment 1 : Value seeker

While analysing the first segment it was found that the following

respondents are more in number. They are 21-30 years age group of the

respondents followed by male respondents, UG qualified respondents, self-

employed respondents, customers earns upto Rs.10000 per month, Unmarried,

nuclear family, having above 5 members in the family, the respondents who have

preferred hypermarket, spends upto Rs.1000 and the rspondents who are shopping

in weekend days.

It was found from the analysis that 119 respondents in cluster I who named

as value seeker opined that they are having the dominant values of Fashion-

conscious, Innovator and child oriented.

The considerable number (16.7%) of the first segment of the respondents

shows action loyalty followed by cognitive loyalty which is having a reliability of

0.8594.

Segment 2 : Leader

While analysing the second segment it was identified that the following

categories are dominating. They are 31-40 years age group of the respondents

followed by female respondents, UG qualified respondents, professionally

qualified respondents, earns above Rs.30000 as income, Unmarried, joint family,

having above 4 members in the family, the respondents who have preferred super

market, the respondents who spend Rs.1001 to Rs.2000 and the respondents who

prefers to shop in any day based on their convenience preferably morning hours.


158

It could be found from the analysis that 159 respondents in cluster II who

named as Leader opined that they are having the dominant values of Leader,

Sports spectator and Innovator.

The second segment (Leader), of the respondents shows action loyalty at

the highest (22.0%) level which is having a reliability of 0.8483.

Segment 3 : Go Grabber

The third segment consist the following respondents more in number. They

are, 21-30 years age group of the respondents followed by female respondents, PG

qualified respondents, others (students, retired, etc.), earns above Rs.30000 as

income, Unmarried, nuclear family, upto 3 members in the family, the respondents

who have preferred super market, the respondents who spends above Rs.2000 and

the respondents who are shopping in week days preferably in the afternoon hours.

It is noted from the analysis that 79 respondents in cluster III who named as

Go Grabber opined that they are having the dominant values of Child oriented,

family orientation and Dislikes housekeeping.

The maximum (11.0%) of the third segment (Go Grabber), respondents

show cognitive loyalty and having the reliability of 0.8713.

Segment 4 : Venturesome

The fourth segment consist and dominated by the respondents upto 20 years

of age followed by female, UG qualified, professionals, earns Rs.10001-Rs.20000

as income, Unmarried, nuclear family, consist of 4-5 members in the family, the

respondents who have preferred department stores, the respondents who spends

upto Rs.1000 and the respondents who are shopping in any days based on their

convenience are having high dominance.


159

It is found from the analysis that 249 respondents in cluster IV who named

as Venturesome opined that they are having the dominant values of Sports

spectator, Dislikes housekeeping, and Innovator.

The most customers (34.4%) belong to fourth segment ‗Venturesome‘,

show conative loyalty and having the reliability of 0.8495.

Segment 5 : Opinion former

The fifth segment found the following respondents are more in number,

they are having above 40 years of age followed by male respondents, upto HSC

qualified, home maker, the respondents who are earning Rs.20001 to Rs.30000 as

monthly income, others (widowed and divorced), belonging to joint family, having

upto 3 members in the family, the respondents who have preferred hypermarket,

the respondents who spends upto Rs.1001 to Rs.2000, those who are shopping in

week days and the respondents who shopping at after noon time.

It is revealed from the analysis that 144 respondents in cluster V who

named as ―Opinion Former‖ opined that they are having the dominant values of

Self-designated opinion leader, Family orientation and Innovator.

The maximum (19.9%) of the fifth segment i.e. Opinion former,

respondents show affective loyalty and having the reliability of 0.8633.


160

FIGURE NO: 5.5

DENDROGRAM USING WARD LINKAGE RESCALED DISTANCE

CLUSTER COMBINE


161

5.8.1 Avenues of Investment preferred by Various Segments

Segment wise classification of the different investment avenues is

discussed in the following table.

TABLE NO: 5.47

AVENUES OF INVESTMENT PREFERRED BY VARIOUS SEGMENTS

Cluster-1 : Value seeker

(Cronbach‟s Alpha=0.812,

23.5% variance)

Cluster-2 : Leader


16.5% variance)

Cluster-3 : Go Grabber


33.7% variance)

Jewellery (36.13) Fixed Deposit (59.12) Jewellery (67.09)

Fixed Deposit (34.55) Jewellery (55.35) Fixed Deposit (60.76)

Insurance (24.08) Insurance (48.43) Insurance (54.43)

Real Estate (23.04) Post Office Savings (27.04) Real Estate (29.11)

Stocks & Shares (16.23) Real Estate (27.04) Post Office Savings (25.32)

Post Office Savings (13.61) Mutual Fund (25.16) Mutual Fund (25.32)

Mutual Fund (11.52) Stocks & Shares (14.47) Stocks & Shares (21.52)

Public PF (6.28) Public PF (10.69) Infrastructure Bonds (10.13)

NSC (5.76) NSC (9.43) Public PF (8.86)

Infrastructure Bonds (3.14) Infrastructure Bonds (7.55) NSC (7.59)

KVP (1.57) KVP (2.52) KVP (3.80)

Cluster-4 : Venturesome


16.8% variance)

Cluster-5 : Opinion former


9.5% variance)

Jewellery (59.44) Jewellery (57.64)

Fixed Deposit (57.03) Fixed Deposit (51.39)

Insurance (47.79) Insurance (40.97)

Real Estate (28.92) Real Estate (34.72)

Post Office Savings (22.89) Post Office Savings (24.31)

Mutual Fund (22.89) Mutual Fund (18.75)

Stocks & Shares (18.47) Public PF (14.58)

NSC (8.43) Stocks & Shares (13.19)

Public PF (7.63) NSC (8.33)

Infrastructure Bonds (5.22) Infrastructure Bonds (6.25)

KVP (4.82) KVP (5.56)

Note : Figures in parenthesis is mean score


162

The cluster analysis has focussed upon the different investment avenues

that are discussed with the selected respondents. Most of the respondents are

interested to invest their money in Jewellery in all the segments except second

segment. In segment 2, the respondents are interested to invest money in fixed

deposits.

5.8.2 Media Habits Across Different Segments

Segment wise classification of the respondents based on the habit of media

is discussed in the following table.

TABLE NO: 5.48

MEDIA HABITS ACROSS DIFFERENT SEGMENTS



41.3% variance)

Cluster-2 : Leader


16.5% variance)



11.2% variance)

TV (43.98) TV (73.58) TV (73.42)

News paper (38.22) News paper (53.46) News paper (64.56)

Internet (31.94) Internet (35.85) Internet (56.96)

Magazines General (16.23) FM Radio (22.64) FM Radio (31.65)

FM Radio (15.18) Magazines General (13.21) Magazines General (29.11)

Magazines Business (9.42) Magazines Business (10.06) Magazines Business (11.39)

Periodicals (3.14) Periodicals (2.52) Periodicals (10.13)



17.5% variance)

Cluster-5 : Opinion former


13.5% variance)

TV (71.89) News paper (80.56)

News paper (52.61) Internet (31.25)

Internet (37.75) Periodicals (21.53)

FM Radio (18.88) Magazines Business (20.83)

Magazines General (14.86) FM Radio (18.88)

Magazines Business (13.25) Magazines General (7.64)

Periodicals (6.43) TV (6.25)



163

The media is more suitable and preferred by the various groups of

respondents are analysed through Cluster analysis. It is evident from the analysis

that all the segments except the fourth segment has preferred Television as a

suitable media to access information. And the fourth segment who preferred

newspaper as the suitable media.

5.8.3 Computer usage pattern across various segments

Segment wise classification of the different computer usage pattern of the

respondents is discussed in the following table.

TABLE NO: 5.49

COMPUTER USAGE PATTERN ACROSS VARIOUS SEGMENTS


(Cronbach‟s

Alpha=0.921, 31.6%

variance)

Cluster-2 : Leader

(Cronbach‟s

Alpha=0.932, 26.1%

variance)


(Cronbach‟s

Alpha=0.896, 11.5%

variance)

Daily (55.5) Daily (38.4) Daily (48.1)

Once in 2 days (26.1) Once in a Week (22.0) Once in 2 days (26.6)

Once in a Week (12.6) Once in 2 days (18.2) Once in a Week (13.9)

Do Not use (4.2) Once in a month (9.4) Do Not use (6.3)

Once in fortnight (0.8) Do Not use (8.8) Once in a month (5.1)

Once in a month (0.8) Once in fortnight (3.1)


(Cronbach‟s

Alpha=0.986, 23.2%

variance)

Cluster-5 : Opinion

former (Cronbach‟s

Alpha=0.875, 7.6%

variance)

Daily (48.2) Daily (43.1)

Once in 2 days (18.1) Once in a Week (20.8)

Once in a Week (15.3) Once in 2 days (18.1)

Do Not use (12.4) Once in a month (6.9)

Once in a month (3.6) Do Not use (6.9)

Once in fortnight (2.4) Once in fortnight (4.2)



164

While analysing the computer usage of the selected respondents, all the

segment respondents are using computer daily followed by once in two days and a

weekly once.

5.8.4 Internet usage pattern across various segments

Segment wise classification of the different internet usage pattern of the


TABLE NO: 5.50

INTERNET USAGE PATTERN ACROSS VARIOUS SEGMENTS


(Cronbach‟s

Alpha=0.942, 26.1%

variance)

Cluster-2 : Leader

(Cronbach‟s

Alpha=0.932, 23.5%

variance)


(Cronbach‟s

Alpha=0.975, 19.5%

variance)

Daily (41.2) Daily (30.2) Daily (36.7)

Once in a Week (25.2) Once in a Week (24.5) Once in a Week (27.8)

Once in 2 days (17.6) Once in 2 days (17.0) Once in 2 days (13.9)

Once in a month (6.7) Do Not use (13.2) Once in a month (10.1)

Once in fortnight (5.0) Once in a month (10.1) Do Not use (7.6)

Do Not use (4.2) Once in fortnight (5.0) Once in fortnight (3.8)


(Cronbach‟s

Alpha=0.941, 17.8%

variance)

Cluster-5 : Opinion


Alpha=0.991, 13.1%

variance)

Daily (39.0) Daily (31.3)

Once in 2 days (21.3) Once in a Week (29.9)

Once in a Week (17.3) Once in 2 days (17.4)

Do Not use (12.9) Once in fortnight (9.0)

Once in a month (5.2) Do Not use (8.3)

Once in fortnight (4.4) Once in a month (4.2)


From the above table it is observed that most of the respondents are using

internet daily basis followed by once in a week.


165

5.8.5 Activities undertaken by various segments

Segment wise classification of the different leisure time activities of the


TABLE NO: 5.51

ACTIVITIES UNDERTAKEN BY VARIOUS SEGMENTS



36.1% variance)

Cluster-2 : Leader

(Cronbach‟s

Alpha=0.979, 16.2%

variance)


(Cronbach‟s

Alpha=0.992, 14.5%

variance)

Listening to Music (89.1) Listening to Music (75.5) Listening to Music (81)

Going to Theatre (52.1) Going to Theatre (46.5) Going to Theatre (55.7)

Walking (51.3) Walking (45.3) Visiting Shopping Malls

(44.3)

Computer Games (43.7) Visiting Shopping Malls

(37.1) Walking (40.5)

Visiting Shopping Malls

(38.7) Computer Games (35.2) Computer Games (40.5)

Cooking Activity (32.8) Cooking Activity (30.2) Cooking Activity (39.2)

Going to Gym (29.4) Visiting Stores (27.7) Playing Chess (34.2)

Visiting Stores (28.6) Playing Cricket (27) Playing Cards (31.6)

Playing Cricket (27.7) Playing Chess (27) Playing Cricket (31.6)

Badminton (25.2) Eating Out (24.5) Swimming (29.1)

Swimming (24.4) Gardening (23.3) Going to Gym (29.1)

Playing Chess (22.7) Going to Gym (22) Visiting Stores (26.6)

Gardening (21) Playing Cards (20.1) Giving Dinner Parties

(26.6)

Practicing Yoga / Reiki (21) Giving Dinner Parties

(19.5) Gardening (25.3)

Playing Cards (20.2) Badminton (17.6) Eating Out (24.1)

Visiting Amusement Parks

(20.2) Swimming (17)

Practicing Yoga / Reiki

(24.1)

Giving Dinner Parties (20.2) Practicing Yoga / Reiki

(17) Badminton (20.3)

Playing Basketball (19.3) Trekking (15.7) Visiting Amusement Parks

(17.7)

Playing Football (17.6) Visiting Amusement Parks

(13.8) Playing Basketball (17.7)

Eating Out (16.8) Playing Football (9.4) Playing Football (13.9)

Trekking (12.6) Playing Basketball (7.5) Trekking (11.4)


166



21.6% variance)

Cluster-5 : Opinion


Alpha=0.955, 11.6%

variance)

Listening to Music (83.1) Listening to Music (78.5)

Going to Theatre (52.6) Walking (53.5)

Walking (48.2) Going to Theatre (49.3)

Computer Games (43.8)


(41.7)


(39.8) Gardening (38.2)

Gardening (32.1) Cooking Activity (36.1)

Visiting Stores (32.1) Computer Games (33.3)

Cooking Activity (31.7) Visiting Stores (31.3)

Eating Out (29.7) Playing Chess (29.9)

Playing Cards (29.7) Eating Out (28.5)

Playing Cricket (28.1) Playing Cricket (26.4)

Playing Chess (25.7) Playing Cards (24.3)

Swimming (22.5) Going to Gym (22.9)

Going to Gym (21.7) Swimming (19.4)

Giving Dinner Parties (19.7) Badminton (18.1)


(17.7)


(15.3)

Badminton (15.7)

Giving Dinner Parties

(15.3)


(14.1)


(13.9)

Playing Basketball (14.1) Trekking (9.7)

Trekking (13.7) Playing Basketball (9.7)

Playing Football (12) Playing Football (8.3) Note : Figures in parenthesis is mean score

Discussion made with their interested activities, all the segment

respondents are having the same leisure time activity like listening to music and

followed by going to theatre and walking.


167

5.8.6 Ownership of consumer durables across various segments

Customers who owned durable goods in their houses in different segment

are discussed in the following table.

TABLE NO: 5.52

OWNERSHIP OF CONSUMER DURABLES ACROSS VARIOUS

SEGMENTS


(Cronbach‟s

Alpha=0.942, 23.9%

variance)

Cluster-2 : Leader

(Cronbach‟s

Alpha=0.962, 19.9%

variance)


(Cronbach‟s

Alpha=0.997, 17.8%

variance)

Gas Stove (84.9) Color TV (81.8) Mobile Phone (88.6)

Color TV (82.4) Mobile Phone (76.7) Color TV (82.3)

Mobile Phone (73.1) 2 Wheeler (64.2) Telephones (74.7)

DVD (69.7) Fridge (63.5) 2 Wheeler (74.7)

Computer (68.1) Washing Machine (61.6) DVD (70.9)

Fridge (64.7) DVD (61) Fridge (68.4)

Telephones (58.8) Gas Stove (57.9) Gas Stove (67.1)

2 Wheeler (58) Computer (57.9) Computer (62)

Music System (56.3) Water Filter (56.6) Music System (53.2)

Washing Machine (56.3) 4 Wheeler (54.1) Washing Machine (50.6)

Water Filter (47.9) Telephones (52.8) 4 Wheeler (49.4)

Air Conditioner (43.7) Music System (50.9) Water Filter (46.8)

4 Wheeler (43.7) Air Conditioner (49.1) I-Pod (45.6)

I-Pod (42.9) Digi-Cam (37.7) Microwave (41.8)

Digi-Cam (38.7) Microwave (35.8) Digi-Cam (40.5)

Microwave (37.8) I-Pod (34.6) Air Conditioner (39.2)

Food Processor (26.1) Exercise Equipment (25.2) Exercise Equipment (25.3)

Exercise Equipment (23.5) Food Processor (23.3) Food Processor (22.8)


168


(Cronbach‟s

Alpha=0.978, 13.4%

variance)

Cluster-5 : Opinion


Alpha=0.932, 25.0%

variance)

Mobile Phone (88.6) Color TV (85.5)

Color TV (82.3) Mobile Phone (76.7)

Telephones (74.7) Computer (67.1)

2 Wheeler (74.7) DVD (65.9)

DVD (70.9) 2 Wheeler (63.9)

Fridge (68.4) Gas Stove (63.5)

Gas Stove (67.1) Telephones (63.5)

Computer (62) Fridge (62.7)

Music System (53.2) Music System (55.4)

Washing Machine (50.6) Washing Machine (55.4)

4 Wheeler (49.4) Water Filter (48.6)

Water Filter (46.8) Air Conditioner (43)

I-Pod (45.6) 4 Wheeler (40.2)

Microwave (41.8) I-Pod (39)

Digi-Cam (40.5) Microwave (36.5)

Air Conditioner (39.2) Digi-Cam (35.7)

Exercise Equipment (25.3) Food Processor (26.5)

Food Processor (22.8) Exercise Equipment (17.3)


In segment 1, customers are mostly having gas stove, in segment 2 and

segment 5, most of the customers are having color TV, in segment 3 and segment

4, most of the customers are having mobile phone.


169

5.8.7 Purpose to Visit

Purpose of visit is discussed through the following table.

TABLE NO: 5.53

PURPOSE TO VISIT


(Cronbach‟s

Alpha=0.876, 19.6%

variance)

Cluster-2 : Leader

(Cronbach‟s

Alpha=0.893, 23.5%

variance)


(Cronbach‟s

Alpha=0.912, 32.4%

variance)

Shopping (61.3) Shopping (65.4) Shopping (69.6)

Shopping / window shop

and hand out (25.2)


and hand out (23.9)

Window shopping / hang

out (15.2)


out (13.4)


out (10.7)


and hand out (15.2)


(Cronbach‟s

Alpha=0.896, 14.8%

variance)

Cluster-5 : Opinion


Alpha=0.932, 9.7%

variance)

Shopping (65.1) Shopping (51.4)


and hand out (22.5)


and hand out (30.6)


out (12.4)


out (18.1)


From the above table it is observed that most of the respondents in all the

segments are visiting food and grocery stores for the main reason for shopping

goods.


170

5.9 FACTORS INFLUENCING STORE CHOICE AMONG CUSTOMERS IN DIFFERENT SEGMENTS

The factors influencing the respondents to prefer the stores in different segments are discussed in the following table.

TABLE NO: 5.54

FACTORS INFLUENCING STORE CHOICE AMONG CUSTOMERS IN DIFFERENT SEGMENTS

S.

No. Factors

Value seeker Leader Go Grabber Venturesome Opinion Former

Mean

Score Rank

Mean

Score Rank

Mean

Score Rank

Mean

Score Rank

Mean

Score Rank

1 Convenience of location & Time 65.7 II 65.2 I 63.1 II 65.4 I 63.3 I

2 Availability of store brand &

Variety of branded products 65.5 III 60.2 III 59.2 III 61.5 III 61.8 II

3 Value for money 66.4 I 61.7 II 63.6 I 63.9 II 61.7 III

4 Parking facility 55.5 IV 54.7 IV 49.4 VI 49.6 V 54.6 IV

5 Services (Return policy, Home

Delivery, Bagging, etc.) 54.5 V 53.0 V 51.4 IV 54.5 IV 54.5 V

6 Clean and serene ambience 47.7 VI 46.6 VII 50.3 V 48.1 VI 51.2 VI

7 Friendly staff 43.0 VIII 49.1 VI 45.3 VIII 42.9 IX 44.0 VIII

8 One stop shopping 46.0 VII 43.0 VIII 42.3 IX 45.4 VII 44.4 VII

9 Loyalty card 40.4 IX 38.5 X 41.0 X 38.2 X 37.9 X

10 Promotion and offer 31.6 XI 36.4 XI 38.8 XI 37.5 XI 37.1 XI

11 Quality of Product 33.6 X 41.6 IX 45.5 VII 43.1 VIII 39.4 IX


171

It is noted from the above analysis that all the stores are preferred by the

respondents for the main reason of its ‗value for money‘ with the Garrett mean

score of 66.4 for ‗Value Seeker‘ and 63.6 for ‗Go Grabber‘, Convenience of

location & Time for ‗Leader‘ with mean score of 65.2, 65.4 for ‗Venturesome‘ and

63.3 for ‗Opinion Former‘. The second major reason is ‗Convenience of location

& Time‘ for Value Seeker and Go Grabber, Value for money for ‗Leader‘ &

‗Venturesome‘ and Availability of store brand & Variety of branded products

preferred by ‗Opinion Former‘.

5.10 RESULTS AND DISCUSSIONS

In this section, the details regarding demographic profile, store choice

profile of the respondents, factor relevant for psychographic profiles, difference of

opinion of the respondents across various segments and classifying the various

psychographic segments are given.

1. Demographic profiles

It was found that considerable number of the customers belongs to the age

group between 21 and 30 years, male, having UG qualification, salaried having

income from Rs.10001 to 20000, having own house, married, belonging to nuclear

family, having 4-5 members in their family, consists maximum of 2 members

earning in the family.

2. Store Choice Profile

The result reveals that most of the customers are not visiting only one store

to buy food and grocery items, having a purchase frequency of upto 2 times in a

month, purchase range falls above Rs.2000 every time they visit. It is found that

they are much fond on visiting retail outlets during weekends. They found to be

visiting retail outlets in evening hours. They always have preferred to shop with

their family members. Customers get to know about the retail outlet through


172

advertisement. Most of the respondents don‘t travel more than 5 kms to reach the

retail outlet. Two wheeler is the usual mobility to reach the store. Many customers

are opined that they buy the product available in a different brand in case of stock

out situation. The previous study (Mario Miranda and Jegasothy, 2008) has

demonstrated that customers do not switch store in case of stock out situation. It

implies that they might be loyal to store they prefers to shop. Many have agreed to

pay extra money to buy branded products. Surprisingly, it is found that the most of

the respondent‘s purchase decisions are influenced by friends. They had

association with the retail outlet with a period of less than 3 months and they

definitely would recommend their retail outlet to others. Customers felt that their

stores are much better than the other conventional retail outlet and they would be

interested to visit the store again.

3. Factors relevant for Psychographic profiles :

The study identified the variables that are relevant to form psychographic

segments for this research. They are: Innovator, Fashion-conscious, Family

orientation, Gender compatibility, Party lover, Destiny believer, Intellectual,

Variety-seeker, Religious, Decision-dependent, Religious-ritual practiser, Child

oriented, Homebody, Sports spectator, Cook, Self-designated opinion leader,

Information seeker, New brand tryer and Arts enthusiast. All the above 19

variables are grouped in to 7 category with the following labels viz., Innovator,

Variety Seeker, Religious, Homebody, Sports Spectator, Opinion Leader and Risk

Taker. It is found that the variable which forms psychographic segments relevant

to the local value system.

4. Findings differences of opinion of the respondents across various

segments

To segment the customers based on psychographic profile, it is mandatory

to know the difference of opinion among customers. It is found four variables


173

which stands outside to differentiate the various segments. They are age,

frequency of visiting the shop, favourite shopping days and willingness to

recommend the store to others. It is found that the above discriminated variables

are perfectly fits to differentiate the behaviour of the various segments.

5. Classifying the segments

Segment 1 : Value seeker (15.9%)

While analysing the first segment which carries male respondents, 21-30

years age group, UG qualified, self-employed, earns upto Rs.10000, Unmarried,

belongs to nuclear family, having above 5 members in their family, preferred

hypermarket, upto Rs.1000 spends for purchase who shops mostly in weekend

days at evening hours.

The respondent in this segment appears to be visiting the marketplace

seeking for new ideas and to keep up with trends and new fashions. Since, they do

not value social aspect of shopping, one might argue that they appear to fulfil the

family roles as part of their responsibilities and engage in fashion and style

consumption for the sake of others but rather for self fulfilment and self

enhancement.

In this first segment, encompasses good number of respondents are having

action loyalty (frequently of visit the store) followed by cognitive loyalty.

Segment 2 : Leader (21.2%)

While analysing the second segment which is dominated by female,

belongs to 31-40 years age group, UG qualified, having professional occupation,

earning above Rs.30000 income, unmarried, belongs to joint family, having above

4 members in their family, favours super market, spends Rs.1001 to Rs.2000 for


174

each time and the respondents who are shopping in any day based on their

convenience preferably in morning hours.

The study found that families who exhibit a greater degree of multistore

food shopping are likely to be those with larger food budgets and those who make

food shopping trips more frequently shopping in grocery stores per monthly than

others (Prasad Kanti, 1972). They enjoy making decisions on their own and

sometimes they like to try something new and different things in their life.

The second segment ie., Leader, the respondents are having the high level

of action loyalty.

Segment 3 : Go Grabber (10.5%)

Third segment dominated by female, 21-30 years age group, PG qualified,

unmarried and others (students, retired, etc), earns above Rs.30000 family income,

belongs to nuclear family, have upto 3 members in their family, preferred super

market, spend above Rs.2000 and they are shopping in week days preferably in

morning hours. It is surprised to find this segment prefers shop which can offered

value for money.

These customers appear to actively seek value and utility because they

carries family orientation value and child oriented value. It might be they wanted

to give quality products with best price to their family. Women feel reinforced by

their family‘s appreciation of their shopping (Ruby Roy Dholakia, 1999).

In this segment named as Go Grabber vested with more number of

respondents are having the cognitive loyalty.


175

Segment 4 : Venturesome (33.2%)

Fourth segment dominated by female, upto 20 years aged, professionally

occupied, UG qualified, earns Rs.10001 – Rs.20000 income in their family,

married, who belongs to nuclear family, having 4-5 members in their family,

preferred departmental stores, spends upto Rs.1000 for purchase and they are

interested to shop in any days/time based on their convenience because they seek

convenience in selecting retail outlet.

This segment interested in sports and seems to be very active but reluctant

in housekeeping. It might be the reason for selecting convenient for choosing

stores. This segment respondents are having the dominant values of Sports

spectator, Dislikes housekeeping, and Innovator. Further, considerable number of

respondents exhibits conative loyalty.

Segment 5 : Opinion former (19.2%)

While analysing the fifth segment, dominated by male, above 40 years

aged, who educated upto HSC, acting as a home maker, whose family income falls

between Rs.20001 and Rs.30000, others (widowed and divorced), belongs to joint

family, having upto 3 members in their family, preferred hypermarket and spends

upto Rs.1001 to 2000, who are interested to shop during week days preferably in

afternoon hours.

These are older men, homemaker and separated. They are unlikely to take

risks because they might believe that ―things are changing too fast these days‖

(Krafft, Susan, 1993). Their favourite place to shop is in hypermarket.

This segment respondents are having the dominant values of Self-

designated opinion leader, Family orientation and Innovator and having more

respondents showcase affective loyalty.


176

6. Avenues of Investment options preferred by various segments

Almost all segments except leader preferred to make investment in

jewellery and fixed deposits. This might be people more in fond to invest money

in jewellery especially in Coimbatore.

7. Media habits across various segments

Television was the most preferred media across all the segments except

opinion former. This is because television became one among the family member.

8. Computer Usage pattern across various segment

It was identified in the research that everybody using computers daily either

in their home or at their office. This depicts people becoming computer friendly.

9. Internet usage pattern across various segments

It was astounding to see almost all segments using internet connection. This

gives idea to introduce online grocery retailing to pull more number of customers.

10. Purpose of visiting the stores

It was amazing to note that the customer prefer to visit shops to purchase

something. This result propagate that browsing habits of the customers are limited.

11. Factors influencing store choice in various segments

The factor ‗Convenience of location & Time‘ was preferred by most of the

customers belongs to ‗Leader‘, ‗Venturesome‘ and ‗Opinion Former‘ and other

segments namely ‗Value Seeker‘ & ‗Go Grabber‘ were attracted by ‗Value for

money‘.


177

Second major factor influencing the customer to choose stores are:

segments ‗Leader‘ & ‗Venturesome‘, were influenced by ‗Value for money‘ and

‗Convenience of location & time‘ was preferred by ‗Value Seeker‘ & ‗Go

Grabber‘ and the factor ‗Availability of store brand & variety of branded products‘

was preferred by the customers who belongs to ‗Opinion Former‘. It might be

because of ‗Value Seeker‘ prefers hypermarket where they can get value for

money and ‗Go Grabber‘ motivated to go departmental store to get value for

money.

******


CHAPTER - V ANALYSIS FOR FINDING PSYCHOGRAPHIC...

Documents

Transcript of CHAPTER - V ANALYSIS FOR FINDING PSYCHOGRAPHIC...