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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.
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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
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It could be inferred from the above table that 41.7 percent of the
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.
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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
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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.
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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
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It could be inferred from the above table that 20.0 percent of the
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.
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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
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It could be inferred from the above table that 45.6 percent of the
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.
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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
It could be inferred from the above table that 22.9 percent of the
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
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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.
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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
It could be inferred from the above table that 52.3 percent of the
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.
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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
It could be inferred from the above table that 29.7 percent of the
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
furnished in the following table.
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
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It could be observed from the above table that 7.3 percent of the
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
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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.
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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
It could be inferred from the above table that 39.7 percent of the
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.
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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
in the following table.
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
furnished in the following table.
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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
It could be inferred from the above table that 46.1 percent of the
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.
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TABLE NO: 5.20
RESPONDENTS REACTION TOWARDS STOCK-OUT SITUATION
S.
No. Behaviour
No. of
respondents Percentage
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
It could be inferred from the above table that 30.7 percent of the
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
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It could be observed from the above table that 59.1 percent of the
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
in the following table.
TABLE NO: 5.22
SOURCES OF INFLUENCE ON PURCHASE DECISION
S.
No. Opinion No. of respondents Percentage
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
It could be stated from the above table that 18.4 percent of the respondents
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.
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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
furnished in the following table.
TABLE NO: 5.23
PERIOD OF ASSOCIATION WITH THIS STORE
S.
No. Opinion No. of respondents Percentage
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
It could be stated from the above table that 11.5 percent of the respondents
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
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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
respondents Percentage
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
It could be observed from the above table that 40.3 percent of the
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.
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TABLE NO: 5.25
COMPARISON WITH OTHER STORES
S.
No. Opinion No. of respondents Percentage
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.
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TABLE NO: 5.26
RESPONDENTS‟ WILLINGNESS TO BUY PRODUCTS AGAIN IN THE
SAME STORE
S.
No. Opinion No. of respondents Percentage
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
It could be stated from the above table that 38.5 percent of the respondents
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.
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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.
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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
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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.
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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
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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.
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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.
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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‟.
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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
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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
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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
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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.
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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
(BETWEEN FAVOURABLE AND UNFAVOURABLE GROUPS)
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.
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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
(BETWEEN FAVOURABLE AND UNFAVOURABLE GROUPS)
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
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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
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TABLE NO: 5.36
RELATIVE DISCRIMINATING INDEX
(BETWEEN FAVOURABLE AND UNFAVOURABLE GROUPS)
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.
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TABLE NO: 5.37
CLASSIFICATION RESULTS
(BETWEEN FAVOURABLE AND UNFAVOURABLE GROUPS)
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
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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.
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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.
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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
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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.
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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.
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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%
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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.
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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
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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
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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.
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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.
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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.
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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.
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FIGURE NO: 5.5
DENDROGRAM USING WARD LINKAGE RESCALED DISTANCE
CLUSTER COMBINE
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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
(Cronbach‟s Alpha=0.891,
16.5% variance)
Cluster-3 : Go Grabber
(Cronbach‟s Alpha=0.881,
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
(Cronbach‟s Alpha=0.932,
16.8% variance)
Cluster-5 : Opinion former
(Cronbach‟s Alpha=0.864,
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
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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
Cluster-1 : Value seeker
(Cronbach‟s Alpha=0.942,
41.3% variance)
Cluster-2 : Leader
(Cronbach‟s Alpha=0.875,
16.5% variance)
Cluster-3 : Go Grabber
(Cronbach‟s Alpha=0.862,
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)
Cluster-4 : Venturesome
(Cronbach‟s Alpha=0.795,
17.5% variance)
Cluster-5 : Opinion former
(Cronbach‟s Alpha=0.893,
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)
Note : Figures in parenthesis is mean score
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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
Cluster-1 : Value seeker
(Cronbach‟s
Alpha=0.921, 31.6%
variance)
Cluster-2 : Leader
(Cronbach‟s
Alpha=0.932, 26.1%
variance)
Cluster-3 : Go Grabber
(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)
Cluster-4 : Venturesome
(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)
Note : Figures in parenthesis is mean score
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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
respondents is discussed in the following table.
TABLE NO: 5.50
INTERNET USAGE PATTERN ACROSS VARIOUS SEGMENTS
Cluster-1 : Value seeker
(Cronbach‟s
Alpha=0.942, 26.1%
variance)
Cluster-2 : Leader
(Cronbach‟s
Alpha=0.932, 23.5%
variance)
Cluster-3 : Go Grabber
(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)
Cluster-4 : Venturesome
(Cronbach‟s
Alpha=0.941, 17.8%
variance)
Cluster-5 : Opinion
former (Cronbach‟s
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)
Note : Figures in parenthesis is mean score
From the above table it is observed that most of the respondents are using
internet daily basis followed by once in a week.
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5.8.5 Activities undertaken by various segments
Segment wise classification of the different leisure time activities of the
respondents is discussed in the following table.
TABLE NO: 5.51
ACTIVITIES UNDERTAKEN BY VARIOUS SEGMENTS
Cluster-1 : Value seeker
(Cronbach‟s Alpha=0.949,
36.1% variance)
Cluster-2 : Leader
(Cronbach‟s
Alpha=0.979, 16.2%
variance)
Cluster-3 : Go Grabber
(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)
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Cluster-4 : Venturesome
(Cronbach‟s Alpha=0.944,
21.6% variance)
Cluster-5 : Opinion
former (Cronbach‟s
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)
Visiting Shopping Malls
(41.7)
Visiting Shopping Malls
(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)
Visiting Amusement Parks
(17.7)
Practicing Yoga / Reiki
(15.3)
Badminton (15.7)
Giving Dinner Parties
(15.3)
Practicing Yoga / Reiki
(14.1)
Visiting Amusement Parks
(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.
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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
Cluster-1 : Value seeker
(Cronbach‟s
Alpha=0.942, 23.9%
variance)
Cluster-2 : Leader
(Cronbach‟s
Alpha=0.962, 19.9%
variance)
Cluster-3 : Go Grabber
(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)
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Cluster-4 : Venturesome
(Cronbach‟s
Alpha=0.978, 13.4%
variance)
Cluster-5 : Opinion
former (Cronbach‟s
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)
Note : Figures in parenthesis is mean score
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.
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5.8.7 Purpose to Visit
Purpose of visit is discussed through the following table.
TABLE NO: 5.53
PURPOSE TO VISIT
Cluster-1 : Value seeker
(Cronbach‟s
Alpha=0.876, 19.6%
variance)
Cluster-2 : Leader
(Cronbach‟s
Alpha=0.893, 23.5%
variance)
Cluster-3 : Go Grabber
(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)
Shopping / window shop
and hand out (23.9)
Window shopping / hang
out (15.2)
Window shopping / hang
out (13.4)
Window shopping / hang
out (10.7)
Shopping / window shop
and hand out (15.2)
Cluster-4 : Venturesome
(Cronbach‟s
Alpha=0.896, 14.8%
variance)
Cluster-5 : Opinion
former (Cronbach‟s
Alpha=0.932, 9.7%
variance)
Shopping (65.1) Shopping (51.4)
Shopping / window shop
and hand out (22.5)
Shopping / window shop
and hand out (30.6)
Window shopping / hang
out (12.4)
Window shopping / hang
out (18.1)
Note : Figures in parenthesis is mean score
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.
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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
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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
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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
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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
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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.
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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.
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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‘.
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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.
******
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