Indian Institute of Management Shillong
PGP'21
TERM I
Project On
STATISTICS FOR DECISION MAKING
PROJECT TITLE
DESCRIPTIVE ANALYSIS AND SOLUTIONS FOR FAST FOOD
BRANDS TARGETING BRAND EQUITY
Presented By:
Name
Group A
Regn. No.
1
Ayesha
Anjum Khan
2021PGP198
2
Rahul Raja
2021PGP227
3
Naval Mittal
2021PGP219
4
Himanshu
Parashar
R Rajsekar
2021PGP206
Ruchikha
Sharma
Tarun Kant
2021PGP230
5
6
7
Section D
2021PGP226
2021PGP245
Contribution
•
Interpreted all the descriptive analysis and
tests and made all the charts
• Summarized hypothesis tests and its results
• Deduced conclusions and made
recommendations
• Made this report
Age wise data analysis of 6 parameters:
• ANNOVA
• Descriptive analysis
Brand and Region wise data analysis of 6
parameters each:
• ANNOVA
• Tukey
• Descriptive analysis
Observed ANNOVA with Tukey and made
recommendations
Observed ANNOVA with Tukey and made
recommendations
Observed ANNOVA with Tukey and made
recommendations
• Parameter correlation, Regression and
inference
• Observed ANNOVA with Tukey and made
recommendations
Contents
ABSTRACT .............................................................................................................................. 3
METHODS AND METHODOLOGY: .................................................................................. 3
DATA ANALYSIS................................................................................................................... 4
Interpretation of kurtosis and skewness ........................................................................................... 4
CORRELATION: Demographic And Brand Related Parameters .................................... 5
Parameter Regression and Inference .................................................................................... 5
Brand Equity Parameter Correlation ............................................................................................... 16
Bin Frequency ................................................................................................................................. 16
Analysis across Brands .................................................................................................................... 16
Analysis across Age Groups ............................................................................................................. 19
Analysis Across Regions .................................................................................................................. 21
Hypothesis testing Summary .......................................................................................................... 24
Hypothesis testing for Age-Income ................................................................................................. 24
Hypothesis testing for Age-Uniqueness .......................................................................................... 25
Hypothesis testing for Age Relevance ............................................................................................. 26
Hypothesis testing for Age Familiarity ............................................................................................ 26
Hypothesis testing for Age Loyalty .................................................................................................. 26
Hypothesis testing for Age Popularity ............................................................................................. 27
Hypothesis testing for Region Popularity ........................................................................................ 28
Hypothesis testing for Region Loyalty ............................................................................................. 28
Hypothesis testing for Region Relevance ........................................................................................ 28
Hypothesis testing for Region Uniqueness ..................................................................................... 29
Hypothesis testing for Region Familiarity ....................................................................................... 29
Hypothesis testing for Brand Familiarity ......................................................................................... 29
Hypothesis testing for Brand Uniqueness ....................................................................................... 29
Hypothesis testing for Brand Relevance ......................................................................................... 30
Hypothesis testing for Brand Loyalty .............................................................................................. 30
Hypothesis testing for Brand Popularity ......................................................................................... 30
Hypothesis testing for Brand Income .............................................................................................. 30
MAJOR CONLCUSIONS ..................................................................................................... 31
RECOMMENDATIONS....................................................................................................... 31
Page 2 of 32
ABSTRACT
We made the brand center of our deduction and analyzed how a particular brand is
perceived across a parameter or is consumed in a segment.
The datasheet has 17 variables for a given BRAND as listed below:
1. Gender
2. Age
3. Children
4. Income
5. Familiarity
6. Uniqueness
7. Relevance
8. Loyalty
9. Popularity
10. Category
11. Family Bin
12. Uniqueness Bin
13. Relevance Bin
14. Loyalty Bin
15. Popularity Bin
16. Region
17. Brand Equity
METHODS AND METHODOLOGY:
There are various methodologies being followed in order to find the relation between
the five parameters mentioned in the fast-food data.
The first methodology is calculating correlation between the income and 5 parameters.
This is done in order to identify the variables that have negative, zero or positive
correlation and to what extent are they correlated.
The second methodology followed is finding the descriptive analysis. This is done in
two ways, one finding the overall analysis considering all the brands together and
second finding the detailed analysis while segregating all the 5 parameters into 3
different aspects; region, brand, and age group.
The third methodology that is used is finding the hypothesis test using ANOVA. Here
the testing is done to identify the comparability of the means for each of the
parameters with respect to each of the aspects. However, when the ANOVA test fails,
we need to identify the variables for which the mean values are not equal. And in
order to find so, TUKEY Test was performed whenever the ANOVA Test got rejected.
And lastly, the fourth methodology used was to identify the frequency of loyalty in
various ratings across the different parameters. And for the findings of those, we
created a Histogram.
Page 3 of 32
DATA ANALYSIS
We identified 6 primary parameters and deduced correlation amongst them. We also
mapped the bin frequency across these parameters and compared the means for these
parameters across Brands, Age Groups and Regions. Lastly we conducted Hypothesis
testing using ANNOVA and Tukey Test and made some recommendations.
Particulars
Mean
Standard Error
Median
Mode
Standard
Deviation
Sample
Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Sum
Count
Confidence
Level(95.0%)
Familiarity
Uniqueness
Relevance
Loyalty
Popularity
7.144096064
0.07636493
8
10
2.956615001
6.305221
0.071216
7
8
2.752679
5.890897
0.075585
6
5
2.921525
5.787333
0.077969
6
8
3.019744
7.2982574
0.0699803
8
10
2.7030891
8.741572263
7.57724
8.535309
9.118852
7.3066905
-0.554388159
-0.837381923
9
1
10
10709
1499
0.149793543
-0.85656
-0.40661
9
1
10
9420
1494
0.139695
-1.10001
-0.2446
9
1
10
8801
1494
0.148264
-1.19474
-0.22361
9
1
10
8681
1500
0.152941
-0.141052
-0.914235
9
1
10
10889
1492
0.1372703
Interpretation of kurtosis and skewness
Kurtosis
Skewness
familiarity
Fewer values in the tails and fewer values close to the mean. The curve
-0.554388159 has a flat peak and has more dispersed scores with lighter tails.
-0.837381923 Fairly skewed. Values are concentrated on the right side (tail)
Kurtosis
Skewness
Uniqueness
-0.85656 Almost like a semicircle.
-0.40661 Very close to normal but values are a little concentrated on the right tail.
Kurtosis
Skewness
Relevance
-1.10001 Kurtosis almost like a block.
-0.2446 Very close to normal but values are a little concentrated on the right tail.
Kurtosis
Loyalty
-1.194744 Kurtosis almost like a block
Page 4 of 32
Skewness
-0.223608 Very close to normal but values are a little concentrated on the right tail.
Popularity
-0.141051503 Very close to normal
-0.914234899 Fairly skewed. Values are concentrated on the right side (tail)
Kurtosis
Skewness
CORRELATION: Demographic And Brand Related Parameters
child
ren
age
gender
age
children
income
gender
1
0.01
-0
0.11
famil
-0
-0.03
uniqu
0.01
-0.01
1
-0.01
0.02
1
0.00
3
relev
0.03
0.006
loyal
0.01
-0.02
popul
0
region
brand_e
quity
1
0.279
0.13
inco
me
uni
qu
famil
rele
v
loy
al
popu
l
1
0.7
7
0.5
8
1
0.6
5
1
-0
-0
-0
1
0.8
3
0.8
7
0.83
-0
region
brand_
equity
1
0.044
1
-0.04
0.63
-0.05
-0.07
0.57
-0.04
0.64
0.014
-0.01
0.02
1
-0.03
0.7
0.04
-0.04
-0.04
0.094
-0.02
1
0.5
99
0.6
24
0.6
08
0.0
3
0.02
0.002
-0.01
0.055
0.85
0.8
13
1
Parameter Regression and Inference
brand_equity
Field: loyal and Field: brand_equity appear highly
correlated.
10
9
8
7
6
5
4
3
2
1
0
0
2
4
6
8
10
12
loyal
Page 5 of 32
Field: famil and Field: gender
appear unrelated.
2.5
gender
2
1.5
1
0.5
0
0
5
10
15
famil
Field: unique and Field: gender appear unrelated.
2.5
gender
2
1.5
1
0.5
0
0
2
4
6
8
10
12
unique
Field: revel and Field: gender appear unrelated.
2.5
gender
2
1.5
1
0.5
0
0
2
4
6
8
10
12
relev
Page 6 of 32
Field: loyal and Field: gender unrelated.
2.5
gender
2
1.5
1
0.5
0
0
2
4
6
8
10
12
loyal
Field: popul and Field: gender appear unrelated
2.5
gender
2
1.5
1
0.5
0
0
2
4
6
8
10
12
popul
Field: famil and Field: age appear unrelated.
70
60
age
50
40
30
20
10
0
0
2
4
6
8
10
12
famil
Page 7 of 32
Field: unique and Field: age appear unrelated.
70
60
age
50
40
30
20
10
0
0
2
4
6
8
10
12
unique
Field: revel and Field: age appear unrelated.
70
60
age
50
40
30
20
10
0
0
2
4
6
8
10
12
relev
Field: loyal and Field: age appear unrelated.
70
60
age
50
40
30
20
10
0
0
2
4
6
8
10
12
loyal
Page 8 of 32
Field: popul and Field: age appear unrelated.
70
60
age
50
40
30
20
10
0
0
2
4
6
8
10
12
popul
Field: famil and Field: family size appear
unrelated.
2.5
Family Size
2
1.5
1
0.5
0
0
2
4
6
8
10
12
famil
Field: unique and Field: family size unrelated.
2.5
Family Size
2
1.5
1
0.5
0
0
2
4
6
8
10
12
unique
Page 9 of 32
Field: relev and Field: family size appear
unrelated.
2.5
Family Size
2
1.5
1
0.5
0
0
2
4
6
8
10
12
relev
Field: loyal and Field: family size appear
unrelated.
2.5
Family Size
2
1.5
1
0.5
0
0
2
4
6
8
10
12
loyal
Field: popul and Field: family size appear
unrelated.
2.5
Family Size
2
1.5
1
0.5
0
0
2
4
6
8
10
12
popul
Page 10 of 32
Field: famil and Field: income appear unrelated.
4.5
4
3.5
Income
3
2.5
2
1.5
1
0.5
0
0
2
4
6
8
10
12
famil
Field: unique and Field: income appear
unrelated.
4.5
4
3.5
Income
3
2.5
2
1.5
1
0.5
0
0
2
4
6
8
10
12
unique
Field: relev and Field: income appear unrelated.
4.5
4
3.5
Income
3
2.5
2
1.5
1
0.5
0
0
2
4
6
8
10
12
relev
Page 11 of 32
Field: loyal and Field: income appear unrelated.
4.5
4
3.5
Income
3
2.5
2
1.5
1
0.5
0
0
2
4
6
8
10
12
loyal
Field: popul and Field: income appear unrelated.
4.5
4
3.5
Income
3
2.5
2
1.5
1
0.5
0
0
2
4
6
8
10
12
popul
brand_equity
Field: famil and Field: brand_equity appear highly
correlated.
10
9
8
7
6
5
4
3
2
1
0
0
2
4
6
8
10
12
famil
Page 12 of 32
brand_equity
Field: unique and Field: brand_equity appear
highly correlated.
10
9
8
7
6
5
4
3
2
1
0
0
2
4
6
8
10
12
unique
brand_equity
Field: relev and Field: brand_equity appear highly
correlated.
10
9
8
7
6
5
4
3
2
1
0
0
2
4
6
8
10
12
relev
brand_equity
Field: loyal and Field: brand_equity appear highly
correlated.
10
9
8
7
6
5
4
3
2
1
0
0
2
4
6
8
10
12
loyal
Page 13 of 32
brand_equity
Field: popul and Field: brand_equity appear
highly correlated.
10
9
8
7
6
5
4
3
2
1
0
0
2
4
6
8
10
12
popul
Field: famil and Field: region appear unrelated.
4.5
4
3.5
region
3
2.5
2
1.5
1
0.5
0
0
2
4
6
8
10
12
famil
Field: unique and Field: region appear unrelated
5
region
4
3
2
1
0
0
2
4
6
8
10
12
unique
Page 14 of 32
Field: loyal and Field: Region appear unrelated.
4.5
4
3.5
Region
3
2.5
2
1.5
1
0.5
0
0
2
4
6
8
10
12
loyal
Field: Popul and Field: Region appear unrelated
4.5
4
3.5
Region
3
2.5
2
1.5
1
0.5
0
0
2
4
6
8
10
12
Popul
Field: relev and Field: region appear unrelated
5
region
4
3
2
1
0
0
2
4
6
8
10
12
relev
Page 15 of 32
Brand Equity Parameter Correlation
Income
Familiarity
Uniqueness
Relevance
Loyalty
Popularity
Parameter Correlation (on a scale of -1 to 1)
Income Familiarity Uniqueness Relevance Loyalty Popularity
1.000
0.045
1.000
-0.041
0.629
1.000
-0.066
0.575
0.600
1.000
-0.044
0.639
0.625
0.767
1.000
-0.026
0.703
0.612
0.579
0.648
1.000
Bin Frequency
Bin Frequency
1500
1000
877
622
879
615
956
948
538
552
867
625
Familiarity
Uniqueness
Relevance
Loyalty
Popularity
500
0
0
1
Analysis across Brands
Means of Brands
Mean of famil
Mean of relev
Mean of popul
Mean of uniqu
Mean of loyal
10.000
9.000
8.000
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
Brand 263
Brand 264
Brand 265
Brand 266
Brand 267
Grand Total
Page 16 of 32
Brand Familiarity
Familiarity Mean of famil
Familiarity SD(+)
12
9.816340207
9.89927405
10
8
Familiarity SD(-)
10.57625411
9.654682735
9.619781341
10.10071106
8.785016287
6.982332155
7.16838488
4.148324104
4.43749571
6
6.310126582
4
6.993778468
6.476821192
7.144096064
4.187481063
3.333861043
2.96557043
2
0
Brand 263 (Count
283)
Brand 264
(Count 291)
Brand 265 (Count Brand 266 (Count Brand 267 (Count
316)
307)
302)
Grand Total
(Count 1499)
Brand Relevance
Relevance Mean of relev
Relevance SD(+)
Relevance SD(-)
10.000
9.000
8.000
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
Brand 263
(Count 281)
Brand 264
(Count 289)
Brand 265
(Count 315)
Brand 266
(Count 308)
Brand 267
(Count 301)
Grand Total
(Count 1494)
Page 17 of 32
Brand Loyalty
12.000
10.000
8.000
6.000
9.567
8.569
8.621
8.448
8.559
8.807
5.430
5.787
6.808
5.802
5.591
5.301
4.050
4.000
3.035
2.000
2.561
2.153
Brand 264
(Count 291)
Brand 265
(Count 316)
2.302
2.768
0.000
Brand 263
(Count 283)
Loyalty Mean of loyal
Brand 266
(Count 308)
Loyalty SD(+)
Brand 267
(Count 302)
Grand Total
(Count 1500)
Loyalty SD(-)
Brand Popularity
Popularity Mean of popul
12.000
10.000
9.337
8.000
6.795
6.000
4.253
9.952
Popularity SD(+)
Popularity SD(-)
10.671
9.219
9.085
7.514
7.499
6.262
9.648
10.001
6.821
7.298
5.076
3.993
3.305
4.000
4.595
2.000
0.000
Brand 263
(Count 283)
Brand 264
(Count 288)
Brand 265
(Count 313)
Brand 266
(Count 307)
Brand 267
(Count 301)
Grand Total
(Count 1492)
Brand Uniqueness
Uniqueness Mean of uniqu
Uniqueness SD(+)
Uniqueness SD(-)
12.000
9.815
10.000
8.000
8.853
8.528
6.228
5.979
3.603
3.430
Brand 263
(Count 281)
Brand 264
(Count 290)
8.695
9.058
6.153
6.305
3.217
3.553
Brand 267
(Count 301)
Grand Total
(Count 1494)
7.325
5.822
4.835
6.000
4.000
9.088
2.948
2.000
0.000
Brand 265
(Count 314)
Brand 266
(Count 308)
Page 18 of 32
Analysis across Age Groups
Means across Age groups
Mean of famil
Mean of uniqu
Mean of relev
Mean of loyal
Mean of popul
8.000
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
Age group 20-29 Age Group 30-39 Age Group 40-49 Age Group 50-59 Age Group 60-69
Grand Total
Familiarity in Age Groups
Familiarity Mean of famil
12.000
Familiarity SD+
10.357
10.230
9.875
10.083
7.306
7.199
7.000
7.314
4.255
4.168
4.125
4.544
10.000
8.000
6.000
4.000
Familiarity SD9.681
6.573
3.465
10.099
7.140
4.181
2.000
0.000
Age group 20-29 Age Group 30-39 Age Group 40-49 Age Group 50-59 Age Group 60-69
(Count 222)
(Count 523)
(Count 392)
(Count 239)
(Count 96)
Grand Total
(Count 1472)
Page 19 of 32
Uniqueness in Age Groups
Uniqueness Mean of uniqu
10.000
8.000
Uniqueness SD+
Uniqueness SD-
8.997
9.129
9.000
9.073
9.058
9.060
6.203
6.382
6.300
6.363
6.011
6.306
3.408
3.636
3.600
3.653
6.000
4.000
2.963
3.552
2.000
0.000
Age group 20-29 Age Group 30-39 Age Group 40-49 Age Group 50-59 Age Group 60-69
(Count 222)
(Count 523)
(Count 390)
(Count 237)
(Count 95)
Grand Total
(Count 1467)
Popularity in Age Groups
Popularity Mean of popul
12.000
Popularity SD+
10.200
9.955
9.981
10.101
7.303
7.201
7.354
7.599
4.406
4.448
4.727
5.098
10.000
8.000
6.000
Popularity SD9.535
10.001
6.781
7.294
4.027
4.587
4.000
2.000
0.000
Age group 20-29 Age Group 30-39 Age Group 40-49 Age Group 50-59 Age Group 60-69
(Count 221)
(Count 522)
(Count 390)
(Count 237)
(Count 96)
Grand Total
(Count 1466)
Relevance in Age Group
Relevance Mean of relev
10.000
9.000
8.000
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
Relevance SD+
Relevance SD-
8.988
8.785
8.703
8.986
8.755
8.823
5.914
5.891
5.833
6.084
5.708
5.898
2.841
2.997
2.963
3.183
2.662
2.974
Age group 20-29 Age Group 30-39 Age Group 40-49 Age Group 50-59 Age Group 60-69
(Count 222)
(Count 523)
(Count 389)
(Count 237)
(Count 96)
Grand Total
(Count 1467)
Page 20 of 32
Loyalty in Age Groups
Loyalty Mean of loyal
10.000
Loyalty SD+
9.077
8.816
8.616
8.908
5.905
5.830
5.634
5.941
2.734
2.843
2.651
2.974
Loyalty SD8.455
8.795
8.000
6.000
4.000
5.344
2.232
5.775
2.756
2.000
0.000
Age group 20- Age Group 30- Age Group 40- Age Group 50- Age Group 60- Grand Total
29 (Count 222) 39 (Count 523) 49 (Count 393) 59 (Count 239) 69 (Count 96) (Count 1473)
Analysis Across Regions
Means across Regions
8.000
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
Mean of famil
Mean of uniqu
Mean of Loyalty
Count of popul
Region 1 (Count 117)
Region 2 (Count 349)
Region 4 (Count 474)
Grand Total (Count 1494)
Mean of relev
Region 3 (Count 554)
Page 21 of 32
Familiarity in region
Mean of famil
SD+
SD-
12.000
10.000
8.000
6.000
4.000
2.000
0.000
Region 1 (Count 119) Region 2 (Count 350) Region 3 (Count 553) Region 4 (Count 477) Grand Total (Count
1499)
Uniqueness in Region
Mean of uniqu
SD+
SD-
10.000
9.000
8.000
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
Region 1 (Count 117) Region 2 (Count 350) Region 3 (Count 554) Region 4 (Count 473) Grand Total (Count
1494)
Relevance in Region
Series1
Series2
Series3
10.000
9.000
8.000
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
Region 1 (Count 117) Region 2 (Count 349) Region 3 (Count 554)Region 4 (Count 474) Grand Total (Count
1494)
Page 22 of 32
Loyality in Region
Series1
Series2
Series3
10.000
9.000
8.000
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
Region 1 (Count 119) Region 2 (Count 350) Region 3 (Count 554)Region 4 (Count 477) Grand Total (Count
1500)
Popularity in Region
Series1
Series2
Series3
12.000
10.000
8.000
6.000
4.000
2.000
0.000
Region 1 (Count 117) Region 2 (Count 346) Region 3 (Count 554)Region 4 (Count 475) Grand Total (Count
1492)
Page 23 of 32
Hypothesis testing Summary
Testing parameter
Hypothesis testing for Age-Income
Hypothesis testing for Age-Income
Hypothesis testing for Age Relevance
Hypothesis testing for Age
Familiarity
Hypothesis testing for Age Loyalty
Test outcome Rejected tests
Rejected
4/10 rejections in Tukey
test
Rejected
5/10 rejections in Tukey
test
Rejected
8/10 rejections in Tukey
test
Accept
NA
Rejected
Hypothesis testing for Age
Popularity
Hypothesis testing for Region
Popularity
Hypothesis testing for Region
Loyalty
Hypothesis testing for Region
Relevance
Hypothesis testing for Region
Uniqueness
Hypothesis testing for Region
Familiarity
Hypothesis testing for Brand
Familiarity
Hypothesis testing for Brand
Uniqueness
Hypothesis testing for Brand
Relevance
Hypothesis testing for Brand Loyalty
Hypothesis testing for Brand
Popularity
Hypothesis testing for Brand Income
Rejected
Accept
Rejected
4/10 rejections in Tukey
test
4/10 rejections in Tukey
test
NA
Accept
4/6 rejections in Tukey
test
4/6 rejections in Tukey
test
4/6 rejections in Tukey
test
NA
Accept
NA
Accept
NA
Accept
NA
Accept
Accept
NA
NA
Accept
NA
Rejected
Rejected
Hypothesis testing for Age-Income
ANOVA
Source of
Variation
Between
Groups
SS
27413.3
df
MS
F
P-value
F crit
4 6853.33 8.40194 0.00092 4.89321 Reject
Page 24 of 32
Within
Groups
12235.3
15 815.683
Total
39648.6
19
Tukey Test
TDifference value
AB
75.25 50.5514
AC
42.75 50.5514
AD
4.25 50.5514
AE
31.5 50.5514
BC
32.5 50.5514
BD
71 50.5514
BE
106.75 50.5514
CD
38.5 50.5514
CE
74.25 50.5514
DE
35.75 50.5514
Result
Reject
Pass
Pass
Pass
Pass
Reject
Reject
Pass
Reject
Pass
Hypothesis testing for Age-Uniqueness
ANOVA
Source of
Variation
SS
df
MS
F
Between
10968.9
11.6061
Groups
2
4 2742.23
8
Within
236.273
Groups
10632.3
45
3
Total
21601.2
2
Tukey Test
Difference T-value
AB
30.1 16.23494
AC
16.8 16.23494
AD
1.5 16.23494
AE
12.7 16.23494
BC
13.3 16.23494
BD
28.6 16.23494
BE
42.8 16.23494
CD
15.3 16.23494
CE
29.5 16.23494
DE
14.2 16.23494
Pvalue
1.47E06
F crit
3.76742
7 Reject
49
Result
Reject
Reject
Pass
Pass
Pass
Reject
Reject
Pass
Reject
Pass
Page 25 of 32
Hypothesis testing for Age Relevance
ANOVA
Source of
Variation
Between
Groups
Within
Groups
Total
SS
10910.1
2
df
MS
4
6433.1
45
17343.2
2
49
Tukey Test
Difference T-value
AB
30.1 12.62812
AC
16.7 12.62812
AD
1.5 12.62812
AE
12.6 12.62812
BC
13.4 12.62812
BD
28.6 12.62812
BE
42.7 12.62812
CD
15.2 12.62812
CE
29.3 12.62812
DE
14.1 12.62812
2727.53
142.957
8
F
19.0792
7
Total
F crit
3.76742
7 Reject
P-value
0.01522
3
F crit
3.76742 Accep
7 t
P-value
F crit
Result
Reject
Reject
Pass
Pass
Reject
Reject
Reject
Reject
Reject
Reject
Hypothesis testing for Age Familiarity
ANOVA
Source of
Variation
SS
df
MS
F
Between
10945.7
3.45309
Groups
2
4 2736.43
2
Within
792.457
Groups
35660.6
45
8
46606.3
2
Pvalue
3.09E09
49
Hypothesis testing for Age Loyalty
ANNOVA
Source of
Variation
SS
df
MS
F
Page 26 of 32
Between
Groups
Within
Groups
Total
10965.32
12053.1
23018.42
Tukey Test
Difference T-value
AB
30.1 17.28591
AC
17.1 17.28591
AD
1.7 17.28591
AE
12.6 17.28591
BC
13 17.28591
BD
28.4 17.28591
BE
42.7 17.28591
CD
15.4 17.28591
CE
29.7 17.28591
DE
14.3 17.28591
4
2741.33 10.2347
45 267.8467
49
Result
Reject
Pass
Pass
Pass
Pass
Reject
Reject
Pass
Reject
Pass
Hypothesis testing for Age Popularity
ANOVA
Source of
Variation
SS
df
MS
F
Between
10897.8
3.87843
Groups
8
4 2724.47
3
Within
702.466
Groups
31611
45
7
Total
42508.8
8
Tukey Test
TDifference value
AB
30.1 27.9937
AC
16.9 27.9937
AD
1.6 27.9937
AE
12.5 27.9937
BC
13.2 27.9937
BD
28.5 27.9937
BE
42.6 27.9937
CD
15.3 27.9937
5.58E06 3.767427 Reject
P-value
0.00863
1
F crit
3.76742
7 Reject
49
Result
Reject
Pass
Pass
Pass
Pass
Reject
Reject
Pass
Page 27 of 32
CE
DE
29.4 27.9937 Reject
14.1 27.9937 Pass
Hypothesis testing for Region Popularity
ANOVA
Source of Variation
SS
df
MS
F
P-value
F crit
Between Groups
10943 3 3647.66667 3.4177828 0.02744382 4.37709562 Accept
Within Groups
38421.4 36 1067.26111
Total
49364.4 39
Hypothesis testing for Region Loyalty
ANOVA
Source of Variation
SS
df
MS
F
P-value
F crit
Between Groups 10860.6 3
3620.2 10.6848345 3.6294E-05 4.37709562 Reject
Within Groups
12197.4 36 338.816667
Total
AB
AC
AD
BC
BD
CD
23058 39
Tukey Test
Difference T-value
23.1 17.4508324
43.5 17.4508324
35.8 17.4508324
20.4 17.4508324
12.7 17.4508324
7.7 17.4508324
Result
Reject
Reject
Reject
Reject
Pass
Pass
Hypothesis testing for Region Relevance
ANOVA
Source of Variation
SS
df
MS
F
P-value
F crit
Between Groups 10907.3 3 3635.76667 17.3549551 3.8864E-07 4.37709562 Reject
Within Groups
7541.8 36 209.494444
Total
AB
AC
AD
18449.1 39
Tukey Test
Difference T-value
23.2 13.7218693
43.7 13.7218693
35.7 13.7218693
Result
Reject
Reject
Reject
Page 28 of 32
BC
BD
CD
20.5 13.7218693 Reject
12.5 13.7218693 Pass
8 13.7218693 Pass
Hypothesis testing for Region Uniqueness
ANOVA
Source of Variation
SS
df
MS
F
P-value
F crit
Between Groups 10882.5 3
3627.5 9.5205809 9.1104E-05 4.37709562 Reject
Within Groups
13716.6 36 381.016667
Total
AB
AC
AD
BC
BD
CD
24599.1 39
Tukey Test
Difference T-value
23.3 18.5056999
43.7 18.5056999
35.6 18.5056999
20.4 18.5056999
12.3 18.5056999
8.1 18.5056999
Result
Reject
Reject
Reject
Reject
Pass
Pass
Hypothesis testing for Region Familiarity
ANOVA
Source of
Variation
Between
Groups
Within
Groups
Total
SS
df
MS
F
2.97692683
10824.875
3
3608.29167
43635.1
36
1212.08611
54459.975
39
P-value
F crit
0.0442824 4.377095
5
62 Accept
Hypothesis testing for Brand Familiarity
Source of Variation
Between Groups
Within Groups
Total
ANOVA
SS
df
MS
F
P-value
F crit
67.88 4 16.97 0.02167914 0.99904859 3.76742708 Accept
35225.1 45 782.78
35292.98 49
Hypothesis testing for Brand Uniqueness
ANOVA
Page 29 of 32
Source of
Variation
Between
Groups
SS
df
MS
17.87
250.0
4
71.48
Within Groups
11251.8
4
4
5
Total
11323.2
8
4
9
F
0.0714685
7
P-value
0.9903732
1
F crit
3.7674270
8 Accept
Hypothesis testing for Brand Relevance
Source of Variation
Between Groups
Within Groups
Total
ANOVA
SS
df
MS
F
P-value
F crit
76.48 4 19.12 0.13479977 0.96868765 3.76742708 Accept
6382.8 45 141.84
6459.28 49
Hypothesis testing for Brand Loyalty
ANOVA
Source of Variation
SS
df
MS
F
P-value
F crit
Between Groups
69.4 4
17.35 0.07242176 0.99012814 3.76742708 Accept
Within Groups
10780.6 45 239.568889
Total
10850 49
Hypothesis testing for Brand Popularity
ANOVA
Source of
Variation
SS
df
MS
F
Between
0.056600
Groups
202.53356
4
50.63339
08
Within
894.58156
Groups
39361.5889 44
6
Total
39564.1224
P-value
0.993827
41
F crit
3.778409
35 Accept
48
Hypothesis testing for Brand Income
ANOVA
Source of
PVariation
SS
df MS
F
value
F crit
Between
Groups
173.5 4 43 0.216 0.9254 4.89321 Accept
Page 30 of 32
Within
Groups
3012.5 15 201
Total
3186 19
MAJOR CONLCUSIONS
•
•
•
•
•
Income has no impact on relevance or loyalty or popularity of the product
Most of the products that are familiar to the people are the only ones that come
in their income bracket
Familiarity builds popularity
Uniqueness of the product makes it relevant to the people
Loyalty comes from relevance
RECOMMENDATIONS
1. As can be observed in the age group 30-39, the income is highest fast food
chains can perform specific demographic targeting.
2. In the age group 60-69, as the mean average becomes the least, these could act
as the lesser targeted audience.
3. As the uniqueness is more preferred in the age group of 30-39, this could be
the parameter kept in mind while performing demographic targeting.
4. Increasing the relevance for the age groups 20-29 and 50-59 can help create
larger consumer base
5. Since across all age groups, familiarity is equally spread, a given fast food
company needs to invest heavily in marketing that targets emotional aspect to
convert familiarity into loyalty and thus get an edge over other companies
6. As most loyalty is shown by the age-group 30-39, special offers can be provided
to the loyal customers and simultaneously to increase the loyalty in the age
group 20-29 and 50-59, primary research to understand their consumption
pattern can be observed, using which they can be converted into loyal
customers.
7. As we have observed in the previous parameters as well, fast food networks
are most popular in the age bracket of 30-39, as they are the high income
bracket who might be able to spend more, however the other two age groups
Page 31 of 32
20-29 and 50-59 are also the emerging demographies and hence could act as
potential demographies.
8. Popularity across all regions is same for all fast-food companies. Therefore, to
compete in such a geography, the company may conduct a thorough PESTLE
analysis and appeal to the segment that has been ignored by expanding its
market.
9. Most loyalty is observed in region 3 and 4 while region 2 appears to be the
emerging market and is show casing growing loyalty towards these fast food
networks and hence increasing loyalty in this region would help create better
profitability
10. Relevance in region 1 can be increased by understanding their consumer
behavior
11. Though in region 2 the relevance for fast food is growing but still there is a lot
of potential to get at par with region 3 and 4
12. Familiarity across regions is not similar therefore competing fast food
companies should extend familiarity to loyalty to retain their customers
otherwise the customers will switch to other products.
13. More uniqueness is preferred in the region3, therefore understanding the needs
of the customers more variations can be introduced in their product categories
14. The Hypothesis tests for Brand Equity across Brand Familiarity, Uniqueness,
Relevance, Loyalty, Popularity and Income were all accepted. This shows that
it is a highly competitive market. Primary recommendation for the company
here is to invest in the Customer Experience and make connections with the
customer by leveraging social media.
Page 32 of 32