market research blind product test
DESCRIPTION
Analysis of data collected from Blind Product TestTRANSCRIPT
ANALYSIS OFBLIND PRODUCT
TEST
Submitted By:Amarjeet
SinghKoushik
RakshitNamita
PandeyRoma
Agrawal
MARKET RESEARCH TERM PROJECT
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AGENDA
Background Objective Research Design Sample Size and Data Description Feedback Analysis Summary Questions
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R & D team of Smirnoff has prepared two new blends of Vodka; Test Blend 1 and Test Blend 2
Marketing team want to do Blind test of the two new blends Vs. Smirnoff (Control Blend)
Any of the Test Blends if found to be better than Smirnoff then it will be replaced by that new Test Blend.
BACKGROUND
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Primary Objective To test whether drinkers have liked the new test
blends of vodka or not. To decide whether current blend should be
replaced by any of the new test blends or not (at 90% and 95% Confidence level)
Secondary Objective To find the important attributes that drive overall
preference of vodka and to what extent they are responsible for overall likability of the blend.
To reduce the correlated attributes into factors and to see their effect on overall likeability
To predict the purchase intentions by evaluating the ratings on attributes.
OBJECTIVE
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One to one interview was conducted in 5 large cities – Delhi, Mumbai, Kolkata, Bangalore, Chennai
The Research was conducted with sequential monadic exposure – 3 blends were given one after the another and feedback was taken
Consumers were given neutralizer after each blend to remove bias
Target GroupMales/Females in the age group of 25 – 35 yrs.Consuming vodka at least twice a weekRegular consumer of any one of the three brands – Smirnoff, Fuel or Magic Moments
RESEARCH DESIGN
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760, each will be given 3 blends of VodkaTotal = 760*3 = 2280 observations
Each person will be given a unique a “unique response no” and they have to response for each of 3 blends, i.e., 3 rows for each persons.
SAMPLE SIZE AND DATA DESCRIPTION
PANEL
PANEL1(where Test Product 1 is first blend)
PANEL1(where Control
Product is first blend)
PANEL1(where Test Product 2 is first blend)
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Age- Recorded as number of yrs., ranging from 25 to 35
Ages – Recorded as two bands of Age 1 – Age between 25–30yrs & 2 – Age between
31–35yrs
25 26 27 28 29 30 31 32 33 34 350
5
10
15
20
25
30
12.93
24.33
6.082.66 2.66
6.46
13.69
9.13
6.08
7.98 7.98
14.4
18.4
6.8
4
1.2
5.6
11.212
3.2
11.212
14.5714.57
6.88
7.69
3.643.64
14.17
9.72
4.86
12.96
7.29
PANEL1PANEL2PANEL3
AGE (YR)
PERCENTAGE
At 95%, there is no significant difference among age and age groups
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Study was done in 5 centers:
Placement Order and Product goes together– 1 – First-placed blend2 – Second-placed blend 3 – Third-placed blend
Product beside this specifies which blend is first, second or third.
DELHI MUMBAI KOLKATA BANGALORE CHENNAI16
17
18
19
20
21
22
20.91
20.53
19.77
18.25
20.53
18
19.6
20.4
20.8
21.2
19.03 19.43
19.84
21.46
20.24
PANEL1PANEL2PANEL3
PERCENTAGE
At 95%, there is no significant difference among centers as well
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Each attribute was ranked on a scale of 1 to 10 (10 being the max and 0 means that it is not all being liked by the drinker)
Strength of different attribute was taken on 5 point likert scale:
Intention to buy
1-Yes and 2-No
FEEDBACK
1 (too weak)5 (too strong)
2 (little weak)
3 (just right)4 (too strong)
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Analysis Starts
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Attributes in the order of their importance:Taste -> Mouth Feel -> Aroma ->
Smoothness -> Throat Feel -> Flavor -> After Taste “After taste” was not adding any value so Ignored
that attribute in predicting the overall likeability Regression Equation:
This equation explains 77.4 % variability in Overall Likeability
IMPORTANCE OF ATTRIBUTES
[Overall Likeability] = 0.589 + 0.174[Aroma] + 0.300[Taste] + 0.118[Smoothness] + 0.089[Flavour] + 0.101[Throat Feel] + 0.206[Mouth Feel]
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Top2 at 95% CL
Prod1 and
Prod2
Prod3 and
Prod2
Overall Likeability SAME SAME
Taste SAME SAME
Mouth Feel SAME SAME
Top3 at 95% CL
Prod1 and
Prod2
Prod3 and
Prod2
Overall Likeability DIFFERENT SAME
Taste DIFFERENT SAME
Mouth Feel SAME SAME
Neither Blends are better than Control Product (Smirnoff)at 95% Confidence Level (Taken top 2 rating and top 3 ratings)
MainBrand %age
Magic Moments 22.76%
Smirnoff 62.23%
Fuel 15.00%
SMIRNOFF OR OTHER ?
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OVERALL LIKEABILITY W.R.T. STRENGTH
Attributes in the order of their importance:Strength Of Taste -> Strength of Smoothness
-> Strength of After Taste -> Strength of Flavor
“Strength of Aroma” is not a important factor.
This equation explains 7.1 % variability in Overall Likeability, We should not consider all these.
[Overall Likeability] = 8.56 - 0.300[Strength of Taste] + 0.150[Strength of Smoothness] - 0.093[Strength of Flavour] - 0.117[Strength of After Taste]
Note: This is not correct to do, as OL is on 10 point scale and rest of the predictors are on 5 point scale
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Correlation Matrix
Arom
aTast
eSmoothn
ess FlavorThroat-
FeelAfter-taste
Mouth-Feel
Correlation
Aroma 1.000
Taste.699
1.000
Smoothness
.650 .778 1.000
Flavor .699 .783 .730 1.000
Throat-Feel
.644 .749 .784 .743 1.000
After-taste
.658 .791 .759 .772 .796 1.000
Mouth-Feel
.652 .797 .762 .768 .814 .831 1.000
CORRELATION ?
Huge Correlation and KMO statistics (0.945) > 0.5 hence we can go for factor Analysis
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CANNOT BE CONVERTED INTO FACTORS
Total Variance Explained
Component
Initial EigenvaluesExtraction Sums of Squared
Loadings
Total% of
VarianceCumulativ
e % Total% of
VarianceCumulativ
e %1 5.482 78.316 78.316 5.482 78.316 78.3162 .431 6.156 84.473 3 .276 3.939 88.412 4 .252 3.603 92.015 5 .220 3.146 95.161 6 .179 2.558 97.718 7 .160 2.282 100.000
Total Variance is explained by 1 component only.
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Structure Matrix
Function
1Taste .373
Aroma .337Throat-feel .212
Smoothness .139Flavor .057
After Taste -.072Mouth Feel .148
Considering all attributes except Overall Likeability
Classification Resultsa,c
Q6_Int_p (Y=1,N=2)
Predicted Group Membership
Total1 2Original Count 1 519 204 723
2 125 1432 1557% 1 71.8 28.2 100.0
2 8.0 92.0 100.0Cross-validatedb
Count 1 516 207 7232 127 1430 1557
% 1 71.4 28.6 100.02 8.2 91.8 100.0
PURCHASE BEHAVIOR W.R.T. ATTRIBUTES
a. 85.6% of original grouped cases correctly classified.b. 85.4% of cross-validated grouped cases correctly classified.
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Standardized Canonical Discriminant Function
Coefficients
Function
1Taste .477
Aroma .370Throat-Feel .329
Classification Resultsa,c
Q6_Int_p (Y=1,N=2)
Predicted Group Membership
Total1 2Original Count 1 498 225 723
2 129 1428 1557% 1 68.9 31.1 100.0
2 8.3 91.7 100.0Cross-validatedb
Count 1 498 225 7232 129 1428 1557
% 1 68.9 31.1 100.02 8.3 91.7 100.0
Only considering 3 most important attributes
a. 84.5% of original grouped cases correctly classified.b. 84.5% of cross-validated grouped cases correctly classified.
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There is no difference in samples w.r.t age, ages, market, centers, panels, products. (Chi square test is used to test this)
Taste and Mouth Feel are most important attributes and After taste is least important (Regression and step-wise regression)
Seen that there were correlation between many attributes, we clubbed the correlated attributes into factors and then tried to find the effect on overall likeability (Factor Analysis and Regression)
We tried to discriminate the two levels of purchase intension on the basis of attributes Important attributes were: Overall likeability, taste,
Mouth Feel Least Important comes out to be: Flavor and after taste
SUMMARY
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Control product should not be replaced by any of the test products
Aroma, Taste, Mouth-Feel and Throat feel are most important attributes that drinkers like.
After taste is least important
Main brand of drinkers is Smirnoff only.
Company should concentrate on these 3 attributes if in future they want to launch any new products
We would like to suggest a launch of new product but not with the replacement of Smirnoff
CONCLUSION
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Thank YouFor Listening
Us…
Any Questions?