Marketing Research Project- Toothpaste

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………………………………………….. 6 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

http://www.colgate.co.in/app/Colgate/IN/OralCare/ToothPastes/DentalCream.cvsp

http://www.colgate.co.in/app/Colgate/IN/OralCare/ToothPastes/Total12.cvsp

http://www.colgate.co.in/app/ColgateSensitiveNew/IN/HomePage.cvsp

http://www.colgate.co.in/app/Colgate/IN/OralCare/ToothPastes/ColgateMaxFreshGel/HomePage.cvsp

http://www.colgate.co.in/app/Colgate/IN/OralCare/ToothPastes/KidsToothPaste.cvsp

http://www.colgate.co.in/app/Colgate/IN/OralCare/ToothPastes/FreshEnergyGel.cvsp

http://www.colgate.co.in/app/Colgate/IN/OralCare/ToothPastes/ColgateHerbal.cvsp

http://www.colgate.co.in/app/Colgate/IN/OralCare/ToothPastes/Advanced_Whitening.cvsp

http://www.colgate.co.in/app/Colgate/IN/OralCare/ToothPastes/CibacaTop.cvsp

http://www.colgate.co.in/app/Colgate/IN/OralCare/ToothPastes/ColgateActiveSalt.cvsp

http://www.colgate.co.in/app/Colgate/IN/OralCare/ToothPastes/ColgateMaxwhite.cvsp

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.


13. The brand of the toothpaste is important.


14. I look for what medicinal value the toothpaste has to offer.


15. Toothpaste which does not lather does not provide satisfaction.


16. My toothpaste should provide me with optimum quantity of calcium content.


17. I like experimenting with various flavours that toothpaste companies have to

offer.


18. My toothpaste should protect me against cavity.


19. The best toothpaste is which prevent me against bad breath.


20. I look for new features promised by the toothpaste every time I buy my

toothpaste.


21. I prefer Indian toothpastes over imported toothpastes.


22. I buy combo packs rather than single units in order to save money.


23. I prefer toothpastes which have offers like free toothbrush, extra quantity,

freebies etc.


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


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



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.


12. The cleansing power of the toothpaste matters a lot.


13. The brand of the toothpaste is important.


14. I look for what medicinal value the toothpaste has to offer.


15. Toothpaste which does not lather does not provide satisfaction.


16. My toothpaste should provide me with optimum quantity of calcium content.


17. I like experimenting with various flavours that toothpaste companies have to

offer.


18. My toothpaste should protect me against cavity.


19. The best toothpaste is which prevent me against bad breath.


20. I look for new features promised by the toothpaste every time I buy my

toothpaste.


21. I prefer Indian toothpastes over imported toothpastes.


22. I buy combo packs rather than single units in order to save money.


23. I prefer toothpastes which have offers like free toothbrush, extra quantity,

freebies etc.


24. Rank these brands according to the features

Feartures/Brands Colgate

Close Up

Pepsodent

Babool Dabur

Sensodyne

Price

Cleansning Power

Medicinal value

Lather

Calcium Content

Cavity Protection



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

West48%

East17%

North26%

South9%

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

Male66%

Female34%

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 month53%Every two

months38%

Every three months

7%

Not very

often2%

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

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 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

Toothpaste

Sensodyne 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

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 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


Region

West 34 17 16 2 0 1 1 5 76

East 13 4 6 1 0 3 0 0 27

North

20 11 7 1 1 1 0 1 42

South

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

Toothpaste


Occupation

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


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

Gender

Male 45 25 20 4 1 5 0 5 105

Female

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

Dif f 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

Dif f 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 5C2 i.e. total ten maps are drawn for the factor combinations.

Sales Promotion Vs. Prevention Against Germs

Sales Promotion


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


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


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

Telev ision

CarsWealth

Gullible

FashionFollower

Indian cuisines bet ter

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

Telev ision

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 descript iv e purposes because the clusters have been chosen to

maximize the dif ferences among cases in dif ferent clusters. The observed signif icance 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


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

Prevention against bad 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 upDabur

Babul

-1

-0.5

0

0.5

1

1.5

-1.5 -1 -0.5 0 0.5 1 1.5 2

MDS

DECAYPROTECTION

MEDICINALVALUE

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.

Appendix

Marketing Research Project- Toothpaste

Documents

Transcript of Marketing Research Project- Toothpaste