Marketing Research: Toothpaste Industry*

Marketing Research: Toothpaste Industry*

Ms. Harshleen Kaur Sethi

Barclays Shared Services Pvt. Ltd.

New Delhi, Delhi 110096

Abstract – One of the fastest growing segments in the FMCG sector has been the toothpaste segment. As per Euromonitor India, the toothpaste industry in India is over Rs.6000 crore in 2013. The industry revenues grew at 9.1% as compared to the previous year. The major players in the industry are Colgate and Palmolive with their time tested brand Colgate that holds close to 56% market share. Over the years, Colgate has been able to develop strong brand equity (Jain, Vipul & Jain, 2012). The trailer of the industry is HUL with popular brands Pepsodent and Colgate. They collectively hold close to 28% market share and saw a growth of 15% in revenues year on year. Other players include Dabur Red, Cibaca, Meswak, Sensodyne, Babool and Oral-B. However, as per analysts the segment is turning out to be one of the most competitive segments in FMCG space. GSK with Sensodyne recently introduced Sensitivity Protection as an entirely new feature in the minds of Indian customer and gaining a 0.8% share of the market in less than a year. Similarly FMCG behemoth P&G also threw its hat in the fray by extending its dental care brand Oral-B to toothpaste segment. The brand emphasis of Whiteness is its central USP. The segment has also seen aggressiveness from the existent players when HUL introduced a directed campaign at Colgate to emphasis its superiority with implicit reference to Colgate.At this point, the importance of marketing research in the industry increases several folds. A comprehensive marketing research will be the only tool that can provide manufacturers proximity to customers to both new brands, who need to identify in roads to the market and for existing brands, who need to up their ante against the onslaught of competitors.

Keywords Toothpaste Industry, demographic, usage, attitude

1. INTRODUCTION

   Numerous product launches in the oral care market in general, are expansions of recognized brands. Marketers realize that there is more demand for products that provide whitening and odour-fighting benefits. Taking advantage of recognized brand names is one strategy through which oral care marketers can bring innovative and novel products into the market. (Sriram, Dr. S & Pugalanthi, Dr. S., July 2013) The project revolves around the extensive application of marketing research techniques to understand the usage, attitude and preference of Indian consumers towards toothpaste, a very generic and routine product used by people of all age groups and demographics and with a very low involvement.

   Customer satisfaction refers to the extent to which customers are happy with the product and services provided by a business. (Kavitha, Dr. T. N. R. & Vanitha, www.iosrjournals.org) Customer expectations, usage, attitude and brand comparison were studied for the toothpaste category, wherein the primary benefits that the consumer seeks while using a particular brand was analyzed with its

   purchasing pattern and behavior, and the core triggers to purchase their favorite brand. The effect of demographic factors like age, gender, occupation, income level was observed with respect to the purchase of toothpaste. Switching behavior between various brands was analyzed with the help of factors like offering attractive discounts, use of samples, price points and availability.

   Also, a typical customer was classified based on the demographic and lifestyle factors using Cluster Analysis. Factor Analysis helped us in identifying three major factors of place, price and promotion out of all the variables considered. Using Discriminant Analysis on different variables like teeth whitening, gum problems, lather, long- lasting freshness, tooth decay etc., a model based on attributes to predict group membership was also analyzed, though the model was found to be insignificant. Techniques like Perceptual Mapping were used to assess the relevance of branding campaigns and promotional activities on the purchase pattern. Brands taken into consideration were Colgate, Pepsodent, Close Up, Dabur Red and Sensodyne. As a result of which, Colgate was found out to be the most preferable and favored brand amongst the others. The toothpastes like Close-up, Colgate and Pepsodent gives emphasis upon the higher class people as well as self esteemed people. So, people using these brands feel higher in status and their performance is more psychological. (Panigrahi, Anita Kumari, April, 2015)

   Different brands have different marketing strategies; some focus on the taste and flavor attributes and some lay their focus on dental care exclusively. Based on our analysis, we found Colgate as the market leader and it should introduce new variants like its competitors have been doing. Brands like Pepsodent have been attacking its competition Colgate with its advertisements and a new variant Pepsodent Attack. As a result, marketers should focus on factors like whiteness and sensitivity, infact a total care as a whole, during their brand communication to its customers and association with Dental Professional Bodies can also be helpful.

   The purchasing pattern says that customers are purchasing toothpastes from super markets and Kirana shops, thus these should be critical locations for the sales staff. Majorly, the product is a planned purchased or through monthly ration.

   Even the advertisement can be an important instrument that can create a clear cut difference in the mind of consumer (Singh, Sukhbir, 2017), hence there is an discrete effect of toothpaste advertisement on the customers.

2. OBJECTIVES The objectives of this research paper are:

   1. To understand the usage and preference of Indian consumers towards toothpaste category products.

   2. Consumer Expectations

      1. Primary benefits that a consumer associates with a toothpaste

   3. Usages and Attitude

      1. Various usage patterns linked with toothpaste

      2. Purchase behavior connected with toothpaste

      3. Affect of demographic factors on the purchase of toothpaste

      4. Analyzing the switching behavior

      5. Identifying the various parameters that affect the purchase behavior

      6. Classifying the customers based on demographic and lifestyle parameters

      7. Develop a model based on attributes to predict group membership

   4. Brand Awareness and Comparison

      1. Feature specific association with brands

      2. Effect of branding campaigns and promotional schemes on usage patterns

3. RESEARCH METHODOLOGY

   Due to a constraint on the cost and time aspects of the research a convenience sampling approach was employed. The survey was distributed to 83 respondents that were spread across the varied demographic profile. The questionnaire was coded on Qualtrics a professional marketing research platform and was distributed to respondents primarily via email.

4. OVERVIEW DEMOGRAPHIC PROFILE

   1. CONSUMER EXPECTATIONS

      • Primary benefits that a consumer associates with a toothpaste

        (One-Sample t-test)

        The objective is to determine which product benefits of toothpaste are most important to customers.

        The mean values were found out for each attribute. Higher the value, more important is the product benefit to customers.

        Through a one-sample t-test, the significance of mean was determined.

        H0: Mean value of Product Benefit=3 H1: Men value of Product Benefit>3

        Significance level=0.05

        This is a one-tailed t-test, so p-value is divided by 2.

        One-Sample t-test
        Rate your agreement/disagreement with the statements indicated below on a five point scale:	N	Mean	Sig. (2- tailed)	Sig. (1- tailed)
        Prevention from tooth decay is most important	83	4.47	.000	.000
        Prevention from gum problems is not important	83	3.84	.000	.000
        Toothpaste should provide teeth whitening	83	4.13	.000	.000
        Medicinal value of the toothpaste does not matter	83	3.69	.000	.000
        Toothpaste that does not offer lather does not provide satisfaction	83	3.35	.008	0.004
        I look at the ingredient (vegetarian/non vegetarian) while buying a toothpaste	83	3.07	.666	0.333
        The best toothpaste is which prevents from bad breath and provides long lasting freshness	83	4.16	.000	0
        Toothpaste should taste good	83	3.82	.000	0
        I do not look for new features promised by the toothpaste every time I buy toothpaste	83	2.87	.235	0.1175

        When p-value<0.05, H0 is rejected implying the corresponding product benefit mean is significant.

        From the above table significant attributes in the order of importance are identified:

        1. Prevention from tooth decay

        2. Prevents from bad breath and provides long lasting freshness

        3. Provide teeth whitening

        4. Prevention from gum problems

        5. Taste good

        6. Medicinal value

        7. Lather

        When p-value>0.05, there is not enough evidence to reject H0 implying the corresponding product benefit mean is insignificant.

        From the above table insignificant attributes are identified:

        1. Ingredient (vegetarian/non vegetarian)

        2. New features promised by the toothpaste

        Demographic Variables vs Primary Benefits (Independent sample t-test)

        The objective is to understand the effect of demographic variables on average importance of product benefits.

        The mean values were found out for each variable. Higher the value, more important is the product benefit to that category of variable.

        Gender

        Through an independent sample t-test, the significance of difference in mean was determined.

        H0: Mean importance to Males = Mean importance to Females

        H1: Mean importance to Males Mean importance to Females

        Significance level=0.05

        Descriptives
        Rate your agreement/disagreement with the statements indicated below on a five point scale:	Gender	N	Mean
        Prevention from tooth decay is most important	Male	48	4.35
        	Female	35	4.63
        Prevention from gum problems is not important	Male	48	3.79
        	Female	35	3.91
        Toothpaste should provide teeth whitening	Male	48	4.31
        	Female	35	3.89
        Medicinal value of the toothpaste does not matter	Male	48	3.67
        	Female	35	3.71
        Toothpaste that does not offer lather does not provide satisfaction	Male	48	3.46
        	Female	35	3.20
        I look at the ingredient ( vegetarian/non vegetarian) while buying a toothpaste	Male	48	2.88
        	Female	35	3.34
        The best toothpaste is which prevents from bad breath and provides long lasting freshness	Male	48	4.06
        	Female	35	4.29
        Toothpaste should taste good	Male	48	3.69
        	Female	35	4.00
        I do not look for new features promised by the toothpaste every time I buy toothpaste	Male	48	2.88
        	Female	35	2.86
        Independent Samples Test
        Rate your agreement/disagreement with the statements indicated below on a five point scale:	Levene's Test for Equality of Variances		t-test for Equality of Means
        		Sig.	Sig. (2-tailed)
        Prevention from tooth decay is most important	Equal variances assumed	.933	.072
        	Equal variances not assumed		.084
        Prevention from gum problems is not important	Equal variances assumed	.692	.670
        	Equal variances not assumed		.672
        Toothpaste should provide teeth whitening	Equal variances assumed	.913	.011
        	Equal variances not assumed		.016

        	Equal
        	variances	.573	.837
        Medicinal value of the toothpaste does not matter	assumed
        	Equal variances not		.835
        	assumed
        	Equal
        	variances	.92	.321
        Toothpaste that does not offer	assumed
        lather does not provide	Equal
        satisfaction	variances not		.323
        	assumed
        	Equal
        	variances	.686	.168
        I look at the ingredient (	assumed
        vegetarian/non vegetarian)	Equal
        while buying a toothpaste	variances not		.171
        	assumed
        	Equal
        The best toothpaste is which prevents from bad breath and provides long lasting freshness	variances assumed	.396	.213
        	Equal variances not		.200
        	assumed
        	Equal
        	variances	.031	.124
        	assumed
        Toothpaste should taste good	Equal
        	variances not		.113
        	assumed
        	Equal
        	variances	.574	.937
        I do not look for new features	assumed
        promised by the toothpaste	Equal
        every time I buy toothpaste	variances not		.937
        	assumed

        Here, p-value corresponding to equality of variances is insignificant (>0.05). So, the variances of two groups are not equal.

        When p-value<0.05, H0 is rejected implying there is difference in the preference of corresponding benefit among males and females.

        From the above table only 1 significant factor was identified

        1. toothpaste should provide teeth whitening. It is more important for males than females, as shown by mean values.

           When p-value>0.05, there is not enough evidence to reject null hypothesis. This means the difference in product benefit preference can be attributed to chance and not to gender. Differences in mean for all other factors were insignificant.

           Occupation (ANOVA)

           Through ANOVA, the significance of difference in mean was determined.

           H0: All means are equal

           H1: At least two means are not equal Significance level=0.05

           ANOVA
           Rate your agreement/disagreement with the statements indicated below on a five point scale-		Sum of Squares	df	Mean Square	F	Sig.
           Prevention from tooth decay is most important	Between Groups	1.118	4	.279	.580	.678
           	Within Groups	37.557	78	.481
           	Total	38.675	82
           Prevention from gum problems is not important	Between Groups	22.927	4	5.732	3.990	.005
           	Within Groups	112.037	78	1.436
           	Total	134.964	82
           Toothpaste should provide teeth whitening	Between Groups	3.737	4	.934	1.663	.167
           	Within Groups	43.806	78	.562
           	Total	47.542	82
           Medicinal value of the toothpaste does not matter	Between Groups	11.008	4	2.752	2.793	.032
           	Within Groups	76.848	78	.985
           	Total	87.855	82
           Toothpaste that does not offer lather does not provide satisfaction	Between Groups	2.802	4	.701	.506	.732
           	Within Groups	108.065	78	1.385
           	Total	110.867	82
           I look at the ingredient ( vegetarian/non vegetarian) while buying a toothpaste	Between Groups	53.226	4	13.307	7.613	.000
           	Within Groups	136.340	78	1.748
           	Total	189.566	82
           which prevents from bad breath and	Between Groups	4.457	4	1.114	1.792	.139

           provides long lasting freshness	Within Groups	48.507	78	.622
           	Total	52.964	82
           Toothpaste should taste good	Between Groups	2.174	4	.544	.641	.635
           	Within Groups	66.115	78	.848
           	Total	68.289	82
           I do not look for new features promised by the toothpaste every time I buy toothpaste	Between Groups	2.520	4 /td>	.630	.606	.659
           	Within Groups	81.023	78	1.039
           	Total	83.542	82

           When p-value<0.05, H0 is rejected implying there is difference in the preference of corresponding benefit among different age groups.

           From the above table following significant factors were identified:

           1. Prevention from gum problems

           2. Medicinal value of the toothpaste

           3. Ingredient (vegetarian/non vegetarian)

        DESCRIPTIVES
        Rate your agreement/disagreement with the statements indicated below on a five point scale-		N	Mean
        Prevention from gum problems is not important	a) Professional	17	4.35
        	b) Business	12	3.25
        	c) Student	42	4.05
        	d) Homemaker	9	3.33
        	e) Retired	3	2.00
        	Total	83	3.84
        Medicinal value of the toothpaste does not matter	a) Professional	17	4.18
        	b) Business	12	3.42
        	c) Student	42	3.62
        	d) Homemaker	9	3.89
        	e) Retired	3	2.33
        	Total	83	3.69
        I look at the ingredient ( vegetarian/non vegetarian) while buying a toothpaste	a) Professional	17	2.59
        	b) Business	12	4.33
        	c) Student	42	2.67
        	d)Homemaker	9	4.56
        	e) Retired	3	2.00
        	Total	83	3.07

        It is most important for those respondents where mean>3 in that occupation in decreasing order:

        BENEFIT	CATEGORY
        Medicinal value of the toothpaste
        Ingredient (vegetarian/non vegetarian)
        Prevention from gum problems

        1. Professional

        2. Homemaker

        3. Student

        4. Business

        1. Homemaker

        2. Business

        1. Professional

        2. Student

        3. Homemaker

        4. Business

        Post- Hoc Analysis

        Difference of mean importance of benefits is significantly high for these pairs of variables wherever the p-value<0.05

        Multiple Comparisons
        TukeyHSD
        Dependent Variable	(I) Occupation	(J) Occupation	Mean Difference (I-J)	Std. Error	Sig.	95% Confidence Interval
        						Lower Bound	Upper Bound
        Prevention from gum problems is not important	a) Professional	b) Business	1.103	.452	.115	-.16	2.36
        		c)Student	.305	.345	.901	-.66	1.27
        		d)Homemaker	1.020	.494	.246	-.36	2.40
        		e) Retired	2.353*	.751	.020	.26	4.45
        	b) Business	a)Professional	-1.103	.452	.115	-2.36	.16
        		c)Student	-.798	.392	.260	-1.89	.30
        		d)Homemaker	-.083	.528	1.000	-1.56	1.39
        		e) Retired	1.250	.774	.492	-.91	3.41
        	c) Student	a)Professional	-.305	.345	.901	-1.27	.66
        		b)Business	.798	.392	.260	-.30	1.89
        		d)Homemaker	.714	.440	.488	-.52	1.94
        		e) Retired	2.048*	.716	.042	.05	4.05
        	d)Homemaker	a)Professional	-1.020	.494	.246	-2.40	.36
        		b)Business	.083	.528	1.000	-1.39	1.56
        		c)Student	-.714	.440	.488	-1.94	.52
        		e) Retired	1.333	.799	.459	-.90	3.56
        	e) Retired	a)Professional	-2.353*	.751	.020	-4.45	-.26
        		b)Business	-1.250	.774	.492	-3.41	.91
        		c)Student	-2.048*	.716	.042	-4.05	-.05
        		d)Homemaker	-1.333	.799	.459	-3.56	.90
        Medicinal value of the toothpaste does not matter	a)Professional	b)Business	.760	.374	.261	-.29	1.80
        		c)Student	.557	.285	.298	-.24	1.35
        		d)Homemaker	.288	.409	.955	-.86	1.43
        		e) Retired	1.843*	.622	.032	.11	3.58
        	b)Business	a)Professional	-.760	.374	.261	-1.80	.29
        		c)Student	-.202	.325	.971	-1.11	.70
        		d)Homemaker	-.472	.438	.817	-1.69	.75
        		e) Retired	1.083	.641	.446	-.71	2.87
        	c) Student	a)Professional	-.557	.285	.298	-1.35	.24
        		b)Business	.202	.325	.971	-.70	1.11
        		d)Homemaker	-.270	.365	.946	-1.29	.75
        		e) Retired	1.286	.593	.203	-.37	2.94
        	d)Homemaker	a)Professional	-.288	.409	.955	-1.43	.86
        		b)Business	.472	.438	.817	-.75	1.69
        		c)Student	.270	.365	.946	-.75	1.29
        		e) Retired	1.556	.662	.140	-.29	3.40

        		b)Business	-1.745*	.498	.007	-3.14	-.35
        	a)Professional	c)Student	-.078	.380	1.000	-1.14	.98
        		d)Homemaker	-1.967*	.545	.005	-3.49	-.45
        		e) Retired	.588	.828	.954	-1.72	2.90
        		a)Professional	1.745*	.498	.007	.35	3.14
        	b)Business	c) Student	1.667*	.433	.002	.46	2.88
        		d)Homemaker	-.222	.583	.995	-1.85	1.41
        		e) Retired	2.333	.853	.058	-.05	4.72
        I look at the ingredient		a)Professional	.078	.380	1.000	-.98	1.14
        (vegetarian/non vegetarian) while	c) Student	b)Business	-1.667*	.433	.002	-2.88	-.46
        		d)Homemaker	-1.889*	.486	.002	-3.25	-.53
        buying a toothpaste		e) Retired	.667	.790	.916	-1.54	2.87
        		a)Professional	1.967*	.545	.005	.45	3.49
        	d)Homemaker	b)Business	.222	.583	.995	-1.41	1.85
        		c) Student	1.889*	.486	.002	.53	3.25
        		e) Retired	2.556*	.881	.038	.09	5.02
        		a)Professional	-.588	.828	.954	-2.90	1.72
        	e) Retired	b)Business	-2.333	.853	.058	-4.72	.05
        		c) Student	-.667	.790	.916	-2.87	1.54
        		d)Homemaker	-2.556*	.881	.038	-5.02	-.09
        *. The mean difference is significant at the 0.05 level.

        When between groups p-value>0.05, there is not enough evidence to reject null hypothesis. This means the difference in product benefit preference can be attributed to chance and not to age. Differences in mean for all other attributes were insignificant.

        Similar Independent t-test/ANOVA analysis was conducted for all demographic variables. Following is the summary of the results:

        S.No.	Demographic Variable	Significant Benefits (p- value<0.05)	Relative Importance in categories (Mean values >3 in decreasing order)	Post-Hoc Analysis(p- value<.05)
        1.	Gender	Teeth Whitening		N.A.
        2.	Age	Prevents from bad breath and provides long lasting freshness	3. 16-25 4. 26-35 5. <16 6. >=46 7. 36-45	N.A.
        3.	Monthly Household income (Rs.)	Prevention from tooth decay is most important	1. 50,001-75,000 2. 75,001-1,00,000 3. <25,000 4. 25,000-50,000 5. >1,00,000	50,001-75,000 and >1,00,000
        4.	Occupation	Medicinal value of the toothpaste		Professional-Retired
        		Ingredient (vegetarian/non vegetarian)
        		Prevention from gum problems		Retired

        1. Female

        2. Male

        1. Professional

        2. Homemaker

        3. Student

        4. Business

        1. Homemaker

        2. Business

        1. Professional- Business

        2. Professional- Homemaker

        3. Business- Student

        4. Homemaker- Retired

        5. Student- Homemaker

        1. Professional

        2. Student

        3. Homemaker

        4. Business

        1. Professional

        2. Student-Retired

   2. USAGE AND ATTITUDE

      • Various usage patterns linked with toothpaste (Frequency Tables)

        Which brand of toothpaste do you use?

        		Frequency	Percent	p>Valid Percent	Cumulative
        	Colgate (or one of its	36 18 11 9 1 5 2 1 83	43.4 21.7 13.3 10.8 1.2 6.0 2.4 1.2 100.0	43.4 21.7 13.3 10.8 1.2 6.0 2.4 1.2 100.0	43.4 65.1 78.3 89.2 90.4 96.4 98.8 100.0
        	sub-brands)
        	Pepsodent (or one of
        	its sub-brands)
        	Close Up
        Valid	Dabur Red
        	Oral-B
        	Sensodyne
        	Meswak
        	Other (please
        	specify)
        	Total

        Interpretation

        43% respondents use Colgate toothpaste, hence, it is the most used toothpaste among the given brands. Pepsodent with approximately 20 % respondents is the second most used brand. This is followed by Close- Up, Dabur Red and Sensodyne in the stated order.

        Which variant/type of the brand of toothpaste do you use?

        		Frequency	Percent	Valid Percent	Cumulative
        	Total care	39	47.0	47.0	47.0
        	Salty	5	6.0	6.0	53.0
        	Herbal	9	10.8	10.8	63.9
        Valid	Sensitive	10	12.0	12.0	75.9
        	Whiteness	14	16.9	16.9	92.8
        	Other	6	7.2	7.2	100.0
        	Total	83	100.0	100.0

        Interpretation:

        With 47% of the respondents using Total care as a toothpaste variant, it is the most used one. This is followed by Whiteness (17%) and Sensitive (12%) type of toothpastes.

        For how long have been you using the brand that you have indicated previously in Q1?

        	Frequency	Percent	Valid Percent	Cumulative Percent
        Less than one year	20	24.1	24.1	24.1
        More than one year and less than 5 years	27	32.5	32.5	56.6
        Valid More than 5 years and less than 10 years	17	20.5	20.5	77.1
        More than 10 years	19	22.9	22.9	100.0
        Total	83	100.0	100.0

        Interpretation:

        Almost 45 % percent of the respondents have been using the same toothpaste for the last 5 years or more. This can show that toothpaste being a fairly low involvement product, a large number of people do not feel like changing it and continue using it.

        How often do you use toothpaste in a day?

        	Frequency	Percent	Valid Percent	Cumulative Percent
        Once Twice Valid After every meal Total	34 42 7 83	41.0 50.6 8.4 100.0	41.0 50.6 8.4 100.0	41.0 91.6 100.0

        Interpretation:

        50.6% of the respondents use toothpaste twice a day and 41

        % use it once a day. There are very few people (8.4 %) who use toothpaste after every meal. This shows that majority use toothpaste as a daily morning and night routine.

        • Purchase behavior connected with toothpaste

          Where do you buy your toothpaste from (select many)?-Supermarket (Like Big Bazaar, Reliance Fresh)

          		Frequency	Percent	Valid Percent	Cumulative
          Valid	yes	50	60.2	100.0	100.0
          Missing	System	33	39.8
          Total		83	100.0

          Where do you buy your toothpaste from (select many)?-Medical shop/ Chemist

          	Frequency	Percent	Valid Percent	Cumulative	Percent
          Valid	yes	24	28.9	100.0	100.0
          Missin g	System	59	71.1
          Total		83	100.0

          Interpretation:

          60% of the respondents bought their toothpaste from supermarkets like, Big Bazaar, Reliance Fresh etc. Almost 58% of the respondents bought their toothpaste from Kirana shops and 29% of the respondents bought their toothpaste from Medical shops/ chemists. Thus more number of toothpaste purchases was from Supermarkets.

          How do you purchase your toothpaste?

          		Frequency	Percent	Valid Percent	Cumulative Percent
          	Ration	24	28.9	28.9	28.9
          Valid	Planned Purchase Impulse Buy	44 15	53.0 18.1	53.0 18.1	81.9 100.0
          	Total	83	100.0	100.0

          Where do you buy your toothpaste from (select many)?- Kirana shop

          		Frequency	Percent	Valid Percent	Cumulative Percent
          Valid	yes	48	57.8	100.0	100.0
          Missing	System	35	42.2
          Total		83	100.0

          Interpretation:

          More than half of the total respondents (53 %) purchase toothpaste as a part of their planned decision. Fewer people (only 18 %) believe that they purchase it as an impulse buying decision. Also, about 28.9 % people also buy as a part of their monthly ration.

          Who all influence your purchase decision while buying toothpaste? (Select many)-Friends

          	Frequency	Percent	Valid Percent	Cumulative	Percent
          Valid	yes	14	16.9	100.0	100.0
          Missing	System	69	83.1
          Total		83	100.0

          Who all influence your purchase decision while buying toothpaste? (Select many)-Parents

          Who all influence your purchase decision while buying toothpaste? (Select many)-Individual Decision

          	Frequency	Percent	Valid Percent	Cumulative	Percent
          Valid	yes	52	62.7	100.0	100.0
          Missing	System	31	37.3
          Total		83	100.0

          Who all influence your purchase decision while buying toothpaste? (Select many)-Dentist

          	Frequency	Percent	Valid Percent	Cumulative	Percent
          Valid	yes	38	45.8	100.0	100.0
          Missing	System	45	54.2
          Total		83	100.0

          	Frequency	Percent	Valid Percent	Cumulative	Percent
          Valid	yes	36	43.4	100.0	100.0
          Missing	System	47	56.6
          Total		83	100.0

          	Frequency	Percent	Valid Percent	Cumulative	Percent
          Valid	yes	11	13.3	100.0	100.0
          Missing	System	72	86.7
          Total		83	100.0

          Who all influence your purchase decision while buying toothpaste? (Select many)- Shopkeeper/Salesperson

          Who all influence your purchase decision while buying toothpaste? (Select many)-Spouse

          	Frequency	Percent	Valid Percent	Cumulative	Percent
          Valid	yes	11	13.3	100.0	100.0
          Missing	System	72	86.7
          Total		83	100.0

          Who all influence your purchase decision while buying toothpaste? (Select many)-Kids

          	Frequency	Percent	Valid Percent	Cumulative	Percent
          Valid	yes	1	1.2	100.0	100.0
          Missing	System	82	98.8
          Total		83	100.0

          Who all influence your purchase decision while buying toothpaste? (Select many)-Others(Please Specify)

          Interpretation:

          For more than 60% respondents toothpaste buying is an individual decision. Next, 45% respondents purchase decision was influenced by their dentist. Also, 43% of respondents were influenced by their parents while buying toothpaste.

          	Frequency	Percent	Valid Percent	Cumulative	Percent
          Valid	yes	12	14.5	100.0	100.0
          Missing	System	71	85.5
          Total		83	100.0

          How much are you willing to spend on a regular size (150 gm) of toothpaste? (Rs.)

          			Frequency	Percent	Valid Percent	Cumulative
          	a)<50		13	15.7	15.7	15.7
          	b)	50-75	46	55.4	55.4	71.1
          Valid	c)	76-100	20	24.1	24.1	95.2
          	d) >100		4	4.8	4.8	100.0
          	Total		83	100.0	100.0

          Interpretation:

          Almost 70% respondents are willing to spend less than Rs.75 on a regular size (150gm) of toothpaste. Only 5% respondents are willing to spend more than Rs.100 for a regular size pack of toothpaste.

          Affect of demographic factors on the purchase of toothpaste

          (Crosstabs) Gender

          		Frequenc y	Percent	Valid Percent	Cumulative Percent
          	Male	48	57.8	57.8	57.8
          Valid	Female	35	42.2	42.2	100.0
          	Total	83	100.0	100.0

          Interpretation:

          Out of all the respondents, 57.8% were males and 42.2% were females.

          Age group

          		Frequenc y	Percent	Valid Percent	Cumulative Percent
          	a)<16	1	1.2	1.2	1.2
          	b)
          		45	54.2	54.2	55.4
          	16-25
          Vali d	c) 26-35	20	24.1	24.1	79.5
          	d) 36- 45	8	9.6	9.6	89.2
          	e) >=46	9	10.8	10.8	100.0
          	Total	83	100.0	100.0

          Interpretation:

          More than half of the respondents, i.e., 54.2% lie in the age group of 16-25 years. About 24% respondents are from the 26-35 age group. Close to 10% respondents are from 36-45 years age group.

          Monthly household income (INR)

          		Frequen cy	Percen t	Valid Percent	Cumulative Percent
          	a)<25,000	6	7.2	7.2	7.2
          	b)
          	25,0	9	10.8	10.8	18.1
          	00-50,000
          	c)
          Vali	50,0	20	24.1	24.1	42.2
          d	01-75,000
          	d)
          	75,0	17	20.5	20.5	62.7
          	01-1,00,000
          	e) >1,00,000	31	37.3	37.3	100.0
          	Total	83	100.0	100.0

          Interpretation:

          • 37.3% of the respondents have a monthly household income of greater than INR 1,00,000,

          • 24.1 % of the respondents have a household income between 50-75,000,

          • Only 7.2 % of the respondents have a family monthly income of less than 25,000.

        Occupation

        		Freque ncy	Percen t	Valid Percent	Cumulative Percent
        	a)
        	Profession	17	20.5	20.5	20.5
        	al
        	b)
        		12	14.5	14.5	34.9
        	Business
        Vali d	c)	42	50.6	50.6	85.5
        	Student
        	d)
        	Homemak	9	10.8	10.8	96.4
        	er
        	e) Retired	3	3.6	3.6	100.0
        	Total	83	100.0	100.0

        Interpretation:

        Nearly half 50% of the respondents are Students. 20.5 % of the respondents are Professionals, 14.5 % are Businessman, only 3.6% are Retired people.

        Summarized Rank Order

        Promotion	Score	Rank
        Combo offers (buy 1 get 1 free)	183	1
        Value packs (buy 2@50/- , 3@80/-)	228	2
        Price discounts (10% off on MRP)	242	3
        Quantity discounts (50g extra)	291	4
        -Freebies (free toothbrush, mouthwash etc.)	299	5

        Interpretation:

        The combo offers (buy one get 1 free) is considered to be most preferred. After this value packs appeal to the consumers more. The consumers are least attracted by freebies and have ranked them the least.

        Crosstab- Satisfaction v/s frequent and brand loyal users

        Satisfaction_level * Usage time Cross tabulation

        	Usage time		Total
        	Frequent shifters	Brand loyal
        Low Count satisfaction % within Satisfaction_ Usage time level Count High satisfaction % within Usage time Count Total % within Usage time	7	7	14
        	35.0%	11.1%	16.9%
        	13	56	69
        	65.0%	88.9%	83.1%
        	20	63	83
        	100.0%	100.0%	100.0 %

        Chi-Square Tests

        	Value	df	Asymp. Sig. (2- sided)	Exact Sig. (2-sided)	Exact Sig. sided)	(1-
        Pearson Chi- Square	6.178 a	1	.013
        Continuity Correctionb	4.592	1	.032
        Likelihood Ratio	5.477	1	.019
        Fisher's Exact Test				.034	.020
        Linear-by-Linear Association	6.104	1	.013
        N of Valid Cases	83

        1. 1 cells (25.0%) have expected count less than 5. The minimum expected count is 3.37.

        2. Computed only for a 2×2 table

        Symmetric Measures

        	Value	Approx.	Sig.
        	Phi	.273	.013
        Nominal by Nominal	Cramer's V	.273	.013
        N of Valid Cases		83

        1. Not assuming the null hypothesis.

        2. Using the asymptotic standard error assuming the null hypothesis.

        Interpretation:

        The p- value (0.13<alpha) shows that there is a relationship between usage time and satisfaction level

        Thus, it is observed that brand loyal people have high satisfaction with their brands as compared to the frequent users.

        Even though it has a weak relationship (phi= 0.273), 7.45% of variations in satisfaction level is explained by the type of respondents that are frequent shifters and brand loyal users.

        Spending redef * Age redefined

        	Age redefined		Tota l
        	Younge r respond ents	Older respond ents
        Count	37	22	59 71.1 % 24 28.9 % 83 100. 0%
        less than equal % within
        to INR 75 Age	80.4%	59.5%
        Spendin redefined
        g redef Count	9	15
        more than INR % within
        75 Age	19.6%	40.5%
        redefined
        Count	46	37
        Total % within Age	100.0%	100.0%
        redefined

        Crosstab

        Chi-Square Tests

        	Valu e	df	Asyp. Sig. (2- sided)	Exact Sig. (2- sided)	Exact Sig. sided)	(1-
        Pearson	Chi-	4.389 a 3.428 4.394 4.336 83	1 1 1 1	.036 .064 .036 .037
        Square
        Continuity
        Correctionb
        Likelihood
        Ratio
        Fisher's	Exact				.051	.032
        Test
        Linear-by-
        Linear
        Association
        N of	Valid
        Cases

        1. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 10.70.

        2. Computed only for a 2×2 table

        Symmetric Measures

        	Value	Approx. Sig.
        Nominal by Nominal Phi Cramer's V N of Valid Cases	.230 .230 83	.036 .036

        1. Not assuming the null hypothesis.

        2. Using the asymptotic standard error assuming the null hypothesis.

           Interpretation:

           Younger respondents prefer to spend less than INR75 as compared to the older respondents. This can be seen to be significant with p- value (.036) greater than alpha (0.05).

           On further probing, using Phi test, we find that the strength of relationship is not very strong. But, phi square= 5.29% of variations in spending patterns for toothpaste are explained by age.

           Spending redef * . Gender

           Crosstab

           		. Gender		Total
           		Male	Femal e
           less than equal to Count		37	22	59
           INR 75 % within Spending Gender	.	77.1%	62.9%	71.1%
           redef Count		11	13	24
           more than INR 75 % within Gender	.	22.9%	37.1%	28.9%
           Count		48	35	83
           Total % within	.	100.0	100.0	100.0
           Gender		%	%	%

           Chi-Square Tests

           	Valu e	df	Asymp. sided)	Sig.	(2-
           Pearson Chi- Square Likelihood Ratio	6.807 a 9.169	4 4	.146 .057
           Linear-by- Linear Association	5.385	1	.020
           N of Valid Cases	83

           	Value	df	Asymp. Sig. (2- sided)	Exact Sig. (2-sided)	Exact Sig. (1-sided)
           Pearson Chi-	1.993a 1.361 1.978 1.969 83	1 1 1 1	.158 .243 .160 .161
           Square
           Continuity
           Correctionb
           Likelihood Ratio
           Fisher's Exact Test				.220	.122
           Linear-by-Linear
           Association
           N of Valid Cases

           1. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 10.12.

           2. Computed only for a 2×2 table

        Interpretation:

        More males prefer spending less than INR 75 on toothpaste as compared to females. But, the results are insignificant as shown by chi square test.

        Spending redef * Monthly household income (INR)

        Crosstab

        		Monthly		household		income	To
        		(INR)					tal
        		a)<	b)	c)	d)	e)
        		25,				>1,0
        		00	25,0	50,0	75,0	0,00
        		0	00-	01-	01-	0
        			50,0	75,0	1,00,
        			00	00	000
        	Count	5 83. 3% 1 16. 7% 6 10 0.0 %	9 100. 0% 0 0.0% 9 100. 0%	15 75.0 % 5 25.0 % 20 100. 0%	12 70.6 % 5 29.4 % 17 100. 0%	18 58.1 % 13 41.9 % 31 100. 0%	59 71 .1 % 24 28 .9 % 83 10 0. 0 %
        	less than % within
        	equal to Monthly
        	INR 75 household
        	income
        Spen	(INR)
        ding
        redef	Count
        	more than % within
        	INR 75 Monthly
        	household
        	income
        	(INR)
        	Count
        	% within
        Total	Monthly
        	household
        	income
        	(INR)

        Chi-Square Tests

        a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is 1.73.

        Interpretation:

        Respondents with monthly household income between INR25001 and INR50000 prefer to spend less than INR75 on toothpaste purchase. But, chi square test is not valid here as 4 cells have expected count less than 5, so, no further analysis is done.

        Spending redef * Occupation

        Crosstab

        		Occupation					To tal
        		a) Profe ssion al	b) Busi ness	c) Stu den t	d) Home maker	e) Retir ed
        Spend ing redef Total	Count less than % equal to within INR 75 Occupat ion Count more than % INR 75 within Occupat ion Count % within Occupat ion	11	7	33	5 55.6% 4 44.4% 9 100.0 %	3	59
        		64.7 %	58.3 %	78. 6%		100. 0%	71. 1 %
        		6	5	9		0	24
        		35.3 %	41.7 %	21. 4%		0.0%	28. 9 %
        		17	12	42		3	83
        		100.0 %	100. 0%	10 0.0 %		100. 0%	10 0.0 %

        Chi-Square Tests

        	Valu e	df	Asymp. sided)	Sig.	(2-
        Pearson Chi-	4.70	4 4 1	.319 .244 .349
        Square	7a
        Likelihood	5.44
        Ratio	6
        Linear-by-
        Linear	.876
        Association
        N of Valid Cases	83

        a. 5 cells (50.0%) have expected count less than 5. The minimum expected count is .87.

        Interpretation:

        Mostly retired people and students prefer spending less than INR75 on toothpaste. But, chi square test is not valid here as 5 cells have expected count less than 5, so, no further analysis is done.

        Crosstabs

        How do you purchase your toothpaste? * Age redefined

        Crosstab

        			Age redefined		Tota l
        			Younge r respond ents	Older respond ents
        		Count	11	13	24
        	Ration	% within Age	23.9%	35.1%	28.9
        		redefined			%
        How do you purchase your toothpaste?	Planned Purchase	Count % within Age redefined	23	21	44
        			50.0%	56.8%	53.0 %
        	Impulse Buy	Count % within Age redefined	12	3	15
        			26.1%	8.1%	18.1 %
        		Count	46	37	83
        Total		% within Age	100.0%	100.0%	100.
        		redefined			0%

        Chi-Square Tests

        	Valu e	Df	Asymp. sided)	Sig.	(2-
        Pearson Chi- Square	4.737 a	2	.094
        Likelihood Ratio	5.062	2	.080
        Linear-by-Linear Association	3.771	1	.052
        N of Valid Cases	83

        a. 0 cells (0.0%) have expected count less than

        1. The minimum expected count is 6.69.

           Interpretation:

           Older respondents generally go for a planned purchase or ration as compared to younger respondents. Impulse buying behavior in case of toothpaste is shown more by the younger respondents. But, the results are insignificant as shown by chi square test.

           How do you purchase your toothpaste? * . Gender

           Total

           4

           8.9%

           4

           Crosstab

           1. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 6.33.

        Interpretation:

        Males generally go for a planned purchase or impulse buy for toothpaste whereas females purchase it with the monthly ration. But, the results are insignificant as shown by chi square test.

        How do you purchase your toothpaste? * Monthly household income (INR)

        Crosstab

        		Monthly household income (INR)					To tal
        		a)< 25, 000	b) 25,00 0- 50,00 0	c) 50,00 1- 75,00 0	d) 75,00 1- 1,00, 000	e) >1,0 0,00 0
        	Count	0 0.0 % 4 66. 7% 2 33. 3% 6 100 .0 %	3 33.3 % 4 44.4 % 2 22.2 % 9 100.0 %	7 35.0 % 9 45.0 % 4 20.0 % 20 100.0 %	6 35.3 % 10 58.8 % 1 5.9% 17 100.0 %	8 25.8 % 17 54.8 % 6 19.4 % 31 100. 0%	24 28. 9 % 44 53. 0 % 15 18. 1 % 83 10 0.0 %
        	% within
        	Ration Monthly
        	household
        	income
        	(INR)
        How do	Count
        you	Planne % within
        purchase	d Monthly
        your	Purchas household
        toothpaste	e income
        ?	(INR)
        	Count
        	% within
        	Impuls Monthly
        	e Buy household
        	income
        	(INR)
        	Count
        	% within
        Total	Monthly
        	household
        	income
        	(INR)

        Chi-Square Tests

        etation:

        3.0%

        5

        18.1%

        		. Gender			Chi-Square Tests
        		Male	Female			Value	df	Asymp.
        Ration How do you purchase Planned your toothpaste? Purchase Impulse Buy Total	Count % within . Gender Count % within . Gender Count % within . Gender Count % within . Gender	13 27.1% 26	11 31.4% 18					Sig. (2- sided)
        					Pearson Chi- Square Likelihood Ratio	5.426 a 7.469	8 8	.711 .487
        		54.2% 9	51.4% 6		Linear-by-Linear Association N of Valid Cases	.527 83	1	.468
        		18.8% 48	17.1% 35	a. 9 cells (60.0%) have expected count less than 5. The minimum expected count is 1.08.
        				8I3nterpr
        		100.0%	100.0%	1C00h.0i %s

        uare test is not valid here as 9 cells have expected count less than 5, so, no further analysis is done.

        How do you purchase your toothpaste? * Occupation

        	Value	df	Asymp. Sig. (2-sided)
        Pearson Chi-Square	.190a	2	.909
        Likelihood Ratio	.189	2	.910
        Linear-by-Linear Association	.155	1	.694
        N of Valid Cases	83

        Crosstab

        	Occupation					Tot
        	a) Pr ofessional	b) Business	c) Studen t	d) H omemaker	e) Retired
        Count Ration % within Occupation How do you Count Planned purchase your % within Purchase toothpaste? Occupation Count Impulse Buy % within Occupation Count Total % within Occupation	8	3	9	3	1	24
        	47.1%	25.0%	21.4%	33.3%	33.3%	28.
        	5	6	25	6	2	44
        	29.4%	50.0%	59.5%	66.7%	66.7%	53.
        	4	3	8	0	0	15
        	23.5%	25.0%	19.0%	0.0%	0.0%	18.
        	17	12	42	9	3	83
        	100.0%	100.0%	100.0 %	100.0%	100.0 %	100 %

        Chi-Square Tests

        	Value	df	Asymp. Sig. (2- sided)
        Pearson Chi-Square	8.248a	8	.410
        Likelihood Ratio	10.428	8	.236
        Linear-by-Linear Association	.003	1	.955
        N of Valid Cases	83

        1. 10 cells (66.7%) have expected count less than 5. The minimum expected count is .54.

           Interpretation:

           Chi square test is not valid here as 10 cells have expected count less than 5, so, no further analysis is done.

           • Switching Behavior

             (One- Sample t-test, Independent sample t-test, ANOVA)

             The objective is to determine which factors are most important for switching or replacement among brands of toothpastes.

             The mean values were found out for each factor. Higherthe value, more important is that factor for customers for replacement.

             Through a one-sample t-test, the significance of mean was determined.

             H0: Mean value of Replacement Factor = 3 H1: Mean value of Replacement Factor > 3

             Significance level=0.05

             This is a one-tailed t-test, so p-value is divided by 2.

             My dentist strongly recommended the brand	83	3.13	.332	0.166
             The other brand was cheaper	83	2.42	.000	0
             The previous brand was not easily available at stores	83	2.24	.000	0

             When p-value<0.05, H0 is rejected implying the corresponding switching factor mean is significant.

             From the above table significant factors in the order of importance are identified:

             1. Offered an attractive discount on the new brand

             2. Used the sample of the new brand and liked it.

             3. The other brand was cheaper

             4. The previous brand was not easily available at stores

             When p-value>0.05, there is not enough evidence to reject H0 implying the corresponding brand replacement factor mean is insignificant.

             From the above table insignificant factors are identified:

             1. Dissatisfaction with the previous brand

             2. A new dental problem not addressed by previous brand

             3. Recommendation by someone from social circle

             4. Attractive advertisements of the new brand

             5. Dentist recommendation

           • Demographic Variables vs Switching Behavior

        The objective is to understand the effect of demographic variables on factors considered most important for switching or replacement among different brands of toothpastes.

        The mean values were found out for each factor across each variable category. Higher the value, more important is the factor to that category of variable.

        Gender

        Through an independent sample t-test, the significance of difference in mean was determined.

        H0: Mean importance to Males = Mean importance to Females

        H1: Mean importance to Males Mean importance to Females

        Decsriptives
        If you have changed your toothpaste , please rate your agreement/disagreement with the following factors	. Gender	N	Mean
        I was dissatisfied with the previous brand	Male	48	2.75
        	Female	35	3.00
        had a new dental problem that the previous brand did not address	Male	48	2.81
        	Female	35	3.34
        It was recommended by someone from my social circle	Male	48	3.00
        	Female	35	2.74
        The advertisements of the new brand attracted me	Male	48	3.02
        	Female	35	3.20
        I used the free sample of the new brand and liked it	Male	48	2.56
        	Female	35	2.74
        I was offered an attractive	Male	48	2.65

        Significance level=0.05

        If you have changed your toothpaste, please rate your agreement/disagreement with the following factors	N	Mean	Sig. (2- tailed)	Sig. (1- tailed)
        I was dissatisfied with the previous brand	83	2.86	.176	0.088
        I had a new dental problem that the previous brand did not address	83	3.04	.789	0.3945
        It was recommended by someone from my social circle	83	2.89	.405	0.2025
        The advertisements of the new brand attracted me	83	3.10	.472	0.236
        I used the free sample of the new brand and liked it	83	2.64	.007	0.0035
        I was offered an attractive discount on the new brand (includes 1+1, or free gifts)	83	2.75	.058	0.029

        discount on the new brand (includes 1+1, or free gifts)	Female	35	2.89
        My dentist strongly recommended the brand	Male	48	2.90
        	Female	35	3.46
        The other brand was cheaper	Male	48	2.40
        	Female	35	2.46
        The previous brand was not easily available at stores	Male	48	2.25
        	Female	35	2.23

        My dentist strongly recommended the brand	Equal variances assumed	1.004	.319	.040
        	Equal variances not assumed			.038
        	Equal
        	variances	.857	.357	.797
        The other brand was cheaper	assumed
        	Equal variances not			.799
        	assumed
        	Equal
        	variances	.306	.582	.926
        The previous brand	assumed
        was not easily	Equal
        available at stores	variances not			.928
        	assumed

        Independent Samples Test
        If you have changed your toothpaste , please rate your agreement/disagreement with the following factors		Levene's Test for Equality of Variances		t-test for Equality of Means
        		F	Sig.	Sig. (2- tailed)
        I was dissatisfied with the previous brand	Equal variances assumed	.270	.605	.246
        	Equal variances not assumed			.256
        I had a new dental problem that the previous brand did not address	Equal variances assumed	4.737	.032	.051
        	Equal variances not assumed			.060
        It was recommended by someone from my social circle	Equal variances assumed	.208	.650	.330
        	Equal variances not assumed			.337
        The advertisements of the new brand attracted me	Equal variances assumed	2.287	.134	.511
        	Equal variances not assumed			.503
        I used the free sample of the new brand and liked it	Equal variances assumed	.008	.930	.501
        	Equal variances not assumed			.501
        I was offered an attractive discount on the new brand (includes 1+1, or free gifts)	Equal variances assumed	.001	.970	.371
        	Equal variances not assumed			.369

        Here, p-value corresponding to equality of variances is insignificant (>0.05). So, the variances of two groups are not equal.

        When p-value<0.05, H0 is rejected implying there is difference in the importance of replacement factor among males and females.

        From the above table only 1 significant factor was identified

        i.e. my dentist strongly recommended the brand. It is more important for females than males. In fact, males do not consider it an important attribute.

        When p-value>0.05, there is not enough evidence to reject null hypothesis. This means the difference in switching factor preference can be attributed to chance and not to gender. Differences in mean for all other attributes were insignificant.

        Age

        Through ANOVA, the significance of difference in mean was determined.

        0

        H : All means are equal

        H1: At least two means are not equal Significance level=0.05

        ANOVA
        If you have changed your toothpaste , please rate your agreement/disagreement with the following factors		Sig.
        I was dissatisfied with the previous brand	Between Groups	.339
        	Within Groups
        	Total
        I had a new dental problem that the previous brand did not address	Between Groups	.440
        	Within Groups
        	Total
        It was recommended by someone from my social circle	Between Groups
        	Within Groups
        	Total
        The advertisements of the new brand attracted me	Between Groups	.455
        	Within Groups

        	Total
        I used the free sample of the new brand and liked it	Between Groups	.572
        	Within Groups
        	Total
        I was offered an attractive discount on the new brand (includes 1+1, or free gifts)	Between Groups	.133
        	Within Groups
        	Total
        My dentist strongly recommended the brand	Between Groups	.985
        	Within Groups
        	Total
        The other brand was cheaper	Between Groups	.064
        	Within Groups
        	Total
        The previous brand was not easily available at stores	Between Groups	.785
        	Within Groups
        	Total

        4	.830	8.296	80.07 0
        5	.692	6.918	86.98 9
        6	.432	4.323	91.31 2
        7	.303	3.029	94.34 1
        8	.265	2.654	96.99 6
        9	.209	2.092	99.08 8
        10	.091	.912	100.0 00

        When between groups p-value>0.05, there is not enough evidence to reject null hypothesis. Differences in mean for all switching factors w.r.t. age are insignificant. This means the difference in factors importance on switching behavior of respondents can be attributed to chance and not to age.

        Similar results were observed when ANOVA analysis was conducted for all other demographic variables (income, occupation).

        Therefore, the differences in the average importance of above factors on switching behavior among toothpaste brands can be attributed to chance.

        • Identifying the various parameters that affect the purchase behavior

        (FACTOR ANALYSIS)

        The major objective of doing factor analysis is to analyze together and extract underlined factors from variables under investigations.

        STEP 1: Analyzing KMO and Bartletts test KMO and Bartlett's Test

        Kaiser-Meyer-Olkin Measure of Sampling Adequacy.	.710
        Approx. Chi-Square	430.746
        Bartlett's Test of Sphericity Df	45
        Sig.	.000

        Since, the value of KMO statistics is greater than 0.5, this indicates that factor analysis can be used for the given set of data.

        Also since the p-value in a Bartletts test <0.05. Hence indicating that the correlation coefficient matrix is significant. STEP 2: Analyzing Total Variance explained

        Co mp one nt	Initial Eigenvalues			Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
        	Tot al	% of Varian ce	Cumu lative %	Tot al	% of Varia nce	Cum ulati ve %	Tot al	% of Varian ce	Cumu lative %
        1	3.86 1	38.607	38.60 7	3.86 1	38.60 7	38.6 07	2.69 6	26.964	26.96 4
        2	1.91 2	19.119	57.72 6	1.91 2	19.11 9	57.7 26	2.33 3	23.331	50.29 5
        3	1.40 5	14.049	71.77 4	1.40 5	14.04 9	71.7 74	2.14 8	21.480	71.77 4

        Total Variance Explained

        Extraction Method: Principal Component Analysis.

        Through this table we can see that:

        • There are 3 factors with eigen values greater than one. The percentage of variance explained by these 3 factors are 26.9, 23.3,21.4 respectively.

        • A total variance explained by these factors is 71.774%.

        Step3: Analyzing Communalities

        Communalities

        	Initial	Extraction
        Rate your agreement/disagreement with the following statement of factors
        which influence your purcha…-I select the toothpaste because it is cheaper than	1.000	.800
        the other toothpastes
        Rate your agreement/disagreement with the following statement of factors
        which influence your purcha…-The toothpaste is available at the store in my	1.000	.848
        locality
        Rate your agreement/disagreement with the following statement of factors
        which influence your purcha…-The toothpaste is prominently placed in	1.000	.772
        departmental stores
        Rate your agreement/disagreement with the following statement of factors
        which influence your purcha…-I see the hoardings, posters, newspaper ads, of	1.000	.808
        popular brands and then decide.
        Rate your agreement/disagreement with the following statement of factors
        which influence your purcha…-I buy that toothpaste which is endorsed by the	1.000	.639
        brand ambassador I like
        Rate your agreement/disagreement with the following statement of factors
        which influence your purcha…-I prefer a toothpaste because it offers attractive	1.000	.520
        schemes and discounts
        Rate your agreement/disagreement with the following statement of factors
        which influence your purcha…-I prefer a toothpaste which gives value for	1.000	.671
        money.
        Rate your agreement/disagreement with the following statement of factors which influence your purcha…-The toothpaste is available at most o the places.	1.000	.910
        Rate your agreement/disagreement with the following statement of factors
        which influence your purcha…-I watch the TV advertisement and decide the	1.000	.811
        brand.
        Rate your agreement/disagreement with the following statement of factors
        which influence your purcha…-I buy that toothpaste which is recommended by	1.000	.399
        dentists

        Extraction Method: Principal Component Analysis.

        This table depicts that:

        80% of variation in selection of toothpaste because it is cheaper than other toothpaste are explained by these 3 factors. A similar analysis of the other 9 variables can be done.

        Step 4: Factor Deduction using Component Matrix

        Using component matrix and a cut-off point of 0.6 the following variables can be clubbed into their respective factors.

        Stage	Cluster Combined		Coefficients	Stage Cl Appears	uster First	Next Stage
        	Cluster 1	Cluster 2		Cluster 1	Cluster 2
        1	33	54	.000	0	0	2
        2	1	33	.000	0	1	13
        3	47	80	6.000	0	0	8
        4	46	70	6.000	0	0	9
        5	44	51	6.000	0	0	22
        6	23	45	6.000	0	0	23
        7	64	65	8.000	0	0	35
        8	47	58	8.000	3	0	16
        9	12	46	8.000	0	4	36
        10	30	34	8.000	0	0	15
        11	9	17	8.000	0	0	36
        12	43	56	9.000	0	0	23
        13	1	49	9.000	2	0	32
        14	6	35	9.000	0	0	26
        15	5	30	9.000	0	10	30
        16	47	53	10.333	8	0	19
        17	20	57	11.000	0	0	38
        18	26	36	11.000	0	0	43
        19	4	47	11.750	0	16	25
        20	19	81	12.000	0	0	41
        21	52	62	12.000	0	0	28
        22	44	50	12.000	5	0	28
        23	23	43	12.500	6	12	29
        24	31	82	13.000	0	0	50
        25	4	21	13.400	19	0	31
        26	6	13	13.500	14	0	38
        27	11	37	14.000	0	0	35
        28	44	52	14.333	22	21	34
        29	8	23	14.750	0	23	46
        30	5	63	15.000	15	0	42
        31	4	61	15.833	25	0	42
        32	1	39	16.250	13	0	39
        33	29	69	17.000	0	0	57
        34	44	60	17.000	28	0	44
        35	11	64	17.500	27	7	51
        36	9	12	17.667	11	9	48
        37	3	41	18.000	0	0	48
        38	6	20	18.833	26	17	59
        39	1	83	19.000	32	0	53
        40	71	75	19.000	0	0	71
        41	19	42	20.000	20	0	46
        42	4	5	20.393	31	30	52
        43	7	26	20.500	0	18	58
        44	44	48	20.833	34	0	52
        45	24	40	21.000	0	0	68
        46	8	19	21.933	29	41	65
        47	22	28	22.000	0	0	56
        48	3	9	22.400	37	36	56
        49	10	79	23.000	0	<>0	73
        50	31	77	23.500	24	0	53
        51	11	55	23.500	35	0	66
        52	4	44	23.792	42	44	58
        53	1	31	24.278	39	50	62
        54	25	76	26.000	0	0	81
        55	15	74	26.000	0	0	68
        56	3	22	27.143	48	47	61
        57	29	78	27.500	33	0	63
        58	4	7	28.037	52	43	61
        59	6	38	28.200	38	0	60
        60	6	16	31.167	59	0	65
        61	3	4	31.381	56	58	67
        62	1	59	31.444	53	0	69
        63	29	72	33.333	57	0	70
        64	68	73	34.000	0	0	77
        65	6	8	34.375	60	46	67
        66	2	11	35.200	0	51	71
        67	3	6	36.451	61	65	73
        68	15	24	37.500	55	45	74

        	Component
        	1	2	3
        Rate your agreement/disagreement with the	.113 .902 .838 .083 .124 .256 .108 .930 .193 – .408	.887 .187 .055 .113 .594 .610 .812 .205 .199 -.173	.026 .011 .259 .888 .521 .286 -.019 .043 .857 .450
        following statement of factors which influence your
        purcha…-I select the toothpaste because it is
        cheaper than the other toothpastes
        Rate your agreement/disagreement with the
        following statement of factors which influence your
        purcha…-The toothpaste is available at the store in
        my locality
        Rate your agreement/disagreement with the
        following statement of factors which influence your
        purcha…-The toothpaste is prominently placed in
        departmental stores
        Rate your agreement/disagreement with the
        following statement of factors which influence your
        purcha…-I see the hoardings, posters, newspaper
        ads, of popular brands and then decide.
        Rate your agreement/disagreement with the
        following statement of factors which influence your
        purcha…-I buy that toothpaste which is endorsed by
        the brand ambassador I like
        Rate your agreement/disagreement with the
        following statement of factors which influence your
        purcha…-I prefer a toothpaste because it offers
        attractive schemes and discounts
        Rate your agreement/disagreement with the
        following statement of factors which influence your
        purcha…-I prefer a toothpaste which gives value for
        money.
        Rate your agreement/disagreement with the
        following statement of factors which influence your
        purcha…-The toothpaste is available at most of the
        places.
        Rate your agreement/disagreement with the
        following statement of factors which influence your
        purcha…-I watch the TV advertisement and decide
        the brand.
        Rate your agreement/disagreement with the
        following statement of factors which influence your
        purcha…-I buy that toothpaste which is
        recommended by dentists

        Rotated Component Matrixa

        Agglomeration Schedule

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

        1. Rotation converged in 5 iterations.

           S.No	Factor 1	Factor 2	Factor 3
           1	available at the store in my locality	is cheaper than the other toothpastes	See the hoardings, posters, newspaper ads, of popular brands and then decide.
           2	prominently placed in departmental stores	it offers attractive schemes and discounts	Watch the TV advertisement and decide the brand.
           3	Toothpaste is available at most of the places.	Toothpaste which gives value for money.
           FACTOR NAME	Place	Price	Promotion

           Hence, the 3 factors that can explain these 10 variables are: Factor 1: Place

           Factor 2: Price

           Factor 3: Promotion

           • Classifying the customers based on demographic and lifestyle parameters

             (Cluster Analysis)

             69	1	18	39.100	62	0	72
             70	29	67	41.500	63	0	80
             71	2	71	42.333	66	40	78
             72	1	66	42.818	69	0	75
             73	3	10	44.189	67	49	74
             74	3	15	44.399	73	68	75
             75	1	3	48.358	72	74	76
             76	1	14	51.317	75	0	77
             77	1	68	56.578	76	64	78
             78	1	2	59.981	77	71	80
             79	27	32	63.000	0	0	82
             80	1	29	66.195	78	70	81
             81	1	25	95.848	80	54	82
             82	1	27	98.920	81	79	0

             					53	1	1	1	1
             					54	1	1	1	1
             					55	1	1	1	1
             					56	1	1	1	1
             					57	1	1	1	1
             					58	1	1	1	1
             					59	1	1	1	1
             					60	1	1	1	1
             					61	1	1	1	1
             					62	1	1	1	1
             					63	1	1	1	1
             					64	1	1	1	1
             					65	1	1	1	1
             					66	1	1	1	1
             					67	4	4	1	1
             As per the agglomeration schedule, the largest difference is between 95.848-66.195=29.653 between 3 cluster and 4					68 69 70	1 4 1	1 4 1	1 1 1	1 1 1
             cluster solution. Hence, there is a 3 cluster solution.					71 72	1 4	1 4	1 1	1 1
             Cluster Membership					73 74	1 1	1 1	1 1	1 1
             Case	5 Clusters	4 Clusters	3 Clusters	2 Clusters
             					75 76 77 78 79 80 81 82 83	1 2 1 4 1 1 1 1 1	1 2 1 4 1 1 1 1 1	1 2 1 1 1 1 1 1 1	1 1 1 1 1 1 1 1 1
             1 2 3 4 5 6 7 8 9 10 11	1 1 1 1 1 1 1 1 1 1 1	1 1 1 1 1 1 1 1 1 1 1	1 1 1 1 1 1 1 1 1 1 1	1 1 1 1 1 1 1 1 1 1 1
             					As per the cluster membership we can observe that majority of the variables lie in the 1st cluster. Hence, it has a one cluster solution.
             12	1	1	1	1
             13	1	1	1	1
             14	1	1	1	1
             15	1	1	1	1
             16	1	1	1	1
             17	1	1	1	1
             18	1	1	1	1
             19	1	1	1	1
             20	1	1	1	1
             21	1	1	1	1
             22	1	1	1	1
             23	1	1	1	1
             24	1	1	1	1
             25	2	2	2	1
             26	1	1	1	1
             27	3	3	3	2
             28	1	1	1	1
             29	4	4	1	1
             30	1	1	1	1
             31	1	1	1	1
             32	5	3	3	2
             33	1	1	1	1
             34	1	1	1	1
             35	1	1	1	1
             36	1	1	1	1
             37	1	1	1	1
             38	1	1	1	1
             39	1	1	1	1
             40	1	1	1	1
             41	1	1	1	1
             42	1	1	1	1
             43	1	1	1	1
             44	1	1	1	1
             45	1	1	1	1
             46	1	1	1	1
             47	1	1	1	1
             48	1	1	1	1
             49	1	1	1	1
             50	1	1	1	1
             51	1	1	1	1
             52	1	1	1	1

             As per the dendogram, most respondents lie in one cluster only. Hence, it has a one cluster solution.

             Hence, by using K-means we find out the 3cluster solution and their scores.

             Final Cluster Centers

             	Cluster
             	1	2	3
             I prefer eating vegetarian food	2.310 3.000 2.552 3.966 3.310 3.897 3.724 2.276 2.241 3.000 2.897 3.621 3.724 3.448 3.379 3.448	2.600 1.933 1.467 2.533 2.800 1.733 1.533 1.733 2.333 2.400 2.067 2.533 1.933 1.800 1.600 2.200	4.538 2.487 1.000 4.179 2.795 3.256 1.590 1.077 2.564 3.590 2.923 4.077 3.538 3.103 2.308 3.897
             over non- vegetarian food
             I prefer fast food over home-
             cooked food
             I smoke more than 3 cigarettes
             a day
             I like ice-creams
             I drink at least 3 cups of coffee/
             tea per day
             I love going out with friends
             over family
             I prefer alcoholic beverages
             when I go out
             I chew tobacco
             I like watching soap operas
             I prefer sweets after my meals
             I like drinking soft drinks with
             my meal
             I like chocolates/ candies
             I travel at least once in 6
             months
             I hang out more than once a
             week
             I work out every day
             I prefer watching movies on
             theatre

             From this we can observe that none of the variables lie in the second cluster. Hence, a three cluster solution is not possible.

             Hence, we study the 2 cluster solution.

             Final Cluster Centers

             	Cluster
             	1	2
             I prefer eating vegetarian food over	3.167 2.944 2.056 4.056 3.944 3.944 3.222 1.778 2.333 3.444 3.139 3.861 3.917 3.750 2.806 3.611	3.596 2.277 1.298 3.617 2.234 2.638 1.638 1.489 2.468 2.957 2.468 3.468 2.851 2.404 2.362 3.298
             non- vegetarian food
             I prefer fast food over home- cooked
             food
             I smoke more than 3 cigarettes a day
             I like ice-creams
             I drink at least 3 cups of coffee/ tea per
             day
             I love going out with friends over
             family
             I prefer alcoholic beverages when I go
             out
             I chew tobacco
             I like watching soap operas
             I prefer sweets after my meals
             I like drinking soft drinks with my meal
             I like chocolates/ candies
             I travel at least once in 6 months
             I hang out more than once a week
             I work out every day
             I prefer watching movies on theatre

             On the basis of the above data we can classify the respondents into 2 clusters.

             The first cluster consists of consumers having:

             • Prefer fast food over home- cooked food

             • Smoke more than 3 cigarettes a day

             • Like ice-creams

             • Drink at least 3 cups of coffee/ tea per day

             • Love going out with friends over family

             • Prefer alcoholic beverages when go out

             • Chew tobacco

             • Prefer sweets after meals

             • Drink soft drinks with meals

             • Like chocolates/ candies

             • Travel at least once in 6 months

             • Hang out more than once a week

             • Work out every day

             • Prefer watching movies on theatre

               Hence, we can classify them as outgoing western consumers The second cluster consists of consumers having traits:

               • Prefer vegetarian over non-vegetarian food

               • Like watching soap operas

             Hence, we can say that the consumers are traditional in their habits.

             ANOVA

             	Cluster		Error		F	Sig.
             	Mean Square	df	Mean Square	df
             I prefer eating vegetarian	3.753 9.092 11.703 3.920 59.637 34.778 51.144 1.696 .370 4.835 9.173 3.149 23.148 36.919 4.016 2.000	1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1	2.498 1.251 1.305 1.272 1.485 1.145 1.421 1.506 1.799 1.467 1.358 1.062 1.145 .964 1.512 1.462	81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81	1.503 7.271 8.967 3.083 40.150 30.376 36.000 1.126 .206 3.296 6.754 2.966 20.225 38.305 2.656 1.369	.224 .009 .004 .083 .000 .000 .000 .292 .651 .073 .011 .089 .000 .000 .107 .245
             food over non- vegetarian
             food
             I prefer fast food over
             home- cooked food
             I smoke more than 3
             cigarettes a day
             I like ice-creams
             I drink at least 3 cups of
             coffee/ tea per day
             I love going out with
             friends over family
             I prefer alcoholic
             beverages when I go out
             I chew tobacco
             I like watching soap operas
             I prefer sweets after my
             meals
             I like drinking soft drinks
             with my meal
             I like chocolates/ candies
             I travel at least once in 6
             months
             I hang out more than once
             a week
             I work out every day
             I prefer watching movies
             on theatre

             Next we see the Anova table to see which all variables that distinguished between both the clusters were not significant. The p-value of variable prefer vegetarian over non- vegetarian which is 0.224 and watching soap operas which is .651are greater than significance level of .05.

             Hence, we can conclude that the two variables are not significant enough to distinguish between clusters.

             We now find out the two cluster solution using SPSS. The conclusion we get is that the cluster quality for a two cluster solution is poor.

           • Develop a model based on attributes to predict group membership :

        (Discriminant Analysis)

        A discriminant analysis was done with the aim to develop a model to predict brand selection (group membership) based on attribute based preference of each customer. The predictor variables were determined from Q7 where users were asked to represent their importance for specific features on a five point scale. These variables were:

        1. Tooth Decay

        2. Gum Problems

        3. Teeth Whitening

        4. Medicinal Value

        5. Lather

        6. Ingredients

        7. Long lasting Freshness

        8. Taste

        A discriminant analysis was performed on the variables and the data file and output file for the model are included in the CD.

        Descriptive Statistics: The mean scores along with standard deviation for predictor variables are indicated below:

        Tests for differences in group means: The following figure indicates test of equality of mean. As per the significance values (greater than 0.05), there is no significant difference in the mean values of the variables.

        Correlation Matrix: The pooled within-group matrices were used to present the correlation for the entire predictor variables. Since the correlation coefficient between any pair of predictor variables does not exceed 0.75, therefore there is no problem of multi-collinearity.

        Unstandardized Discriminant Functions:

        The results in the form of discriminant functions:

        Y 1 = – 3.439 + 0.505 X1 + 0.833 X3 + 0.135 X4 0.204 X5

        + 0.125 X6 0.011 X7 0.601 X8

        Y2 = – 4.328 – 0.544 X1 0.45 X2 + 0.697 X3 + 0.81 X4-

        0.117 X5 -0.392 X6 + 1.018 X7 + 0.26 X8

        Where, Y1= Discriminant Score 1 Y2= Discriminant Score 2

        X1= Prevention of Tooth Decay X2= Prevention of Gum Problems X3= Teeth Whitening

        X4= Medicinal Value X5= Lather

        X6= Ingredients X7= Bad Breath X8= Taste

        The eigenvalue for the discriminant functions comes out to be

        0.121 and 0.041. Canonical Correlation is the correlation between the discriminant score and the group membership (Colgate/Pepsodent/Close up). Square of the canonical correlation is (0.329)2 = 0.108, which means 10.8 percent of the variance in the discriminating model between Colgate/Pepsodent/Close Up is due to the changes in Function 1, making it more important than Function 2 (with canonical correlation as 0.199)

        Significance of discriminant function model:

        Wilks Lambda is 0.856 for Function 1 and 0.96 for Function

        2. The lower the value of Wilks Lambda (ranging from 0 to 1), the higher is the significance of the discriminant function. Thus, in the case of Colgate/Pepsodent/Close Up discriminant analysis for various attributes, it can be inferred that the discriminant function is not significant. Also, the significance value is more than 0.05, and thus cannot be used for further interpretation of results.

        Hence, we conclude that we have a one cluster solution. Since the product is a low involvement product all the consumers do not think much and all have a similar

        preference. Due to the limitation of our profile that has roughly around 50% students between the age group of 16- 25, all have a similar lifestyle.

   3. BRAND COMPARISON

      • Feature specific association with brands Effect of branding campaigns and promotional schemes on usage patterns

   (Perceptual Mapping)

   Based on the rating provided by the respondents on various attributes to each brand the perceptual map for the various brands was created.

   Steps in conducting a perceptual map

   Step 1: Means for each attribute for various brands were calculated.

   Step 2: Factor analysis was conducted on these attributes and the results were as shown:

   Total Variance Explained

   Co mpo nent	Initial Eigenvalues			Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
   	Total	% of Varianc e	Cumul ative %	Total	% of Var ianc e	Cum ulati ve %	Tot al	% of Varia nce	Cumul ative %
   1	2.77 7	55.540 34.195 10.240 .024 – 5.917E- 016	55.540	2.777	55. 540	55.5 40	2.7 24	54.48 1	54.481
   2	1.71 0		89.735	1.710	34. 195	89.7 35	1.7 63	35.25 4	89.735
   3	.512		99.976
   4	.001		100.00 0
   	–
   5	2.95 9E-		100.00 0
   	017

   Extraction Method: Principal Component Analysis.

   This result indicates that the two factors explain a total variance of 89.735%.

   Where factor 1 explain a variance of 54.48%, factor 2 explain a variance of 35.25%.

   Rotated Component Matrixa

   	Component
   	1	2
   prevention_of_tooth_decay	.987	-.021
   long_lasting_freshness	-.954	.125
   teeth_whitening	.910	-.004
   taste_flavour	.009	.946
   prevention_of_gumproblem	.105	-.93

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

   1. Rotation converged in 3 iterations.

      Taking a cut-off point of 0.7, the rotated component matrix indicate that

      Factor 1 comprises of attributes like prevention_of_tooth_decay and teeth_whitening.

      Factor 2 comprises of attributes like taste and flavour.

      Hence we can name Factor1 as Dental care and Factor 2 as Taste and Flavour.

      Step 3:Based on these factors we plot the various brands on the map with Dental care on the x-axis and taste and flavour on the y-axis.

      The perceptual map for the various brands is as follows:

      Inferences :

      • Colgate is very high on the second factor i.e dental care and is decent on the first factor i.e. taste and flavour.

      • Hence colgate is perceived as a total dental care brand and is the most preferred brand.

      • Close-up is very high on the first factor i.e., taste and flavour and is low on dental care.

      • Pepsodent is very low on dental care and high on taste factor.

      • Sensodyne is very bad on taste and flavour and less on dental hygiene. Sensodyne only focuses on gum problems and sensitivity and hence it lies in the lower half of the graph.

      • Dabur red is a brand that is moderate on both the factors.

5. MARKETING IMPLICATIONS & CONCLUSION