KUMANDAN

Marketing Research Project
To determine the consumer preferences while buying
toothpastes in the age group 21-30.
Report
Submitted by:
Kunal Singh (2010 C43)
Nitika Madan (2010C44)
Nikhil Agarwal (2010C45)

Acknowledgement
We would like to thank our Professor, Mr. Prantosh Banerjee for providing us constant
guidance during our project and providing us with an opportunity to apply the concepts learnt
in the course “Marketing Research-I” to a practical and real life situation.
We would also like to thank all the respondents who gave their valuable time for filling up the
questionnaires and for giving valuable inputs during the exploratory research. Their unbiased
and valuable input has helped us to administer a project in which we have taken out
inferences about the consumer buying behavior for toothpastes.

Executive Summary
Oral hygiene is sought to be one of the most necessary aspects to maintain good health
since the pre-modern era where natural products like Neem sticks were used to maintain
good teeth. With the advancement of technology in the modern era, products like
toothpastes, mouth washes, dental floss, and teeth whiteners have been introduced.
Realizing the importance of these products in consumers daily lives especially toothpastes,
many companies like P & G, Hindustan Unilever etc. are planning to launch products to fight
for the share of the existing market giants. Before launching a new product in the market,
the companies need to realize the factors affecting the buying behavior so as to design their
marketing strategies to cater to the correct consumer segment(s).
Initially, an exploratory research was conducted to figure out what brands of toothpastes the
consumers know about and what factors do the consumers consider while making their
purchase decision.
Then questionnaires were administered through an online survey. Two questionnaires were
administered with one question different where the first questionnaire had one non-attribute
based question while the second had attribute based question; this being done for using
multi-dimensional scaling. Other approaches used for analysis were tabs, cross-tabs, chi-
square, factor analysis, cluster analysis, etc. These statistical tools were used with the help
of MS-Excel and SPSS. The analysis from these tools helped gather useful insights upon
what type of respondents we had, what attributes the consumers consider while making the
purchase decision, how the consumers perceive the various brands to be etc.

Table of Contents
Background…………………………………………………………………. Page 1
Objectives…………………………………………………………………... Page 2
Research Approach……………………………………………………….. Page 3
Exploratory Research……………………………………………………… Page 7
Secondary Data……………………………………………………………. Page 9
Questionnaire Design……………………………………………………... Page 11
Project Findings……………………………………………………………. Page 20
Respondent Profile……………………………………... Page 20
Chi-square Analysis……………………………………. Page 24
Factor Analysis………………………………………….. Page 46
Perceptual Maps………………………………………... Page 50
Cluster Analysis………………………………………… Page 60
Multi-dimensional scaling……………………………… Page 67
Analysis……………………………………………………………………... Page 74
Limitations…………………………………………………………………... Page 76
Conclusion…………………………………………………………………... Page 76
Appendix – Data Sheet …………………………………………………… Page 77

Background
The oral care market in India is estimated to be Rs 4,400-crore. Toothpaste, for the record,
is estimated to be Rs 3,200 crore in size. Colgate Palmolive is the leader in Indian
toothpaste market having a market share of 50% in 2009. HUL follows with 28%. HUL’s
brand Close-Up has a market share of 17% and Pepsodent 11%, according to AC Nielsen
data. Dabur is enjoying 10% market share.
From past few years the toothpaste market is restructuring & market share of different
players are changing. Since 2007-08, analysts said HUL has lost 8-10% market share in oral
care.
Market is likely to see a few key launches in the toothpaste segment this year.
Procter & Gamble (P&G) is set to throw another gauntlet at Colgate-Palmolive and
Hindustan Unilever (HUL). The company plans to launch its global toothpaste brand Crest at
an aggressive price point this year.
As and when P&G introduces Crest in India, it will entail price competition as well as heavy
brand investment in the category from all the players, in our view. It will put the market share
and margins of Colgate under pressure. Colgate will need to sustain its higher-than-industry
ad spends to protect its turf.
The consumer products arm of Johnson & Johnson (J&J) may launch toothpaste under the
Listerine umbrella, while GlaxoSmithKline (GSK) Consumer Healthcare may relaunch its
Aquafresh brand, phased out a few years earlier. GSK had launched Sensodyne toothpaste
last year. A mass-market toothpaste product is what is missing at the moment, which GSK
will plug with the relaunch of Aquafresh. Kishore Biyani's Future Group is also entering the
fray with its private label.

Objectives
Primary Research Objective (PRO):
To determine the consumer preferences while buying toothpastes in the age group 21-30.
Secondary Research Objectives (SROs):
 To determine the various factors affecting the purchase of toothpastes.
 To determine the brand preferences for toothpastes in the age group.
 To determine the type of toothpastes preferred by consumers in the age group.
 To determine the positioning of various brands in the minds of consumers in the age
group.
 To determine whether the various demographical factors affect the purchase of
toothpaste.
 To determine the relative importance of various functionalities attached to toothpaste
by youngsters (whiteness, freshness, protection).

Research Approach
Data Collection Method:
An exploratory research was conducted for which the following techniques were used:
a. Open-ended questionnaire
These questions were used to know what are the different attributes which a student at SIC
looks for while selecting toothpaste.
b. Focused group discussions
Here, a discussion among a group of students was arranged to bring out the attributes that
are evaluated by the students while selecting toothpaste.
For secondary research, the following sources were used:
a. Websites of different toothpaste brands to know their unique selling propositions.
b. CMIE
c. Other journals and reports
Based on the attributes found out in the exploratory research and the secondary research,
the information gap was identified and hence it was decided to conduct primary research to
fill the gap. The research was conducted by administering questionnaire for the target age-
group. For primary data collection, Questionnaire administration was done personally and
through online questionnaires.

Measurement Technique:
To record the data the following measurement techniques would be used:
Rank order scale
In order to know the preference of this scale would be used to rank the various brands.
Itemized non- comparative rating scale
Respondents would rate certain attributes of mobile phones on a scale with positions from
extremely influential to not at all influential.
Likert Scale
The Likert scale would be used to find out how the respondents perceive the features of a
mobile phone.
Semantic Differential Scale
Respondents would rate the mobile phones they are aware of on various attributes.
These individual rating scales would be combined to study the overall effect of all the
attributes and different Attitude scales would be used to rank items.
Dichotomous Questions
These questions would be asked to get an objective answer.
Willingness of Respondents
Personal questions like Name, Age, Gender etc have been asked at the end of the
questionnaire.

Sampling Plan:
The sample for survey would be taken on the following basis.
Sample Frame : People residing or working in India
Sample Unit : Students and working professionals
Sample Size : 159 respondents
Time Frame : 10-15 Days.
Sampling Method: Simple random sampling (SRS)
Data Analysis Technique
The data collected from the exploratory research provided us with the different factors that a
consumer looks for in toothpaste. Based on these responses, another questionnaire will be
used to do factor analysis to reduce the number of attributes handled into fewer attributes,
so that handling of factors becomes easier for subsequent analysis.
To determine the profile of various consumers so that we can know more about their
lifestyle, attitudes and preferences so as to gain an insight on what kind of toothpaste they
are likely to choose, we will use cluster analysis, a segmentation technique.
Finally to evaluate the student perceptions about toothpastes of different brands, we will use
attribute based perceptual mapping using Discriminant analysis and also Multi-Dimensional
Scaling.
Apart from using these three major techniques, we plan to use chi square analysis with cross
tab to evaluate whether the preferences are different for various demographical factors. We
will also use ANOVA technique to analyze if the effect of various independent variables on
the choice of the brand of toothpaste and also the interaction effect that these variables have
on the toothpaste choice of the population.
These various techniques would be carried out the help of software like MS-Excel, SPSS
etc.

Time and Cost Requirements:
Time Requirements:
Sl. No. Activity Expected Start Date Expected Completion
Date
1 Submission of research
proposal
02-Jan-11 05-Jan-11
2 Questionnaire preparation 06-Jan-11 11-Jan-11
3 Data collection 12-Jan-11 22-Jan-11
4 Data entry 23-Jan-11 24-Jan-11
5 Data analysis 25-Jan-10 28-Jan-10
6 Final report compilation 29-Jan-10 31-Jan-10
Buffer 2 days
Cost requirement:
 Expenses for printing exploratory research questionnaires
 Expenses for printing main questionnaires
 Report Printing
 Binding

Exploratory Research:
Questionnaire:
1. Which brands of toothpaste are you aware of?
2. What brand of toothpaste do you use?
3. Why do you use the aforementioned toothpaste?
4. What additional features would you like to see in your toothpaste?
5. What factors influence the choice of toothpaste?

Findings:
The exploratory research phase aims to find out the parameters over which the research
should proceed. The questionnaires explored the different factors that respondents look into
before buying toothpaste. The sample size was 12 respondents.
Some of the findings of exploratory research were as follows
Brands commonly used were:
Colgate, close-up and Pepsodent
Other Brands which people were able to recall were:
Babool, Cibaca, Meswak, Signal, Vicco Vajradanti, Dabur, Glister, Emofoam, Neem, Amway
Some of the reasons given by the respondents for choosing their preferred
brand of toothpaste were:
Good Cleaning Power, Habit, Brand Loyalty, Good Lather, Color, Shelf Positioning,
Calcium content, Flavors, liking for gel based toothpastes , taste , Cavity Protection
,Prevention of Bad Breath, Medicinal Value , and utility viewpoint.
Some additional features that the respondents said they might want in their
toothpastes were:
Lower Price, Change of Color, New Flavors, Mouth, Refreshing Breath, Anti Bacterial
Protection
The factors that respondents thought were influential in buying toothpastes in
general were:
Advertisements, Family Influence, Packaging, Personal Experience, Protection, Cleanliness,
whitening, freshness, taste, Dentist Recommendations, Pricing, Availability and peer
suggestion.

Secondary Data
The oral care market in India is estimated to be Rs 4,400-crore. Toothpaste, for the record, is
estimated to be Rs 3,200 crore in size, followed by the toothbrush segment at Rs 800 crore,
toothpowder at Rs 300 crore, and mouthwash being Rs 100 crore.
Colgate Palmolive is the leader in Indian toothpastes having a market share of 50% in 2009. HUL
follows with 28%. It’s Close-Up has a market share of 17% and Pepsodent 11%, according to AC
Nielsen data.
Another player, Dabur, enjoys 10% share through its portfolio of Red Toothpaste, Promise, Meswak
and Babool. Recently, GlaxoSmithKline Consumer forayed into the sector by launching Sensodyne
(though it was available as an import earlier), a toothpaste brand for sensitive teeth. The Future
Group launched its Sach brand recently in this segment. P&G is launching Crest in India
In toothpowder, Colgate leads in the white segment with 70 per volume share (value share is even
more), while Dabur leads in the red segment with 70 per cent volume share again (value is more than
70 per cent).

The major brands are:
Hindustan Unilever
Pepsodent Germicheck+ Close-Up Crystal
Pepsodent Whitening Close-Up Crystal Frost
Pepsodent 2in1 Close-Up Eros Red
Pepsodent Center Fresh Close-Up Green Core
Pepsodent Gum Care Close-Up Green Explorer
Pepsodent Sensitive Close-Up Jares
Pepsodent Kids Close-Up Lemon Mint
Close-Up Menthol Chill
Close-Up Orange Explorer
Close-Up Red Hot
Close-Up Snowman Green
Close-Up Yellow Core
Colgate Palmolive Dabur
Colgate Dental Cream Dabur Red
Colgate Total 12 Meswak
Colgate Sensitive Promise
Colgate Max Fresh Lal Dant Manjan
Colgate Kids ToothPaste Babool Mint Fresh Gel
Colgate Fresh Energy Gel
Colgate Herbal
Colgate Advanced Whitening
Colgate Cibaca Family Protection
Colgate Active Salt
Colgate Maxwhite
Others
Emoform Himalaya Dental Cream
Optifresh (Oriflame) Ajanta
Aquafresh Crest
Sensodyne Dant Kanti

Questionnaire Design:
Two questionnaires were administered with the aim of conducting multi-dimensional scaling.
One questionnaire had non attribute based question in which respondents had to give
distance scores between two brands based on their perception while the other questionnaire
had attribute based question in which respondent had to rank each brand according to the
various features identified through the exploratory research. Questionnaires were distributed
to similar set of respondents to get similar unbiased responses.
Questionnaire 1: Based on Non Attribute Based Response
Recruiter
1. Name: _________________________
2. Region:
West East
North South
3. Occupation: _____________________
4. Gender:
5. Age:
Less than 15 Between 16-
20
Between 21-
25
Between 26-
30
Above 30
Main Questionnaire
1. How often do you use toothpaste in day?
 Once a day  Twice a day
 After every meal
2. How often do you buy toothpaste?
 Every month  Every two months
 Every three months  Not every often
3. Which brand of toothpaste do you use?
 Colgate  Close up  Pepsodent
 Meswak  Babool  Dabur Red Toothpaste
 Sensodyne  Amway  Others
(____________)
4. How long have you been using this toothpaste?
 Less than 3 months
 Between 3 to 12 months
 Between 1 to 3 years
 More than 3 years

5. How often do you change your toothpastes?
 Do not change/ Brand Loyal
 Occasionally
 Frequently
 As long as it is a toothpaste, the brand doesn’t matter
6. Which type of toothpaste do you prefer?
 Paste
 Gel
 Others
7. Where do you buy your toothpaste from?
 General store
 Departmental store
 Medical shops/ Pharmacies
8. What features do you look for while buying toothpaste? Rank these features
according to your preference.
Features Rank
Price
Cleansing Power
Medicinal value
Lather
Calcium Content
Cavity Protection
Prevention against bad
breath
Anti Bacterial Protection
Flavors
Brand
9. What various promotional activities for toothpaste have you come across?
 Newspaper Ads
 TV Commercial
 Radio Jingle
 Kiosks
 Free Sample Distribution
 Word of mouth/Recommendations
10. Whose advice do you generally take while buying toothpaste?
 Friends
 Family
 Individual decision
 Dentist
 Shopkeeper/Salesperson

11. I select the toothpaste because it is cheaper than other toothpastes.
(1-Strongly agree; 2- agree; 3- neither agree nor disagree; 4- disagree; 5 –strongly
disagree)
12. The cleansing power of the toothpaste matters a lot.
disagree)
13. The brand of the toothpaste is important.
disagree)
14. I look for what medicinal value the toothpaste has to offer.
disagree)
15. Toothpaste which does not lather does not provide satisfaction.
disagree)
16. My toothpaste should provide me with optimum quantity of calcium content.
disagree)
17. I like experimenting with various flavours that toothpaste companies have to
offer.
disagree)
18. My toothpaste should protect me against cavity.
disagree)
19. The best toothpaste is which prevent me against bad breath.
disagree)
20. I look for new features promised by the toothpaste every time I buy my
toothpaste.
disagree)
21. I prefer Indian toothpastes over imported toothpastes.
disagree)
22. I buy combo packs rather than single units in order to save money.
disagree)

23. I prefer toothpastes which have offers like free toothbrush, extra quantity,
freebies etc.
disagree)
24. According to you, give the distance between each pair of brands. (1 being the
closest, 10 being the farthest)
P-Pepsodent, S- Sensodyne, C – Colgate, CL – Close Up, D – Dabur, B – Babool
P
C
S
C
P
S
P
B
S
B
C
B
CL
B
D
B
P
D
S
D
C
D
CL
D
P
CL
S
CL
C
CL

25. Read the following statements and mark accordingly
1-Strongly agree; 2- agree; 3- neither agree nor disagree; 4- disagree; 5 –strongly
disagree
(i) Health is a major concern today 1 2 3 4 5
(ii) I think a lot before buying anything 1 2 3 4 5
(iii) I eat out often 1 2 3 4 5
(iv) Branded products are better 1 2 3 4 5
(v) I make my own decisions 1 2 3 4 5
(vi) I do not mind paying higher prices for premium quality 1 2 3 4 5
(vii) Who carries cash these days; credit cards are in. 1 2 3 4 5
(vii) I go on holidays often 1 2 3 4 5
(viii) Who cares about calories? I go for Dominos, McDonalds,
Maggi, Pasta
1 2 3 4 5
(ix) Advertisements influence my decision 1 2 3 4 5
(x) Imported products are better than Indian products 1 2 3 4 5
(xi) I check for all details like Mfg date, Date of expiry before
buying a product.
1 2 3 4 5
(xi) I am brand loyal for most products 1 2 3 4 5
(xii) I would never settle abroad 1 2 3 4 5
(xiii) I watch television for my leisure 1 2 3 4 5
(xiv) Cars are used for showing off ones wealth 1 2 3 4 5
(xv) Others influence my decisions a lot 1 2 3 4 5
(xvi) I follow latest fashion and fads 1 2 3 4 5
(xvii) Indian cuisines are better than foreign cuisines 1 2 3 4 5
(xviii) I spend a lot 1 2 3 4 5
(xix) I don’t compromise quality for price 1 2 3 4 5
(xx) I party out often 1 2 3 4 5

Questionnaire 2: Based on Attribute Based Response
Recruiter
1. Name: _________________________
2. Region:
West East
North South
3. Occupation: _____________________
4. Gender:
5. Age:
Less than 15 Between 16-
20
Between 21-
25
Between 26-
30
Above 30
Main Questionnaire
1. How often do you use toothpaste in day?
 Once a day  Twice a day
 After every meal
2. How often do you buy toothpaste?
 Every month  Every two months
 Every three months  Not every often
3. Which brand of toothpaste do you use?
 Colgate  Close up  Pepsodent
 Meswak  Babool  Dabur Red Toothpaste
 Sensodyne  Amway  Others
(____________)
4. How long have you been using this toothpaste?
 Less than 3 months
 Between 3 to 12 months
 Between 1 to 3 years
 More than 3 years
5. How often do you change your toothpastes?
 Do not change/ Brand Loyal
 Occasionally
 Frequently
 As long as it is a toothpaste, the brand doesn’t matter
6. Which type of toothpaste do you prefer?
 Paste
 Gel
 Others

7. Where do you buy your toothpaste from?
 General store
 Departmental store
 Medical shops/ Pharmacies
8. What features do you look for while buying toothpaste? Rank these features
according to your preference.
Features Rank
Price
Cleansing Power
Medicinal value
Lather
Calcium Content
Cavity Protection
breath
Flavors
Brand
9. What various promotional activities for toothpaste have you come across?
 Newspaper Ads
 TV Commercial
 Radio Jingle
 Kiosks
 Free Sample Distribution
 Word of mouth/Recommendations
10. Whose advice do you generally take while buying toothpaste?
 Friends
 Family
 Individual decision
 Dentist
 Shopkeeper/Salesperson

23. I prefer toothpastes which have offers like free toothbrush, extra quantity,
freebies etc.
disagree)
24. Rank these brands according to the features
Feartures/Brands Colgat
e
Close
Up
Pepsoden
t
Babool Dabu
r
Sensodyn
e
Price
Cleansning Power
Medicinal value
Lather
Calcium Content
Cavity Protection
breath
Flavors
Brand
25. Read the following statements and mark accordingly
1-Strongly agree; 2- agree; 3- neither agree nor disagree; 4- disagree; 5 –strongly
disagree
(i) Health is a major concern today 1 2 3 4 5
(ii) I think a lot before buying anything 1 2 3 4 5
(iii) I eat out often 1 2 3 4 5
(iv) Branded products are better 1 2 3 4 5
(v) I make my own decisions 1 2 3 4 5
(vi) I do not mind paying higher prices for premium quality 1 2 3 4 5
(vii) Who carries cash these days; credit cards are in. 1 2 3 4 5
(vii) I go on holidays often 1 2 3 4 5
(viii) Who cares about calories? I go for Dominos, McDonalds,
Maggi, Pasta
1 2 3 4 5
(ix) Advertisements influence my decision 1 2 3 4 5
(x) Imported products are better than Indian products 1 2 3 4 5
(xi) I check for all details like Mfg date, Date of expiry before
buying a product.
1 2 3 4 5
(xi) I am brand loyal for most products 1 2 3 4 5
(xii) I would never settle abroad 1 2 3 4 5
(xiii) I watch television for my leisure 1 2 3 4 5
(xiv) Cars are used for showing off ones wealth 1 2 3 4 5
(xv) Others influence my decisions a lot 1 2 3 4 5
(xvi) I follow latest fashion and fads 1 2 3 4 5
(xvii) Indian cuisines are better than foreign cuisines 1 2 3 4 5
(xviii) I spend a lot 1 2 3 4 5
(xix) I don’t compromise quality for price 1 2 3 4 5
(xx) I party out often 1 2 3 4 5

Project Findings
Respondent Profile
Region:
West 76
East 27
North 42
South 14
Total 159
Occupation:
Student 130
Service 24
Self Employed 5
Total 159
West
48%
East
17%
North
26%
South
9%
Region
82%
15%
3%
Chart Title
Student Service Self Employed

Gender:
Male 105
Female 54
Total 159
Age:
Less than 15 0
Between 16-20 0
Between 21-25 137
Between 26-30 22
Above 30 0
Total 159
Male
66%
Female
34%
Gender
0
20
40
60
80
100
120
140
Less than
15
Between
16-20
Between
21-25
Between
26-30
Above 30
0 0
137
22
0

Frequency of Use:
Once a day 81
Twice a day 75
After every meal 3
Total 159
Purchase Frequency:
Every month 84
Every two months 60
Every three months 11
Not very often 4
Total 159
51%47%
2%
Frequency of Use
Once a day Twice a day After every meal
Every month
53%Every two
months
38%
Every three
months
7%
Not
very
often
2%
Purchase Frequency

Current Brand:
Colgate 72
Close up 37
Pepsodent 31
Meswak 5
Babool 1
Dabur Red 6
Sensodyne 1
Amway 1
Others 0
Total 159
0 10 20 30 40 50 60 70 80
Colgate
Close up
Pepsodent
Meswak
Babool
Dabur Red
Sensodyne
Amway
Others
72
37
31
5
1
6
1
1
0

Chi- Square Analysis
Analysis 1: Type of Toothpaste V/S Age Group
Hypothesis:
H0: The type of the toothpaste does not have a significant impact on the
buying behavior of various age groups at confidence level of 80%
Ha: The type of the toothpaste has a significant impact on the buying behavior
of various age groups at confidence level of 80%
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
Age * Type 159 100.0% 0 .0% 159 100.0%
Age * Type Crosstabulation
Count
Type Total
Paste Gel Others Paste
Age Between 21-25 70 61 6 137
Between 26-30 17 4 1 22
Total 87 65 7 159
Chi-Square Tests
5.593a
2 .061
6.086 2 .048
3.770 1 .052
159
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asy mp. Sig.
(2-sided)
1 cells (16.7%) have expected count less than 5. The
minimum expected count is .97.
a.

P critical = 0.20
P observed= 0.061
At 80 % confidence level, since P observed < P critical we reject the null hypothesis
indicating that there is significant relationship between age group and the type of
toothpastes preferred.

Analysis 2: Place of Purchase V/S Age Group
Hypothesis:
H0: The place of purchase of the toothpaste does not have a significant impact
on the buying behavior of various age groups at confidence level of 80%
Ha: The place of purchase of the toothpaste has a significant impact on the
Cases
Valid Missing Total
Age * PlaceOfPurchase 159 100.0% 0 .0% 159 100.0%
Age * PlaceOfPurchase Crosstabulation
Count
PlaceOfPurchase Total
General
Stores
Departmental
Stores
Medical
Shops/Pharma
cies
General
Stores
Age Between 21-25 87 47 3 137
Between 26-30 8 13 1 22
Total 95 60 4 159
Chi-Square Tests
5.841a
2 .054
5.716 2 .057
5.554 1 .018
159
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asy mp. Sig.
(2-sided)
a.

P critical = 0.20
P observed= 0.054
indicating that there is significant relationship between age group and the place of purchase
of the toothpastes.

Analysis 3: Brand V/S Age Group
Hypothesis:
H0: The Brand of the toothpaste does not have a significant impact on the
Ha: The Brand of the toothpaste has a significant impact on the buying
behavior of various age groups at confidence level of 80%
Cases
Valid Missing Total
Age * Brand 159 100.0% 0 .0% 159 100.0%
Age * Brand Crosstabulation
Count
Brand Total
Colgate
Close
Up
Pepsode
nt Meswak Babool
Dabur
Red
Toothpast
e
Sensody
ne Others Colgate
Age Between 21-
25
59 35 27 5 0 4 1 6 137
Between 26-
30
13 2 4 0 1 2 0 0 22
Total 72 37 31 5 1 6 1 6 159
Chi-Square Tests
13.371a
7 .064
12.788 7 .077
.243 1 .622
159
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asy mp. Sig.
(2-sided)
a.

P critical = 0.20
P observed= 0.064
indicating that there is significant relationship between age group and the preference
of brands in the toothpastes

Analysis 4: Brand V/S Region
Hypothesis:
buying behavior of various regions at confidence level of 80%
behavior of various regions at confidence level of 80%
Cases
Valid Missing Total
Region * Brand 159 100.0% 0 .0% 159 100.0%
Region * Brand Crosstabulation
Count
Brand Total
Colgate
Close
Up
Pepsode
nt Meswak Babool
Dabur Red
Toothpaste
Sensodyn
e Others Colgate
Regio
n
West 34 17 16 2 0 1 1 5 76
East 13 4 6 1 0 3 0 0 27
Nort
h
20 11 7 1 1 1 0 1 42
Sout
h
5 5 2 1 0 1 0 0 14
Total 72 37 31 5 1 6 1 6 159
Chi-Square Tests
16.706a
21 .729
17.126 21 .703
.638 1 .425
159
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asy mp. Sig.
(2-sided)
a.

P critical = 0.20
P observed= 0.729
At 80 % confidence level, since P observed > P critical we do not reject the null
hypothesis indicating that there is no significant relationship between region and the
preference of the toothpastes.

Analysis 5: Brand V/S Occupation
Hypothesis:
buying behavior of occupation groups at confidence level of 80%
behavior of occupation at confidence level of 80%
Cases
Valid Missing Total
Occupation * Brand 159 100.0% 0 .0% 159 100.0%
Occupation * Brand Crosstabulation
Count
Brand Total
Colgate
Close
Up
Pepsode
nt
Meswa
k Babool
Dabur
Red
Toothpast
e
Sensody
ne Others Colgate
Occupati
on
Student 58 34 23 5 0 4 1 5 130
Service 12 3 6 0 1 1 0 1 24
Self
Employed
2 0 2 0 0 1 0 0 5
Total 72 37 31 5 1 6 1 6 159
Chi-Square Tests
15.483a
14 .346
14.251 14 .431
.372 1 .542
159
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asy mp. Sig.
(2-sided)
a.

P critical = 0.20
P observed= 0.346
hypothesis indicating that there is no significant relationship between occupation and
the preference of brands of the toothpastes.

Analysis 6: Age group V/S Usage Time
Hypothesis:
H0: The age group of the users does not have a significant impact on the
usage period of the same brand at confidence level of 80%
Ha: The age group of the users has a significant impact on the usage period of
the same brand at confidence level of 80%
Cases
Valid Missing Total
Age * UsagePeriod 159 100.0% 0 .0% 159 100.0%
Age * UsagePeriod Crosstabulation
Count
UsagePeriod Total
Less
than 3
months
Between 3
to 12
months
Between
1 to 3
years
More
than 3
years 5.00 6.00 7.00 9.00
Less
than 3
months
Age Between 21-
25
59 35 27 5 0 4 1 6 137
Between 26-
30
13 2 4 0 1 2 0 0 22
Total 72 37 31 5 1 6 1 6 159
Chi-Square Tests
13.371a
7 .064
12.788 7 .077
.243 1 .622
159
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asy mp. Sig.
(2-sided)
a.

P critical = 0.20
P observed= 0.064
indicating that there is significant relationship between the age group and the time
interval they use the toothpaste.

Analysis 7: Occupation Vs Frequency of Change
Hypothesis:
H0: The occupation of the users does not have a significant impact on the
frequency of change of brands at confidence level of 80%
Ha: The occupation of the users has a significant impact on the frequency of
change of brands at confidence level of 80%
Cases
Valid Missing Total
Occupation *
FrequencyOfChange 159 100.0% 0 .0% 159 100.0%
Occupation * FrequencyOfChange Crosstabulation
Count
FrequencyOfChange Total
Brand Loyal Occasionally Frequently Brand Loyal
Occupation Student 76 48 6 130
Service 13 11 0 24
Self Employed 1 3 1 5
Total 90 62 7 159
Chi-Square Tests
6.118a
4 .191
6.180 4 .186
1.807 1 .179
159
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asy mp. Sig.
(2-sided)
a.

P critical = 0.20
P observed= 0.191
indicating that there is significant relationship between the occupation and the
frequency of change of toothpastes.

Analysis 8: Occupation Vs Point of Purchase
Hypothesis:
H0: The occupation of the users does not have a significant impact on the
point of purchase at confidence level of 80%
Ha: The occupation of the users has a significant impact on the point of
purchase at confidence level of 80%
Cases
Valid Missing Total
Occupation *
PointOfPurchase 159 100.0% 0 .0% 159 100.0%
Occupation * PointOfPurchase Crosstabulation
Count
PointOfPurchase Total
General Store
Departmental
Store
Medical
Shops/Pharma
cies General Store
Occupation Student 81 46 3 130
Service 12 11 1 24
Self Employed 2 3 0 5
Total 95 60 4 159
Chi-Square Tests
2.523a
4 .641
2.546 4 .636
1.823 1 .177
159
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asy mp. Sig.
(2-sided)
a.

P critical = 0.20
P observed= 0.641
hypothesis indicating that there is no significant relationship between the occupation
and the point of purchase

. Analysis 9: Gender Vs Brand
Hypothesis:
H0: The gender of the respondents has a significant impact on the brand of
the toothpaste they use at confidence level of 80%
Ha: The gender of the respondents has a significant impact on the brand of
the toothpaste they use at confidence level of 80%
Cases
Valid Missing Total
Gender * Brand 159 50.0% 159 50.0% 318 100.0%
Gender * Brand Crosstabulation
Count
Brand Total
Colgate
Close
up
Pepsode
nt Meswak Babool
Dabur Red
Toothpast
e
Sensody
ne Others Colgate
Gend
er
Male 45 25 20 4 1 5 0 5 105
Femal
e
27 12 11 1 0 1 1 1 54
Total 72 37 31 5 1 6 1 6 159
Chi-Square Tests
4.966 7 .664
5.736 7 .571
1.315 1 .252
159
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asy mp. Sig.
(2-sided)

P critical = 0.20
P observed= 0.664
hypothesis indicating that there is no significant relationship between the gender and
the brand they use.

. Analysis 10: Gender Vs Type
Hypothesis:
H0: The gender of the respondents has a significant impact on the type of the
toothpaste they use at confidence level of 80%
Ha: The gender of the respondents has a significant impact on the type of the
toothpaste they use at confidence level of 80%
Cases
Valid Missing Total
Gender * Type 159 50.0% 159 50.0% 318 100.0%
Gender * Type Crosstabulation
Count
Type Total
Paste Gel Others Paste
Gender Male 58 41 6 105
Female 29 24 1 54
Total 87 65 7 159
Chi-Square Tests
1.478a
2 .478
1.664 2 .435
.057 1 .812
159
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asy mp. Sig.
(2-sided)
minimum expected count is 2.38.
a.

P critical = 0.20
P observed= 0.478
hypothesis indicating that there is no significant relationship between the gender and
the type of toothpaste they use.

Analysis 11: Gender Vs Frequency of Change
Hypothesis:
H0: The gender of the respondents has a significant impact on the frequency
at which they change the toothpaste at confidence level of 80%
Ha: The gender of the respondents has a significant impact on the frequency
at which they change the toothpaste at confidence level of 80%
Cases
Valid Missing Total
Gender *
FrequencyOfChange 159 50.0% 159 50.0% 318 100.0%
Gender * FrequencyOfChange Crosstabulation
Count
FrequencyOfChange Total
Brand Loyal Occasionally Frequently Brand Loyal
Gender Male 61 42 2 105
Female 29 20 5 54
Total 90 62 7 159
Chi-Square Tests
4.583a
2 .101
4.287 2 .117
1.448 1 .229
159
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asy mp. Sig.
(2-sided)
minimum expected count is 2.38.
a.

P critical = 0.20
P observed= 0.101
indicating that there is significant relationship between the gender and frequency at
which they change the toothpaste.

Factor Analysis
Factor Analysis is a general name denoting a class of procedures primarily used for data
reduction and summarization. In marketing Research, there may be a large number of
variables most of which are correlated and which must be reduced to a manageable level.
Relationships among sets of many interrelated variables are examined and represented in
terms of a few underlying factors. Factor Analysis is an independent technique in that an
entire set of independent relationships is examined.
Factor analysis is used in the following circumstances:
1. To identify underlying dimensions or factors that explains the correlation among a set of
variables. For ex, a set of lifestyle statements may be used to measure the psychographic
profiles of consumers. These statements may be factor analyzed to identify the underlying
psychographic factors.
2. To identify a new, smaller set of uncorrelated variables to replace the original set of
correlated variables in subsequent multivariate analyses.
3. To identify a smaller set of salient variables from a larger set for use in subsequent
multivariate analysis. For example, a few of the original lifestyle statements that correlate
highly with the identified factors may be used as independent variables to explain the
differences between the loyal and normal users.
In the exploratory research, we obtained 13 attributes which respondents find important
while buying toothpaste. Factor analysis was used to club similar attributes into factors so as
to know what exactly the consumers look for while choosing toothpaste.
The total variance explained is shown in the table below along with the eigen value at each
stage. When the eigen value drops below 1, we stop the factor analysis process. Since at
the 5th stage, the eigen value became < 1, we stopped the process and concluded that
there are 5 factors as per the respondents.
By the main questionnaire, we tried to measure people’s attitude towards various attributes
that directly or indirectly affect the buying behaviors of people towards buying of toothpastes.
Respondents were asked to rate their attitude towards on a Likert scale of 1 to 5, where 1
stands for Strongly agree and 7 stands for strongly disagree.
The data collected was analyzed using SPSS for identifying the significant factors. Factors
with eigen values more than 1 were considered and it explained 71% of the total variation.

Factors identified are:
 Sales Promotion
 Prevention Against Germs
 Value for Money
 Medicinal Content
 Functions
SPSS Output
Communalities
1.000 .662
1.000 .790
1.000 .642
1.000 .563
1.000 .621
1.000 .631
1.000 .765
1.000 .738
1.000 .794
1.000 .757
1.000 .770
1.000 .795
1.000 .691
IndianToothpastePref er
Brand
MedicinalValue
Lather
CalciumContent
Diff erentFlavors
ProtectionAgainstCav ity
ProtectionAgainstBad
Breath
Features
Cleansning
PromotionalPacks
Off ersGif ts
Price
Initial Extraction
Extraction Method: Principal Component Analy sis.
Total Variance Explained
2.908 22.366 22.366 2.908 22.366 22.366 2.186 16.813 16.813
2.062 15.860 38.226 2.062 15.860 38.226 1.870 14.388 31.201
1.675 12.888 51.114 1.675 12.888 51.114 1.840 14.157 45.358
1.457 11.208 62.322 1.457 11.208 62.322 1.736 13.353 58.711
1.118 8.601 70.923 1.118 8.601 70.923 1.588 12.212 70.923
.808 6.218 77.141
.689 5.302 82.443
.585 4.497 86.940
.485 3.733 90.673
.359 2.759 93.432
.335 2.580 96.011
.284 2.183 98.194
.235 1.806 100.000
Component
1
2
3
4
5
6
7
8
9
10
11
12
13
Total % of Variance Cumulativ e % Total % of Variance Cumulativ e % Total % of Variance Cumulativ e %
Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Extraction Method: Principal Component Analysis.

Rotated Component Matrixa
.418 -.046 .187 .618 -.263
.094 .269 .841 -.026 .008
-.165 -.037 -.139 .768 .070
.527 -.191 .406 .145 .250
.127 .262 .063 .718 .128
.419 -.329 .443 -.167 .350
-.025 .844 .116 .195 -.041
-.076 .840 .048 -.045 .149
.220 -.142 .070 .339 .779
-.032 .269 -.026 -.131 .816
.842 -.196 .044 .140 -.038
.861 .180 -.034 -.083 .116
-.012 .003 .830 .032 -.026
IndianToothpastePref er
Brand
MedicinalValue
Lather
CalciumContent
Diff erentFlavors
ProtectionAgainstCav ity
ProtectionAgainstBad
Breath
Features
Cleansning
PromotionalPacks
Off ersGif ts
Price
1 2 3 4 5
Component
Extraction Method: Principal Component Analy sis.
Rotation Method: Varimax with Kaiser Normalization.
Rotation converged in 7 iterations.a.
Component Transformation Matrix
.754 -.105 .498 .277 .308
-.220 .878 .232 .299 .193
.084 -.092 -.500 .837 -.181
.032 -.003 -.508 -.123 .852
-.612 -.457 .435 .343 .331
Component
1
2
3
4
5
1 2 3 4 5
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.

Inferences:
Number of Major Factors = 5
70.923 % of total variance is explained cumulatively by the extracted factors.
Factor1= fn (Promotional Pack, Offers & Gifts) Sales Promotion
Factor2= fn (Protection against cavity, Protection against bad breath)Prevention Against
Germs
Factor3= fn (Brand, Price)Value for Money
Factor4= fn (Medicinal Value, Calcium Content)Medicinal Content
Factor5= fn (Features, Cleansing)Functions

Perceptual Maps
After the factor analysis, perceptual maps were drawn using excel for graphically depicting
the relationship by showing the loadings of various attributes on factors identified. Every
possible combination leading to 5
C2 i.e. total ten maps are drawn for the factor combinations.
Sales Promotion Vs. Prevention Against Germs
Sales
Promotion
Prevention
Against
Germs
PromotionalPacks 0.841639 -0.19565
OffersGifts 0.860928 0.180006
ProtectionAgainstCavity -0.02458 0.843645
ProtectionAgainstBadBreath -0.07631 0.839862

Sales Promotion Vs. Value for Money
Sales
Promotion
Value For
Money
PromotionalPacks 0.841639 0.044328
OffersGifts 0.860928 -0.03367
Brand 0.093782 0.841154
Price -0.01244 0.83034

Sales Promotion Vs. Medicinal Content
Sales
Promotion
Medicinal
Content
PromotionalPacks 0.841639 0.140178
OffersGifts 0.860928 -0.08269
MedicinalValue -0.16469 0.767849
CalciumContent 0.126874 0.718397

Sales Promotion Vs. Functions
Sales Promotion Functions
PromotionalPacks 0.841639 -0.03827
OffersGifts 0.860928 0.116341
Features 0.219508 0.778582
Cleansing -0.03229 0.815857

Prevention Against Germs Vs. Value for Money
Prevention
Against
Germs
Value
for
Money
ProtectionAgainstCavity 0.843645 0.116313
ProtectionAgainstBadBreath 0.839862 0.047713
Features -0.14231 0.778582
Cleansning 0.269371 0.815857

Prevention against Germs Vs. Medicinal Content
Prevention
against
Germs
Medicinal
Content
ProtectionAgainstCavity 0.843645 0.194529
ProtectionAgainstBadBreath 0.839862 -0.04482

Prevention Against Germs Vs. Functions
Prevention
Against
Germs
Functions
ProtectionAgainstCavity 0.843645 -0.0406
ProtectionAgainstBadBreath 0.839862 0.149276
Features -0.14231 0.778582
Cleansing 0.269371 0.815857

Value for Money Vs. Medicinal Content
Value
for
Money
Medicinal
Content
Brand 0.841154 -0.02608
Price 0.83034 0.03197

Value for Money Vs. Functions
Value for
Money
Functions
Brand 0.841154 0.008322
Price 0.83034 -0.02635
Features 0.070271 0.778582
Cleansning -0.02636 0.815857

Medicinal Content Vs. Functions
Medicinal
Content
Functions
MedicinalValue 0.767849 0.070459
Features 0.33865 0.778582
Cleansing -0.1312 0.815857

Cluster Analysis
Cluster Analysis is a class of techniques used to classify objects or cases into relatively
homogeneous groups called clusters. Objects in each cluster tend to be similar to each other
and dissimilar to objects in the other clusters. Cluster analysis is also called classification
analysis or numerical taxonomy. Cluster Analysis is also used for the following:
1. Segmenting the market: For ex: Consumers may be clustered on the basis of benefits
sought from the purchase of a product. Each cluster would consist of consumers who are
relatively homogenous in terms of the benefits they seek. This approach is called benefit
segmentation.
2. Understanding Buyer Behaviors: Cluster Analysis can be used to identify homogenous
groups of buyers. Then the buying behavior of each group can be examined separately.
3. Identifying new product opportunities: By clustering brands and products, competitive
sets within the market can be determined.
4. Selecting Test Markets
5. Reducing Data: Clustering analysis can be used as general data reduction tool to
develop clusters or subgroups of data that are more manageable than individual
observations.
The hierarchical clustering was performed on the sample data using SPSS. The sample
consisted of data from 159 respondents on 22 variables. The agglomeration schedule gives
the stage wise cluster formation. Based on the quantum jump in the coefficients, it was
decided to have 2 clusters. After the subjective decision to have two clusters, K-means
cluster analysis was carried out with number of clusters as 2. Through K-means cluster
analysis, the cluster membership of each cluster was identified. Also using the ANOVA table,
the parameters on which each cluster is different was identified. Using these parameters,
profile segmentation or descriptions based on their distinguishing characteristics were
formulated.
Based on the Cluster Analysis, the identified clusters and their characteristics were:
 Cluster 1 - Orthodox Sub Urban Individuals
 Cluster 2 - Modern Urban Individuals

Characteristics:
Orthodox Sub Urban Individuals
These people do not give branded products and the eating out lifestyle much importance
though they prefer premium quality and are ready to pay for high quality products. These
people prefer Indian cuisines and are indifferent between imported and domestic products.
These people not being brand conscious switch brands often and do not believe in showing
off their wealth. These people do not party out often.
Modern Urban Individuals
These modern urban individuals are classified with their attraction towards the Gen Next
culture being more attracted towards partying, branded products, holidaying, showing off
through new fashion trends and fads, preference of junk food over home cooked food etc.
These people spend a lot and are generally very brand loyal.

Hierarchal Clustering
Agglomeration Schedule
Stage Cluster Combined Coefficients
Stage Cluster First
Appears Next Stage
Cluster 1 Cluster 2 Cluster 1 Cluster 2 Cluster 1 Cluster 2
1 156 158 .000 0 0 36
2 25 153 .000 0 0 15
3 121 132 .000 0 0 6
4 93 129 .000 0 0 9
5 68 125 .000 0 0 10
6 8 121 .000 0 3 12
7 103 114 .000 0 0 8
8 15 103 .000 0 7 13
9 27 93 .000 0 4 14
10 40 68 .000 0 5 11
11 40 57 .000 10 0 71
12 8 53 .000 6 0 63
13 15 49 .000 8 0 34
14 27 44 .000 9 0 35
15 25 112 1.000 2 0 66
16 6 148 4.000 0 0 33
17 21 98 4.000 0 0 30
18 59 83 4.000 0 0 26
19 13 77 4.000 0 0 71
20 82 133 6.000 0 0 28
21 5 78 6.000 0 0 52
22 30 110 7.000 0 0 36
23 58 73 7.000 0 0 38
24 52 60 7.000 0 0 34
25 9 35 7.000 0 0 67
26 59 145 8.000 18 0 43
27 89 107 8.000 0 0 75
28 82 87 8.000 20 0 114
29 11 63 8.000 0 0 48
30 17 21 8.000 0 17 40
31 47 147 9.000 0 0 37
32 38 119 9.000 0 0 64
Case Processing Summarya,b
159 100.0 0 .0 159 100.0
Valid Missing Total
Cases
Squared Euclidean Distance useda.
Av erage Linkage (Between Groups)b.

33 6 97 9.000 16 0 42
34 15 52 9.500 13 24 44
35 27 155 10.000 14 0 45
36 30 156 10.500 22 1 61
37 47 127 10.500 31 0 74
38 58 96 10.500 23 0 47
39 130 159 11.000 0 0 113
40 17 157 11.000 30 0 53
41 76 142 11.000 0 0 73
42 6 19 11.000 33 0 48
43 59 136 11.333 26 0 54
44 15 33 11.500 34 0 47
45 27 139 11.600 35 0 84
46 100 101 12.000 0 0 106
47 15 58 12.000 44 38 61
48 6 11 12.750 42 29 67
49 10 135 13.000 0 0 123
50 46 134 13.000 0 0 103
51 48 67 13.000 0 0 78
52 5 56 13.000 21 0 81
53 17 111 13.250 40 0 65
54 59 94 13.500 43 0 64
55 92 140 14.000 0 0 104
56 42 138 14.000 0 0 120
57 106 117 14.000 0 0 74
58 12 105 14.000 0 0 97
59 3 95 14.000 0 0 108
60 1 36 14.000 0 0 96
61 15 30 14.350 47 36 75
62 34 108 15.000 0 0 79
63 8 29 15.000 12 0 104
64 38 59 15.100 32 54 80
65 17 151 15.200 53 0 94
66 25 70 15.333 15 0 130
67 6 9 15.333 48 25 72
68 7 123 16.000 0 0 101
69 4 43 16.000 0 0 109
70 22 41 16.000 0 0 78
71 13 40 16.000 19 11 99
72 6 152 16.250 67 0 89
73 76 131 16.500 41 0 88
74 47 106 16.667 37 57 89
75 15 89 16.714 61 27 81
76 137 144 17.000 0 0 93
77 54 109 17.000 0 0 125
78 22 48 17.000 70 51 111
79 34 104 17.500 62 0 108
80 38 116 17.714 64 0 90
81 5 15 17.854 52 75 88
82 2 154 18.000 0 0 125
83 81 146 18.000 0 0 124

84 27 143 18.000 45 0 98
85 32 99 18.000 0 0 130
86 69 85 18.000 0 0 119
87 18 31 18.000 0 0 112
88 5 76 18.456 81 73 90
89 6 47 18.622 72 74 98
90 5 38 18.693 88 80 94
91 79 141 19.000 0 0 118
92 37 51 19.000 0 0 110
93 75 137 19.500 0 76 136
94 5 17 19.711 90 65 100
95 23 149 20.000 0 0 127
96 1 102 20.000 60 0 109
97 12 39 20.000 58 0 112
98 6 27 20.245 89 84 105
99 13 20 21.333 71 0 118
100 5 120 21.833 94 0 103
101 7 113 22.000 68 0 123
102 16 62 22.000 0 0 142
103 5 46 22.284 100 50 105
104 8 92 22.600 63 55 113
105 5 6 22.834 103 98 114
106 72 100 23.000 0 46 117
107 55 61 23.000 0 0 148
108 3 34 23.000 59 79 116
109 1 4 23.000 96 69 115
110 37 128 23.500 92 0 120
111 22 126 24.750 78 0 116
112 12 18 25.000 97 87 133
113 8 130 25.071 104 39 121
114 5 82 25.261 105 28 115
115 1 5 26.241 109 114 121
116 3 22 26.600 108 111 122
117 72 118 26.667 106 0 127
118 13 79 26.786 99 91 129
119 69 122 27.000 86 0 131
120 37 42 27.667 110 56 131
121 1 8 27.846 115 113 122
122 1 3 29.009 121 116 126
123 7 10 29.167 101 49 133
124 81 124 30.000 83 0 144
125 2 54 30.000 82 77 134
126 1 14 30.218 122 0 129
127 23 72 30.750 95 117 140
128 45 86 33.000 0 0 149
129 1 13 33.196 126 118 134
130 25 32 33.500 66 85 155
131 37 69 33.733 120 119 138
132 24 66 34.000 0 0 146
133 7 12 34.600 123 112 141
134 1 2 34.616 129 125 136

135 90 150 35.000 0 0 142
136 1 75 35.469 134 93 137
137 1 80 36.144 136 0 138
138 1 37 36.752 137 131 141
139 64 115 37.000 0 0 145
140 23 71 38.000 127 0 143
141 1 7 39.712 138 133 143
142 16 90 40.000 102 135 150
143 1 23 41.772 141 140 144
144 1 81 44.267 143 124 146
145 64 65 44.500 139 0 151
146 1 24 45.075 144 132 147
147 1 26 46.941 146 0 148
148 1 55 47.206 147 107 149
149 1 45 47.732 148 128 150
150 1 16 49.321 149 142 151
151 1 64 49.815 150 145 152
152 1 74 51.673 151 0 153
153 1 91 58.649 152 0 154
154 1 28 60.919 153 0 155
155 1 25 61.600 154 130 157
156 50 88 65.000 0 0 158
157 1 84 65.378 155 0 158
158 1 50 121.385 157 156 0

K- Means Cluster Approach
Number of Clusters: 2
Number of Cases in each Cluster
Cluster 1 68.000
2 91.000
Valid 159.000
Missing .000
Final Cluster Centers
2 1
2 2
3 2
3 2
2 2
2 2
3 3
3 3
3 2
3 2
3 3
2 2
3 2
3 3
3 2
4 3
3 3
3 2
2 2
3 2
2 2
4 2
Health Conscious
Choosy
Eating out
BrandPreference
Self Decision
PremiumQuality
CreditCardPref er
Holiday
FastFoodCulture
Adv ertisements
Imported better
Inf ormedBuy er
BrandLoy al
HomeCountryPref
Television
CarsWealth
Gullible
FashionFollower
Indian cuisines better
Spendthrif t
Quality Ov erPrice
Partygoer
1 2
Cluster
Distances between Final Cluster Centers
3.131
3.131
Cluster
1
2
1 2

Cluster Membership:
Case
Number
Cluster Case
Number
Cluster Case
Number
Cluster Case
Number
Cluster
1 2 41 1 81 1 121 1
2 1 42 2 82 2 122 2
3 1 43 2 83 2 123 1
4 2 44 1 84 1 124 1
5 2 45 1 85 2 125 2
6 1 46 2 86 1 126 1
7 1 47 1 87 2 127 1
8 1 48 1 88 1 128 1
9 1 49 2 89 2 129 1
10 1 50 1 90 1 130 1
11 1 51 2 91 1 131 2
12 1 52 2 92 1 132 1
13 2 53 1 93 1 133 2
14 2 54 2 94 2 134 1
15 2 55 2 95 2 135 1
16 1 56 2 96 2 136 2
17 2 57 2 97 2 137 2
18 1 58 2 98 2 138 1
19 1 59 2 99 2 139 1
20 2 60 2 100 2 140 1
21 2 61 1 101 2 141 2
22 1 62 1 102 2 142 2
23 2 63 2 103 2 143 1
24 2 64 1 104 1 144 2
25 2 65 1 105 1 145 2
26 2 66 1 106 1 146 1
27 1 67 1 107 2 147 1
28 2 68 2 108 1 148 1
29 1 69 1 109 2 149 2
30 2 70 2 110 1 150 1
31 1 71 2 111 2 151 2
32 2 72 2 112 2 152 1
33 2 73 2 113 1 153 2
34 1 74 2 114 2 154 2
35 2 75 2 115 2 155 2
36 2 76 2 116 2 156 2
37 1 77 2 117 1 157 2
38 2 78 2 118 2 158 2
39 2 79 2 119 2 159 1
40 2 80 2 120 2

ANOVA
4.305 1 .508 157 8.476 .004
.448 1 .764 157 .587 .445
28.528 1 .796 157 35.859 .000
27.303 1 .614 157 44.464 .000
8.186 1 .575 157 14.232 .000
8.054 1 .562 157 14.339 .000
2.862 1 1.252 157 2.285 .133
8.583 1 .909 157 9.437 .003
18.863 1 1.113 157 16.942 .000
11.109 1 .779 157 14.262 .000
16.630 1 .913 157 18.219 .000
1.712 1 .700 157 2.445 .120
17.085 1 .743 157 22.992 .000
.005 1 1.278 157 .004 .948
13.674 1 .981 157 13.938 .000
27.769 1 .923 157 30.075 .000
2.223 1 .890 157 2.498 .116
44.045 1 .571 157 77.121 .000
3.195 1 .645 157 4.952 .027
42.494 1 .872 157 48.754 .000
13.944 1 .575 157 24.246 .000
80.525 1 .750 157 107.411 .000
Health Conscious
Choosy
Eating out
BrandPreference
Self Decision
PremiumQuality
CreditCardPref er
Holiday
FastFoodCulture
Adv ertisements
Imported better
Inf ormedBuyer
BrandLoy al
HomeCountryPref
Television
CarsWealth
Gullible
FashionFollower
Indian cuisines better
Spendthrif t
Quality Ov erPrice
Partygoer
Mean Square df
Cluster
Mean Square df
Error
F Sig.
The F tests should be used only for descriptiv e purposes because the clusters have been chosen to
maximize the dif ferences among cases in dif ferent clusters. The observed significance levels are not
corrected f or this and thus cannot be interpreted as tests of the hy pothesis that the cluster means are equal.

Multidimensional Scaling
Multidimensional scaling is a set of statistical technique which allows one to:
 Translate consumers preferences or perceptions towards products or brands into a
reduced number of dimensions (usually two or three)
 Represent them graphically into a perceptual map.
Here, the multidimensional scaling is used for the six brands of toothpastes to determine
how the Indian consumers perceive them. It also helped to find out how many dimensions
the consumers seem to be considering when they think of these brands.
Following is the DRAS response obtained from the 75 respondents:
Methodology Used- For each of the Attributes, the following matrix was drawn up.
Price
Respondents Colgate Close Up Pepsodent Babool Dabur Sensodyne
R1 2 1 3 4 5 6
R2 2 3 4 6 1 5
R3 1 2 3 4 5 6
. 2 3 4 6 5 1
. 1 3 2 4 5 6
. 3 1 2 5 4 6
R74 5 6 4 1 3 2
R75 6 4 5 1 3 2
The median ranking was taken for each brand and hence the table was prepared.
Colgate Close
Up
Pepsodent Babool Dabur Sensodyne
Price 2 3 3 4 5 6
Cleansning Power 1 2 3 4 6 6
Medicinal value 4 5 4 3 3 3
Lather 2 2 3 4 5 6
Calcium Content 1 3 3 4 5 6
Cavity Protection 2 3 3 4 5 6
breath
2 2 3 4 5 6
Anti Bacterial Protection 3 4 3 4 4 4
Flavors 2 2 3 4 5 6
Brand 1 3 3 4 5 6

The non attribute based Matrix of the 75 respondents taken.
Methodology Used: The distance matrix was obtained from each respondents. The rating
was averaged across respondents and a single distance matrix was constructed.
Resp. P-
S
P-
C
P-
CL
P-
D
P-
B
S-
C
S-
CL
S-
D
S-
B
C-
CL
C-
D
C-
B
CL-
D
CL-
B
D-
B
R1 6 4 4 6 7 8 8 6 5 1 7 7 6 6 3
R2 5 2 7 6 6 4 8 7 7 6 5 5 7 6 3
R3 3 4 6 4 5 8 9 3 4 4 5 4 7 6 3
. 6 3 4 9 3 5 9 9 5 5 7 1 8 5 9
. 7 6 3 7 8 7 6 6 8 5 6 7 7 8 3
R74 6 4 3 6 5 4 5 6 5 3 5 6 4 5 6
R75 6 2 6 4 8 4 8 7 4 7 3 9 7 6 3
Avg 6.8 3.6 4.65 6.5 6.9 6.3 6.77 5.5 5.3 4 5.8 5.8 6.08 6.15 3.2
7 4 5 7 7 6 7 6 5 4 6 6 6 6 3
P Pepsodent
S Sensodyne
Cl CloseUp
B Babool
D Dabur
C Colgate
Attribute 1 2 3 4 5 6
Price C Cl/P B D S
Cleansning Power C Cl P B D/S
Medicinal value B/D/S C/P Cl
Lather C/Cl P B D S
Calcium Content C Cl/P B D S
Cavity Protection C Cl/P B D S
breath C/Cl P B D S
Anti Bacterial Protection C/P Cl/B/D/S
Flavors C/Cl P B D S
Brand C Cl/P B D S

Multidimensional scale uses a non attribute based approach to understand raw consumer
perception.
Consolidated comparison matrix is made from the above data:
Pepsodent Synsodyne Colgate Close
up
Dabur Babul
Pepsodent 0 7 4 5 7 7
Synsodyne 7 0 6 7 6 5
Colgate 4 6 0 4 6 6
Close up 5 7 4 0 6 6
Dabur 7 6 6 6 0 3
Babul 7 5 6 6 3 0
Output:
No. of
Dimensions
K- Stress R square Value
1 .29250 0.74318
2 .08232 0.97228
For an acceptable MDS solution, Kruskal Stress < .15 and R square > .70,
No of dimension = 1 then Kruskal stress is not within acceptable range and R square is
within acceptable range.
No of dimension =2, value of Kruskal Stress is within acceptable range and R square
improved.
So, Number of dimensions used by consumer to evaluate the brand =2.
Stimulus Coordinates
Stimulus No. Stimulus Name Dimension
1 2
1 Pepsodent 1.6565 0.3836
2 Synsodyne -1.1552 1.3139
3 Colgate 0.8698 0.2095
4 Close up 1.0058 -0.7589
5 Dabur -1.1236 -0.8636
6 Babul -1.2533 -0.2846

3 Rules have been used to identify the constituent attributes:-
Top/Bottom :- In this case from the SPSS out put the Highest, Lowest score of the brand
was taken and was matched against each attribute.
2nd Top/2nd Bottom - In this case 2nd highest and 2nd lowest score of the brand was
taken and was matched against the attribute to see if that attribute belong to the Dimension.
Fifty Fifty Rules: - Median score was checked to determine the constituent of the
Dimensions.
Attributes
Dimension
1
Prevention
against Germs
Cleansing Power, Lather, Calcium
content, Prevention against bad
breath, Flavours
Dimension
2
Medicinal value Medicinal value

Two dimensional output:
Peps-
odent
Synsodyne
Colgate
Close up
Dabur
Babul
-1
-0.5
0
0.5
1
1.5
-1.5 -1 -0.5 0 0.5 1 1.5 2
MDS
DECAY
PROTECTION
MEDICINAL
VALUE

Analysis
Through our analysis in this report, we have figured out various important factors through
which marketers can target various consumer segments for their brands of toothpastes.
With the help of chi square analysis, it was found that with the change in demographic
factors, the various consumer patterns for toothpastes also change. The following results
were found:
 Young people prefer gel based toothpastes while older people prefer pastes.
 With age, the preference for brand also change as younger people relate themselves
with brands like Close Up and Pepsodent while older people relate themselves with
brands like Dabur etc.
 With increase in age, the preference for the point of purchase also changes.
 According to occupation, the frequency at which they change the toothpastes also
changes. While students do not experiment much because of lower disposable
income, earning people tend to experiment more with toothpastes and hence
become frequent switchers.
 Males are found to be more brand loyal than females.
With the help of factor analysis, we found out the various factors that a consumer consider
while buying toothpaste. These factors are:
 Sales Promotion: The various offers given by companies like extra toothpaste,
discounts, freebies, promotional packs have a significant impact on the buying
behaviour.
 Prevention Against Germs: The protection provided by toothpaste against cavity
and bad breath is considered very important by consumers
 Value For Money: The brand and the price at which the brand is offered is also a
major influence in the buying decision.
 Medicinal Content: The medicinal value provided by the toothpaste along with the
calcium content is considered an important feature for buying toothpastes.
 Functions: The basic functions provided by toothpastes like cleansing, whitening,
freshness etc also influence consumers while buying their toothpastes.
Based on these 5 factors, 10 perceptual maps were drawn to see how the various attributes
are associated with each other and also to find the nature of association between the
attributes.
Then, multi-dimensional scaling was used based on the responses given by two similar set
of respondents. One set of respondents were measured on the basis of non-attribute based
questions while the other set of respondents were measured on the basis of attribute based
questions. With the analysis, we identified two major dimensions i.e. Prevention Against
Germs and Medicinal Content on which consumers perceive each brand. The perceptual
map drawn on the basis of this technique helped to identify the market gap at which
marketers can introduce their new toothpastes.

Finally, Cluster Analysis was conducted through which the respondents were put into two
clusters viz. Orthodox Sub Urban Individuals and Modern Urban Individuals. Orthodox
individuals usually do not give much importance to brands and the western way of living
while the modern individuals are more brand conscious and have a influence of western
culture in their lifestyle.
Hence through these analysis, marketers can get ample information about the target groups
of consumers, their brand positioning and also the factors which are sought out before
buying a toothpaste.

Limitations
 Research was conducted within a constrained sample of respondents mainly the
students of various colleges.
 Respondents were largely from big cities which biased the results towards the
consumer behaviour of the urban areas.
 Unequal distribution of both the genders.
 Unequal distribution of the various age groups.
 The chances of respondents filling the questionnaire hastily are high.
Conclusion
This project was aimed to understand the consumer buying behavior for toothpastes in the
age group 21-30. According to the findings of the project, we can confer that consumers are
more enticed by factors like sales promotion, prevention against germs, value for money,
medicinal content and functions. Marketers hold a huge potential to target such opportunities
and to cash in all what they can attain.
As a researcher, this project was a great platform to learn the techniques and apply them in
a marketing research project.

KUMANDAN

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