Districts Region Units Unit Price Sales Revenue

1 Central 46 8.99 413.54

2 Central 90 4.99 449.10 Descriptive Analysis
3 Central 36 4.99 179.64
4 Central 96 4.99 479.04 What can be understood from the
following data?
5 Central 14 1.29 18.06
6 Central 50 19.99 999.50
7 Central 28 8.99 251.72
8 Central 50 4.99 249.50
9 Central 11 4.99 54.89
1 Central 2 125.00 250.00
2 Central 5 125.00 625.00
3 Central 66 1.99 131.34
4 Central 27 19.99 539.73
5 Central 55 12.49 686.95
6 Central 42 23.95 1,005.90
7 Central 53 1.29 68.37
8 Central 94 19.99 1,879.06
9 Central 7 1.29 9.03
10 Central 28 4.99 139.72
Region Units Sales Revenue
11 East 62 4.99 309.38
12 East 16 15.99 255.84
13 East 64 8.99 575.36
14 East 74 15.99 1,183.26
15 East 35 4.99 174.65
16 East 15 19.99 299.85
17 East 81 19.99 1,619.19
18 East 95 1.99 189.05
19 East 60 4.99 299.40
20 East 60 8.99 539.40
21 East 29 1.99 57.71
22 East 96 4.99 479.04
23 East 4 4.99 19.96
Region Units Sales Revenue
24 West 3 275.00 825.00
25 West 87 15.00 1,305.00
26 West 32 1.99 63.68
27 West 90 4.99 449.10
28 West 7 19.99 139.93
29 West 75 1.99 149.25
30 West 67 1.29 86.43
31 West 80 8.99 719.20
32 West 57 19.99 1,139.43
33 West 76 1.99 151.24
34 West 56 2.99 167.44
 Central
Units Units
e Analysis
Mean 42.1052631579 Mean
be understood from the Standard Error 6.73773294549 Standard Error
ata?
Median 42 Median
Mode 50 Mode
Standard Deviation 29.3690970179 Standard Deviation
Sample Variance 862.543859649 Sample Variance
Kurtosis -0.5459352528 Kurtosis
Skewness 0.4996586906 Skewness
Range 94 Range
Minimum 2 Minimum
Maximum 96 Maximum
Sum 800 Sum
Count 19 Count

Sales Revenue Sales Revenue

Mean 443.688947368 Mean

Standard Error 105.722710653 Standard Error
Median 251.72 Median
Mode #N/A Mode
Standard Deviation 460.834611775 Standard Deviation
Sample Variance 212368.53941 Sample Variance
Kurtosis 4.31367116786 Kurtosis
Skewness 1.87698465138 Skewness
Range 1870.03 Range
Minimum 9.03 Minimum
Maximum 1879.06 Maximum
Sum 8430.09 Sum
Count 19 Count
 Units Units

53.15384615385 Mean
8.492716452444 Standard Error
60 Median
60 Mode
30.62092463726 Standard Deviation
937.641025641 Sample Variance
-1.17303928739 Kurtosis
-0.20741887921 Skewness
92 Range
4 Minimum
96 Maximum
691 Sum
13 Count

Sales Revenue Sales Revenue

461.6992307692 Mean
126.9181747833 Standard Error
299.85 Median
#N/A Mode
457.6099869696 Standard Deviation
209406.9001744 Sample Variance
2.823554052693 Kurtosis
1.759065028705 Skewness
1599.23 Range
19.96 Minimum
1619.19 Maximum
6002.09 Sum
13 Count
 Units

57.2727272727273
9.21667550899002
67
#N/A
30.5682544777778
934.418181818182
-0.408770557186027
-0.928279623798765
87
3
90
630
11

Sales Revenue

472.336363636363
136.55045941318
167.44
#N/A
452.886638824171
205106.307625455
-0.722268506679418
0.888738356406602
1241.32
63.68
1305
5195.7
11
50000+125q = 175q Break Even(Mnfg vs Outsrcng)
50000
175000 175q Units Mfg. Outsource Outsource Benefit
100 62500 17500 45000
q 1000 200 75000 35000 40000
300 87500 52500 35000
400 100000 70000 30000
500 112500 87500 25000
600 125000 105000 20000
700 137500 122500 15000
800 150000 140000 10000
900 162500 157500 5000
175000 1000 175000 175000 0
100 12500 1100 187500 192500 -5000
200 12500 1200 200000 210000 -10000
300 12500 1300 212500 227500 -15000
400 12500 1400 225000 245000 -20000
500 12500 1500 237500 262500 -25000
237500 1600 250000 280000 -30000
1700 262500 297500 -35000
1800 275000 315000 -40000
1900 287500 332500 -45000
2000 300000 350000 -50000

Break Even
400000

350000

300000

250000

200000
175000
150000

100000

50000

0
100 200 300 400 500 600 700 800 900 10001100120013001400150016001700180019002000

Mfg. Outsource
 Mfg. Benefit
-45000
-40000
-35000 Benefit Comparison
-30000
60000
-25000
-20000
-15000 40000
-10000
-5000 20000
0
5000 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
10000 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200
15000 -20000
20000
25000 -40000
30000
35000 -60000
40000
45000 Outsource Benefit Mfg. Benefit
50000

the BE analysis btw Out. and Manu

indicates 1000 units as BEP point.

This means that beyond 1000 quantity

outsourcing apears costly to company and
below 1000 qty manuf. appears costly.

Therefore company should outsource its

unit till 1000 an manuf beyond 1000 units.
And get a Low total cost of supply.

Suppose the company wishes to manu.

1500 units what should be its total cost.

400150016001700180019002000
 00 00 00 00
17 18 19 20
Score of Cars on various parameters…RATINGS
Brand_Name Price_On_Road Interior_Exterior Technology Safety AfterSales_Service
1 4 2 1 2 4
1 3 2 1 2 3
1 3 1 3 1 1
1 3 1 3 1 1
1 2 2 3 1 1
1 2 1 2 1 2
1 7 7 7 7 5
1 3 3 2 1 2
1 2 1 1 1 1
1 2 1 1 2 1
1 6 5 6 6 7
1 3 2 1 2 2
1 2 3 1 2 2
1 7 5 5 7 4
1 5 7 7 7 5
1 2 2 2 2 2
1 3 2 3 1 2
1 2 1 1 1 1
1 2 1 1 1 1
1 2 1 2 1 3
1 1 1 1 1 1
1 1 3 2 1 4
1 2 1 2 1 2
1 3 1 1 1 1
1 3 1 1 1 1
1 2 1 1 1 1
1 5 5 2 6 4
1 4 1 1 1 1
1 3 1 1 1 4
1 4 1 1 1 3
1 2 1 2 1 2
Brand_Name Price_On_Road Interior_Exterior Technology Safety AfterSales_Service
2 1 1 2 2 1
2 3 2 2 3 3
2 4 3 3 2 2
2 4 3 3 2 2
2 4 5 5 5 5
2 1 1 3 3 1
2 3 1 1 1 1
2 1 1 1 1 1
2 5 6 5 6 4
2 2 1 1 2 2
2 2 1 1 2 2
2 1 7 7 3 1
2 3 2 1 1 2
2 3 1 1 1 2
2 4 1 1 2 3
 2 5 1 2 1 1
2 3 2 1 1 2
2 2 2 1 1 2
2 1 2 2 3 2
2 1 2 2 3 2
2 5 1 2 1 1
2 1 1 1 1 3
2 3 2 3 1 3
2 3 2 1 1 2
2 1 1 1 1 1
2 4 5 3 5 6
2 3 2 2 2 2
2 3 3 2 1 1
2 2 2 2 1 1
2 1 3 1 1 1
Brand_Name Price_On_Road Interior_Exterior Technology Safety AfterSales_Service
3 2 3 2 1 4
3 2 2 2 1 1
3 1 2 1 1 1
3 7 7 6 7 6
3 5 6 5 5 5
3 2 4 1 1 1
3 1 3 2 2 2
3 1 1 1 1 1
3 2 2 1 1 3
3 6 6 7 7 6
3 2 2 3 2 2
3 6 4 3 7 6
3 2 1 2 1 1
3 2 1 2 1 1
3 2 1 2 1 1
3 7 7 7 7 6
3 5 2 2 1 1
3 1 2 1 2 2
3 6 7 7 7 7
3 3 2 2 1 1
3 4 4 4 2 3
3 4 4 4 2 3
3 2 1 2 2 1
Driving_Pleasure Trust_on_Brand Advertising_and_Marketing Fuel_Efficiency Social_Status
3 2 2 5 5
2 2 1 5 1
1 1 3 1 1
1 1 3 1 1
1 1 4 2 2
1 2 3 4 2
7 6 7 6 7
2 4 2 3 1
1 1 5 2 2
1 2 2 1 1
6 7 4 6 7
1 2 3 2 1
3 1 2 2 3
6 5 3 7 5
7 7 2 4 6
1 2 3 4 4
1 1 3 2 1
1 1 1 1 1
1 1 1 1 1
1 3 2 1 1
1 1 1 1 1
2 3 3 2 2
1 1 2 2 3
1 2 4 1 2
1 2 4 1 2
1 1 1 1 3
4 4 3 5 1
1 1 3 5 1
1 1 3 1 3
2 4 3 2 3
1 1 3 2 2
Driving_Pleasure Trust_on_Brand Advertising_and_Marketing Fuel_Efficiency Social_Status
1 2 3 2 1
2 1 3 2 1
2 3 3 3 3
2 3 3 3 3
5 5 5 5 5
1 3 3 2 2
2 2 2 4 3
1 3 5 3 5
5 3 5 3 5
2 1 2 3 2
2 1 2 3 2
4 1 6 4 5
1 1 3 2 4
1 1 3 1 1
3 2 3 2 2
 1 1 3 1 4
2 1 2 2 3
1 1 1 2 1
2 2 2 2 2
2 2 2 2 2
1 1 3 1 4
1 3 1 1 3
3 3 4 3 3
2 2 3 2 2
1 1 1 2 1
5 4 5 4 3
3 3 4 2 3
1 1 2 1 4
1 2 3 2 2
3 1 3 1 4
Driving_Pleasure Trust_on_Brand Advertising_and_Marketing Fuel_Efficiency Social_Status
2 1 2 3 4
2 1 3 1 2
1 2 3 1 2
6 6 3 6 4
6 6 6 6 6
1 2 3 3 5
2 4 3 3 3
1 1 5 3 6
2 1 2 1 3
5 6 5 6 5
3 3 4 2 3
7 6 4 7 5
2 1 3 2 3
2 1 3 2 3
2 1 3 2 3
7 7 5 5 5
2 2 4 5 4
2 4 3 1 5
7 7 6 7 7
2 3 6 2 4
3 3 4 3 4
3 3 4 3 4
1 3 5 3 3
Quality Running_and_Maintenance _Cost
2 3 What are the average ratings by brand for the various
2 2 parameters?
1 3
1 3 What is the relationship between the ratings for the
2 2 brands individually?
1 4
7 7 What comments can you make on the average ratings
2 3 and relationship between the parameters for Brand 1
and Brand 2 respectively?
1 1
2 1
6 7
2 3
2 3
7 6
7 4
3 3
1 2
2 1
2 3
1 1
1 1
1 2
2 2
1 1
1 1
2 2
1 1
1 3
1 1
2 3
1 1
Quality Running_and_Maintenance _Cost
1 2
1 3
3 3
3 3
7 5
2 1
3 4
1 3
3 2
1 2
1 2
1 2
2 1
1 1
1 1
 1 1
3 2
1 2
2 2
2 2
1 1
3 1
2 2
3 3
1 1
3 5
2 3
2 2
2 2
1 1
Quality Running_and_Maintenance _Cost
2 1
1 2
1 1
7 7
6 6
1 1
2 1
1 3
1 1
6 6
2 2
6 5
1 0
1 2
1 2
6 6
2 4
1 2
7 7
2 2
3 3
3 3
2 3
 for the various

atings for the

average ratings
ers for Brand 1
 Price_On_Road Interior_Exterior Technology Safety
Price_On_Road 0.7538091205381 0.7053074423 0.8467679221
Interior_Exterior 0.753809120538 0.8257273202 0.9285693271
Technology 0.705307442335 0.8257273202085 0.7967857882
Safety 0.846767922113 0.9285693270782 0.7967857882
AfterSales_Service 0.677956314618 0.762658639595 0.6504481712 0.7451423503
Driving_Pleasure 0.838966760684 0.9490733728014 0.8255265576 0.9477807146
Trust_on_Brand 0.761796722357 0.8524232383409 0.7701573808 0.8382914282
Advertising_and_Marketing 0.460619780659 0.3499599901682 0.4481411724 0.3244874806
Fuel_Efficiency 0.763807528286 0.7001236287175 0.5521638786 0.7445727629
Social_Status 0.662769858075 0.6918090443634 0.7098984428 0.7086896834
Quality 0.75587794702 0.826823939519 0.8396686606 0.8625915796
Running_and_Maintenance _Cost 0.733497146709 0.6703616377303 0.7552546087 0.6731260884
Average Rating 3.064516129032 2.1612903225807 2.1935483871 2.0967741935
Rank 1 10 8 11
Average Correlation 0.723743322127 0.7555762962782 0.7162799476 0.7651641023
Adjusted Rating 11.09300290087 8.8423924916911 7.7313829899 8.9286783419
Adjusted Rank Err:522 Err:522 Err:522 Err:522
AfterSales_Service Driving_Pleasure Trust_on_Brand Advertising_and_Marketing Fuel_Efficiency
0.677956314618005 0.8389667606844 0.761796722357 0.460619780659162 0.76380752829
0.762658639595029 0.9490733728014 0.852423238341 0.349959990168203 0.70012362872
0.650448171221304 0.825526557584 0.770157380847 0.448141172379046 0.55216387856
0.745142350293811 0.9477807146136 0.838291428245 0.324487480640462 0.74457276294
0.8119433496795 0.817993502071 0.260918184741863 0.66650639816
0.811943349679518 0.882963386969 0.321197305846883 0.73742875815
0.817993502070637 0.8829633869693 0.321286731013511 0.63960757306
0.260918184741863 0.3211973058469 0.321286731014 0.29104403619
0.666506398158696 0.737428758149 0.639607573061 0.291044036189531
0.743553383828672 0.8013707461932 0.694582645364 0.401241293082361 0.60778302676
0.657704182716405 0.8896870068669 0.803228910518 0.26889342765645 0.65447611343
0.600775774188986 0.7461898191968 0.677131284808 0.374506675046958 0.71016195044
2.38709677419355 2.0645161290323 2.354838709677 2.7741935483871 2.67741935484
6 12 7 2 3
0.672327295555721 0.7956479798713 Err:522 0.347481461584039 0.64251596861
7.28500342511585 10.102743920674 Err:522 4.25151683065077 7.48961945075
Err:522 Err:522 Err:522 Err:522 Err:522
Social_Status Quality Running_and_Maintenance _Cost
0.6627698581 0.755877947 0.733497146708774
0.6918090444 0.8268239395 0.670361637730308
0.7098984428 0.8396686606 0.755254608717086
0.7086896834 0.8625915796 0.673126088354005
0.7435533838 0.6577041827 0.600775774188986
0.8013707462 0.8896870069 0.746189819196785
0.6945826454 0.8032289105 0.677131284808309
0.4012412931 0.2688934277 0.374506675046958
0.6077830268 0.6544761134 0.710161950441883
0.834335131 0.732774217446391
0.834335131 0.806881672773669
0.7327742174 0.8068816728
2.4516129032 2.1935483871 2.58064516129032
5 8 4
0.6898915884 0.7454698702 0.680060079583014
7.9056639918 8.6180303621 8.0660305157509
Err:522 Err:522 Err:522
Cost Of Transportation =
The current company from P M N with
warehouse 1 2 3 with one worehouse
PUNE Mumbai Nasik supply to only one city.
W1 500 420 400
W2 150 190 200 The company has apointed a manager
A, who allocated W1 to pune, W2-
W3 1300 280 250 Nasik, W3 to mum,
The company also given cost of
transportation per ton.
The weighted cost of transportation b/w
Scenario 1 Mngr A Warehouse and market currently is
Rs980 per TON
PUNE Mumbai Nasik
The company appoints a Analytics firm
W1 1 0 0 1 to examine whether this allocation is
W2 0 0 1 1 the best allocation i.e. is this allocation
W3 0 1 0 1 done at the lowest cost of distribution
1 1 1 b/w the warehouses to the markets

Rs/T
TC 980

Scenario 2 Company

PUNE Mumbai Nasik

W1 0 1 0 1
W2 1 0 0 1
W3 0 0 1 1
1 1 1

Rs/T
TC 820
any from P M N with
with one worehouse
e city.

apointed a manager
W1 to pune, W2-
m,
given cost of
r ton.
of transportation b/w
arket currently is

oints a Analytics firm

her this allocation is
n i.e. is this allocation
t cost of distribution
es to the markets

x
 a b c d e f
Buyers Pizza Ice cream Pasta Garlic Ice Tea Cold drinks
1 1 1 1 1
2 1 1 1
3 1 1 1
4 1 1 1 1
5 1 1 1 1
6 1 1 1 1
7 1 1 1 1 1
8 1 1 1 1
9 1 1 1
10 1 1 1
11 1 1
12 1 1 1
13 1 1
14 1 1 1
15 1 1 1
16 1 1 1 1 1
17 1 1 1 1
18 1 1 1 1
19 1 1 1
20 1 1 1
21 1 1 1 1
22 1 1 1
23 1 1 1
24 1 1 1
25 1 1
26 1 1 1
27 1 1 1 1
28 1 1 1 1 1
29 1 1
30 1 1 1
31 1 1
32 1 1 1 1 1
33 1 1 1
34 1 1 1
35 1 1
36 1 1 1
37 1 1 1
38 1 1 1 1
39 1 1 1 1
40 1 1 1
41 1 1
42 1
43
44 1 1 1
45 1 1
46 1 1 1
47 1 1 1 1
48 1 1 1
49 1 1 1
50 1 1
51 1 1 1 1
52 1 1 1
53 1 1 1 1
54 1 1
55 1 1
56 1 1 1
57 1 1
58 1 1
59 1 1 1 1
60 1 1 1 1
61 1 1 1
62 1 1 1
63 1 1 1
64 1 1 1
65 1 1
66 1 1
67 1 1 1
68 1 1 1
69 1 1
70 1 1 1 1
71 1 1 1
72 1 1 1 1
73 1 1 1
74 1 1 1 1
75 1 1 1
76 1 1 1
77 1 1
78 1 1
79 1 1
80 1 1
81 1 1 1
82
83 1 1 1 1
84 1 1 1
85 1 1 1
86 1 1 1 1
87 1 1
88 1 1 1
89 1 1 1
90 1 1 1 1
91 1 1 1
92 1 1
93 1 1
 94 1 1 1
95 1 1 1
96 1 1 1 1
97 1 1 1
98 1 1
99 1 1 1
100 1 1 1
101 1 1 1 1 1
102 1 1 1
103 1 1 1
104 1 1
105 1 1
106 1 1 1
107 1 1 1
Buyers Pizza Ice cream Pasta Garlic Ice Tea Cold drinks
1 1 0 1 0 1 1
2 1 0 0 1 0 1
3 1 1 0 1 0 0
4 1 0 0 1 1 1
5 1 0 0 1 1 1
6 0 0 1 1 1 1
7 1 0 1 1 1 1
8 1 0 0 1 1 1
9 0 1 0 1 1 0
10 1 0 0 1 1 0
11 1 0 0 0 0 1
The following
12 1 0 0 1 0 1 to a pizza sto
13 1 0 0 0 0 1 items that the
14 1 0 0 1 0 1 visit.
15 0 0 1 1 1 0
16 1 1 0 1 1 1 Tasks
17 1 0 0 1 1 1
18 1 0 0 1 1 1 Convert the d
Which Statis
19 1 0 1 0 0 1
to interpret th
20 0 0 1 1 1 0 What are you
21 1 0 1 1 1 0 recommenda
22 1 1 0 0 0 1 Company?
23 1 1 0 0 0 1
24 0 1 0 1 1 0
25 1 1 0 0 0 0
26 1 0 0 1 0 1
27 1 0 1 0 1 1
28 1 0 1 1 1 1
29 1 0 0 1 0 0
30 0 0 1 0 1 1
31 1 0 0 1 0 0
32 1 1 1 1 1 0
33 1 0 0 1 0 1
34 1 0 0 1 0 1
35 1 0 0 0 0 1
36 1 0 0 1 0 1
37 1 0 0 1 1 0
38 1 0 0 1 1 1
39 1 1 1 0 0 1
40 1 0 0 1 0 1
41 0 0 0 1 1 0
42 0 0 1 0 0 0
43 0 0 0 0 0 0
44 1 0 0 1 0 1
45 0 0 1 0 1 0
46 1 0 0 1 0 1
47 1 0 0 1 1 1
48 1 0 0 1 0 1
49 1 0 0 1 0 1
50 1 1 0 0 0 0
51 1 0 1 0 1 1
52 1 1 0 0 0 1
53 1 1 0 1 0 1
54 1 0 0 0 0 1
55 1 0 0 0 0 1
56 1 1 0 1 0 0
57 1 0 0 0 0 1
58 0 0 0 1 1 0
59 1 0 0 1 1 1
60 1 0 0 1 1 1
61 0 0 1 1 1 0
62 1 0 0 1 0 1
63 1 1 0 0 0 1
64 0 0 1 1 1 0
65 1 0 0 0 0 1
66 1 0 0 0 0 1
67 1 0 0 1 1 0
68 1 1 0 0 0 1
69 0 0 1 0 1 0
70 1 1 1 0 0 1
71 1 0 0 1 0 1
72 1 0 1 1 0 1
73 1 0 1 0 0 1
74 1 0 1 1 0 1
75 1 1 0 0 0 1
76 0 0 1 1 0 1
77 1 0 0 0 0 1
78 1 0 0 0 0 1
79 1 0 0 0 0 1
80 0 0 0 1 0 1
81 1 1 0 0 0 1
82 0 0 0 0 0 0
83 0 0 1 1 1 1
84 1 1 1 0 0 0
85 1 1 0 0 0 1
86 1 0 1 1 0 1
87 1 1 0 0 0 0
88 1 0 0 1 0 1
89 1 0 0 1 0 1
90 1 1 0 1 0 1
91 1 0 0 1 0 1
92 1 0 0 0 1 0
93 1 0 0 0 0 1
 94 1 0 0 1 0 1
95 1 0 0 1 0 1
96 1 0 1 1 0 1
97 1 1 0 1 0 0
98 1 0 0 0 0 1
99 1 0 0 1 1 0
100 0 1 1 0 1 0
101 1 0 1 1 1 1
102 1 0 0 1 0 1
103 0 1 0 1 1 0
104 1 0 0 0 0 1
105 1 0 0 0 0 1
106 1 0 0 1 0 1
107 0 0 1 1 1 0
 Pizza Ice cream Pasta Garlic Ice Tea Cold drinks
Pizza 0.050412 -0.37258 -0.0599 -0.40804 0.499538
Ice cream 0.050412 -0.0988 -0.2346 -0.14282 -0.2182
Pasta -0.37258 -0.0988 -0.05217 0.348673 -0.1376
Garlic -0.0599 -0.2346 -0.05217 0.290629 -0.06524
Ice Tea -0.40804 -0.14282 0.348673 0.290629 -0.35357
Cold drinks 0.4995384 -0.218204 -0.137605 -0.065242 -0.353568

The following is data collected by visitors

to a pizza store. The data indicates the
items that they purchased during their
visit.

Tasks

Convert the data to a relevant format.

Which Statistical technique you can use
to interpret the data?
What are your observations and
recommendations to the Pizza
Company?
City Area Pop 1980 Pop 1990 Pop 2000 Growth Food PersRoomWater Elec
Buenos Ai 700 9918 11448 12822 1.4 40 1.3 80 91
Dhaka 100 3290 6578 11511 7.2 63 2.4 60 85
Rio de Jan 650 8789 10948 12162 2.2 26 0.8 86 98
Sao Paolo 800 12101 18119 22552 4.1 50 0.8 100 100
Beijing 1680 9029 10867 14366 1.9 52 1.2 88 90
Shanghai 630 11739 13447 17407 1.4 55 2 95 95
Tianjin 400 7268 9249 12508 2.4 52 1.3 80 84
Cairo 21.4 6852 8633 10761 2.3 47 1.5 91 98
Bombay 60 8067 12223 18142 4.2 57 4.2 92 78
Calcutta 130 9030 10741 12675 1.8 60 3 51 63
Delhi 59.1 5559 8171 11692 3.9 40 3.1 50 81
Jakarta 59 5985 9206 13380 4.4 45 3.4 75 94
Osaka 200 9990 10482 10601 0.5 18 0.6 96 100
Tokyo 216 21854 25013 27956 1.4 18 0.9 100 100
Seoul 165 8283 10979 12949 2.9 34 2 100 100
Mexico Cit 250 13888 15085 16190 0.8 41 1.9 92 97
Lagos 40 4385 7742 13480 5.8 58 5.8 47 53
Karachi 353 5023 7943 11895 4.7 43 3.3 66 84
Manila 64 5966 8882 12582 4.1 38 3 89 93
Los Angel 1660 9523 11456 13151 1.9 12 0.5 91 98
New York 359 15601 16056 16645 0.3 16 0.5 99 100
Phones Vehicles
14 1000
2 600 What can be researched/
8 4000 investigated given the data?
16 4000
2 308 Offer your comments
4 148
4 200
4 939
5 588
2 500
5 1660
3 1380
42 4400
44 4400
22 2660
6 2500
1 500
2 650
9 510
35 8000
56 1780
City Area Pop 1980 Pop 1990 Pop 2000 Growth Food PersRoomWater Elec
Buenos Ai 700 9918 11448 12822 1.4 40 1.3 80 91
Dhaka 100 3290 6578 11511 7.2 63 2.4 60 85
Rio de Jan 650 8789 10948 12162 2.2 26 0.8 86 98
Sao Paolo 800 12101 18119 22552 4.1 50 0.8 100 100
Beijing 1680 9029 10867 14366 1.9 52 1.2 88 90
Shanghai 630 11739 13447 17407 1.4 55 2 95 95
Tianjin 400 7268 9249 12508 2.4 52 1.3 80 84
Cairo 21.4 6852 8633 10761 2.3 47 1.5 91 98
Bombay 60 8067 12223 18142 4.2 57 4.2 92 78
Calcutta 130 9030 10741 12675 1.8 60 3 51 63
Delhi 59.1 5559 8171 11692 3.9 40 3.1 50 81
Jakarta 59 5985 9206 13380 4.4 45 3.4 75 94
Osaka 200 9990 10482 10601 0.5 18 0.6 96 100
Tokyo 216 21854 25013 27956 1.4 18 0.9 100 100
Seoul 165 8283 10979 12949 2.9 34 2 100 100
Mexico Cit 250 13888 15085 16190 0.8 41 1.9 92 97
Lagos 40 4385 7742 13480 5.8 58 5.8 47 53
Karachi 353 5023 7943 11895 4.7 43 3.3 66 84
Manila 64 5966 8882 12582 4.1 38 3 89 93
Los Angel 1660 9523 11456 13151 1.9 12 0.5 91 98
New York 359 15601 16056 16645 0.3 16 0.5 99 100
Phones Vehicles Area Pop 1980 Pop 1990 Pop 2000
14 1000 Buenos Aires 0.603293 0.181047228 -0.03235912169 -0.40956
2 600 Dhaka -0.64214 -1.3804598714 -1.18948058153 -0.72134
8 4000 Rio de Janeiro 0.499507 -0.0849367061 -0.15116009293 -0.56652
16 4000 Sao Paolo 0.810866 0.6953456586 1.55268343655 1.904436
2 308 Beijing 2.6375 -0.0283945058 -0.17040585027 -0.04237
4 148 Shanghai 0.457993 0.6100611731 0.44260716131 0.680847
4 200 Tianjin -0.01942 -0.4432729008 -0.55484579319 -0.48424
4 939 Cairo -0.80529 -0.5412793813 -0.70120858975 -0.89971
5 588 Bombay -0.72517 -0.2550344921 0.15178238373 0.855646
2 500 Calcutta -0.57987 -0.0281589133 -0.20034369502 -0.44452
5 1660 Delhi -0.72704 -0.8459004857 -0.81098068717 -0.6783
3 1380 Jakarta -0.72724 -0.7455380801 -0.56506267671 -0.27686
42 4400 Osaka -0.43457 0.1980098881 -0.26188259812 -0.93776
44 4400 Tokyo -0.40136 2.9930793249 3.19071122795 3.18962
22 2660 Seoul -0.50722 -0.2041465118 -0.14379443271 -0.37936
6 2500 Mexico City -0.33078 1.1163494586 0.83179914308 0.391419
1 500 Lagos -0.76668 -1.1224860823 -0.91291192049 -0.25308
2 650 Karachi -0.11698 -0.9721780664 -0.86515393006 -0.63002
9 510 Manila -0.71687 -0.7500143376 -0.64204570607 -0.46664
35 8000 Los Angeles 2.595986 0.0879881899 -0.03045830615 -0.33132
56 1780 New York -0.10453 1.5199194135 1.06251062922 0.499628

Buenos Aires Dhaka Rio de Janeiro Sao Paolo

Buenos Aires -0.5240639939 0.32010036007 0.122316
Dhaka -0.52406 -0.43329262484 -0.30497
Rio de Janeiro 0.3201 -0.4332926248 0.338376
Sao Paolo 0.122316 -0.3049724467 0.33837576539
Beijing 0.724682 -0.0877622681 0.16305341206 0.171969
Shanghai 0.5145 -0.3109248966 -0.22552946933 0.302091
Tianjin 0.258868 0.465036423 -0.39568295295 -0.03212
Cairo 0.007823 0.2305526776 0.08999665778 -0.14379
Bombay -0.6094 0.4617782458 -0.82076068721 -0.24647
Calcutta -0.16 0.3674936977 -0.71903734332 -0.34298
Delhi -0.58253 0.7426571739 -0.40323182306 -0.55613
Jakarta -0.67546 0.7806664541 -0.38210250205 -0.49248
Osaka 0.290154 -0.6186678805 0.65052194559 0.042069
Tokyo 0.155377 -0.7454107592 0.19544428463 0.582434
Seoul -0.10143 -0.2393964687 0.46293034434 -0.07839
Mexico City 0.34193 -0.7439766033 0.24621928876 0.392223
Lagos -0.58734 0.6824224297 -0.70868726245 -0.52984
Karachi -0.49953 0.8588987094 -0.4395698164 -0.5718
Manila -0.54341 0.5603484897 -0.30933681366 -0.50081
Los Angeles 0.367969 -0.4790902916 0.86146967788 0.203738
New York 0.4564 -0.7820940235 0.30842046588 0.24263
Growth Food PersRoomWater Elec Phones Vehicles
-0.79243 -0.07706 -0.55512 -0.13094 0.109021 0.023169 -0.46717
2.403526 1.41174 0.236441 -1.27667 -0.36466 -0.70666 -0.66614
-0.35161 -0.98329 -0.91492 0.212779 0.661648 -0.34174 1.025093
0.695343 0.570244 -0.91492 1.014792 0.819541 0.144807 1.025093
-0.51692 0.699705 -0.62708 0.327352 0.030075 -0.70666 -0.81139
-0.79243 0.893896 -0.0514 0.728359 0.424808 -0.58502 -0.89098
-0.2414 0.699705 -0.55512 -0.13094 -0.4436 -0.58502 -0.86511
-0.2965 0.376053 -0.4112 0.499212 0.661648 -0.58502 -0.49752
0.750446 1.023357 1.531726 0.556499 -0.91728 -0.5242 -0.67211
-0.57202 1.217548 0.668203 -1.79225 -2.10148 -0.70666 -0.71589
0.585138 -0.07706 0.740163 -1.84954 -0.68044 -0.5242 -0.13888
0.860651 0.246592 0.956044 -0.41737 0.345861 -0.64584 -0.27815
-1.28835 -1.50113 -1.05884 0.785646 0.819541 1.726099 1.224062
-0.79243 -1.50113 -0.84296 1.014792 0.819541 1.847737 1.224062
0.034111 -0.46544 -0.0514 1.014792 0.819541 0.50972 0.358547
-1.12305 -0.01233 -0.12336 0.556499 0.582701 -0.46338 0.278959
1.632089 1.088088 2.68309 -2.0214 -2.89095 -0.76748 -0.71589
1.025959 0.117131 0.884083 -0.93295 -0.4436 -0.70666 -0.64127
0.695343 -0.20652 0.668203 0.384639 0.266915 -0.28093 -0.71091
-0.51692 -1.88951 -1.1308 0.499212 0.661648 1.300366 3.014784
-1.39856 -1.63059 -1.1308 0.957506 0.819541 2.577564 -0.07918

Beijing Shanghai Tianjin Cairo Bombay Calcutta Delhi Jakarta Osaka Tokyo
0.724682 0.5145 0.258868 0.007823 -0.6094 -0.16 -0.58253 -0.67546 0.290154 0.155377
-0.08776 -0.31092 0.465036 0.230553 0.461778 0.367494 0.742657 0.780666 -0.61867 -0.74541
0.163053 -0.22553 -0.39568 0.089997 -0.82076 -0.71904 -0.40323 -0.3821 0.650522 0.195444
0.171969 0.302091 -0.03212 -0.14379 -0.24647 -0.34298 -0.55613 -0.49248 0.042069 0.582434
0.544235 0.590622 -0.00871 -0.20646 0.00671 -0.33556 -0.33623 -0.25253 -0.28148
0.544235 0.543437 0.271266 0.188977 0.098498 -0.55392 -0.26215 -0.30463 0.144559
0.590622 0.543437 0.4442 0.32662 0.367705 -0.03943 0.130901 -0.53348 -0.58421
-0.00871 0.271266 0.4442 0.045591 -0.32274 -0.18838 0.36979 0.104965 -0.41796
-0.20646 0.188977 0.32662 0.045591 0.570957 0.386548 0.570163 -0.73077 -0.30969
0.00671 0.098498 0.367705 -0.32274 0.570957 0.558714 0.205639 -0.64393 -0.27437
-0.33556 -0.55392 -0.03943 -0.18838 0.386548 0.558714 0.751127 -0.48991 -0.54175
-0.33623 -0.26215 0.130901 0.36979 0.570163 0.205639 0.751127 -0.51658 -0.65523
-0.25253 -0.30463 -0.53348 0.104965 -0.73077 -0.64393 -0.48991 -0.51658 0.42743
-0.28148 0.144559 -0.58421 -0.41796 -0.30969 -0.27437 -0.54175 -0.65523 0.42743
-0.39274 -0.24508 -0.33718 0.584774 -0.30452 -0.77677 -0.3681 0.035939 0.730663 0.085688
-0.03772 0.582254 -0.20602 0.112844 -0.20042 -0.14996 -0.61289 -0.46883 0.276318 0.658482
-0.18806 -0.28643 0.195995 -0.27086 0.749063 0.773717 0.835076 0.631925 -0.70711 -0.536
-0.02536 -0.33466 0.264239 0.049027 0.534953 0.403874 0.846095 0.854879 -0.66062 -0.79551
-0.2975 -0.18025 0.118324 0.539961 0.51654 -0.15179 0.359965 0.818346 -0.23875 -0.55458
0.21228 -0.39415 -0.46016 -0.27827 -0.8136 -0.53256 -0.3057 -0.54763 0.685972 0.208074
-0.14864 0.055472 -0.48111 -0.17069 -0.57239 -0.49346 -0.66301 -0.72963 0.77526 0.780752
 Seoul Mexico City Lagos Karachi Manila Los AngelesNew York
-0.10143 0.34193 -0.58734 -0.49953 -0.54341 0.367969 0.4564
-0.2394 -0.74398 0.682422 0.858899 0.560348 -0.47909 -0.78209
0.46293 0.246219 -0.70869 -0.43957 -0.30934 0.86147 0.30842
-0.07839 0.392223 -0.52984 -0.5718-0.50081 0.203738 0.24263
-0.39274 -0.03772 -0.18806 -0.02536 -0.2975 0.21228 -0.14864
-0.24508 0.582254 -0.28643 -0.33466 -0.18025 -0.39415 0.055472
-0.33718 -0.20602 0.195995 0.264239 0.118324 -0.46016 -0.48111
0.584774 0.112844 -0.27086 0.049027 0.539961 -0.27827 -0.17069
-0.30452 -0.20042 0.749063 0.534953 0.51654 -0.8136 -0.57239
-0.77677 -0.14996 0.773717 0.403874 -0.15179 -0.53256 -0.49346
-0.3681 -0.61289 0.835076 0.846095 0.359965 -0.3057 -0.66301
0.035939 -0.46883 0.631925 0.854879 0.818346 -0.54763 -0.72963
0.730663 0.276318 -0.70711 -0.66062 -0.23875 0.685972 0.77526
0.085688 0.658482 -0.536 -0.79551 -0.55458 0.208074 0.780752
0.11943 -0.53402 -0.28802 0.422938 0.277952 0.418044
0.11943 -0.5849 -0.74877 -0.4397 0.007275 0.459261
-0.53402 -0.5849 0.819138 0.365735 -0.52339 -0.71167
-0.28802 -0.74877 0.819138 0.651788 -0.40878 -0.81077
0.422938 -0.4397 0.365735 0.651788 -0.47129 -0.4014
0.277952 0.007275 -0.52339 -0.40878 -0.47129 0.3996
0.418044 0.459261 -0.71167 -0.81077 -0.4014 0.3996
Retailer
Sales in Statistical
(000) measures Values

24 Skew 0.25901404 0
35 Max 58 10
17 Min 12 20
21 Range 46 30
24 Mean 32.4 40
37 Std. D- (S) 12.6715595 50
26 x 40
46
58
30
32
13 Approx.
12 Stergis rule(K) 5.29339899 5
38
41 Rice rule (K) 5.42883523 5
43
44 8.69006854
27 8.47327245
53
27
 8

7
Class Frequency
6

10 0-10 0
5
20 10-20 3 Solution
30 20-30 7 P(x) 0.725669676

Axis Title
40 30-40 4 1-P(x) 0.274330324 4
50 40-50 4
60 50-60 2 3

0
0
0-10
 Retailers
8

7
7

5
Axis Title

4 4
4

3
3

2
2

0
0
0-10 10-20 20-30 30-40 40-50 50-60

Axis Title
Max 58
Min 12 Rice 2*N^(1/3)
Range 46 Stergis 1+3.3log(n)
N 20 Rice k 5.428835
Stergis 5.293399
Sales in a region skew 0.416
12 32 22 22 55 28 7 18 K 6.84 X
35 14 20 31 12 30 17 22 max 55 P(X)
10 20 35 34 10 15 12 20 min 2 1-P(x)
5 35 35 28 34 2 2 5 sd 12.95 40
19 18 15 2 32 46 28 47 mean 22.15

Use Rice rule and calculate the class intervals. 0 10 0-10 8

10 20 10-20 13
Is the data normally distributed? 20 30 20-30 7
30 40 30-40 9
Calculate all relevant statistics 40 50 40-50 2
50 60 50-60 1
(Round off at last stage of class width)

Chart T
14 13

12

10
8
8 7

0
0-10 10-20 20-30
 Discount
33
0.799 0.05 31.96
0.201 0.08 8.04
40

Chart Title
13

2
1

10-20 20-30 30-40 40-50 50-60

OrderDate Region City Category Product TotalPrice
Use Rice rule and calculate the class intervals
43843 East Boston Cookies Arrowroot 82.84
(USE TOTAL PRICE column) for both data
43861 East Boston Cookies Arrowroot 78.48 sets
43879 East Boston Cookies Arrowroot 93.74
43976 East Boston Cookies Arrowroot 58.86 Is the data normally distributed?
44060 East Boston Cookies Arrowroot 67.58
44081 East Boston Cookies Arrowroot 61.04
Calculate all relevant statistics
44093 East New York Cookies Arrowroot 239.8
(Round off at last stage of class width)
44102 East Boston Cookies Arrowroot 176.58
44117 East New York Cookies Arrowroot 488.32 Also use descriptive statistics and comment on
44129 East Boston Cookies Arrowroot 87.2 the comparative results of sales dispersion for
44147 West San Diego Cookies Arrowroot 224.54 both products
44168 West San Diego Cookies Arrowroot 303.02
44189 East New York Cookies Arrowroot 516.66
44195 West San Diego Cookies Arrowroot 180.94
44198 East Boston Cookies Arrowroot 69.76
44222 East Boston Cookies Arrowroot 113.36
44231 West Los AngeleCookies Arrowroot 126.44
44252 West Los AngeleCookies Arrowroot 65.4
44290 East Boston Cookies Arrowroot 78.48
44317 West Los AngeleCookies Arrowroot 167.86
44344 West San Diego Cookies Arrowroot 78.48
44386 East New York Cookies Arrowroot 80.66
44404 West Los AngeleCookies Arrowroot 43.6
44413 West San Diego Cookies Arrowroot 196.2
44437 East Boston Cookies Arrowroot 296.48
44461 East Boston Cookies Arrowroot 87.2
44476 East New York Cookies Arrowroot 381.5
44485 East Boston Cookies Arrowroot 189.66
44515 East New York Cookies Arrowroot 318.28
44524 East Boston Cookies Arrowroot 303.02
44548 East Boston Cookies Arrowroot 74.12
culate the class intervals
column) for both data

istributed?

statistics

ge of class width)

statistics and comment on

ts of sales dispersion for
OrderDate Region City Category Product TotalPrice
Use Rice rule and calculate the class intervals
43843 East Boston Cookies Arrowroot 82.84
(USE TOTAL PRICE column) for both data
43861 East Boston Cookies Arrowroot 78.48 sets
43879 East Boston Cookies Arrowroot 93.74
43976 East Boston Cookies Arrowroot 58.86 Is the data normally distributed?
44060 East Boston Cookies Arrowroot 67.58
44081 East Boston Cookies Arrowroot 61.04
Calculate all relevant statistics
44093 East New York Cookies Arrowroot 239.8
(Round off at last stage of class width)
44102 East Boston Cookies Arrowroot 176.58
44117 East New York Cookies Arrowroot 488.32 Also use descriptive statistics and comment on
44129 East Boston Cookies Arrowroot 87.2 the comparative results of sales dispersion for
44147 West San Diego Cookies Arrowroot 224.54 both products
44168 West San Diego Cookies Arrowroot 303.02
44189 East New York Cookies Arrowroot 516.66
44195 West San Diego Cookies Arrowroot 180.94 skew 1.290393
44198 East Boston Cookies Arrowroot 69.76 max 516.66
44222 East Boston Cookies Arrowroot 113.36 min 43.6
44231 West Los AngeleCookies Arrowroot 126.44 mean 171.9387
44252 West Los AngeleCookies Arrowroot 65.4 sd 126.3366
44290 East Boston Cookies Arrowroot 78.48 N 31
44317 West Los AngeleCookies Arrowroot 167.86 k 6.282761
44344 West San Diego Cookies Arrowroot 78.48 Class Widt 75.29492
44386 East New York Cookies Arrowroot 80.66
44404 West Los AngeleCookies Arrowroot 43.6 0 100
44413 West San Diego Cookies Arrowroot 196.2 100 200
44437 East Boston Cookies Arrowroot 296.48 200 300
44461 East Boston Cookies Arrowroot 87.2 300 400
44476 East New York Cookies Arrowroot 381.5 400 500
44485 East Boston Cookies Arrowroot 189.66 500 600
44515 East New York Cookies Arrowroot 318.28
44524 East Boston Cookies Arrowroot 303.02
44548 East Boston Cookies Arrowroot 74.12
culate the class intervals
column) for both data

istributed?

statistics

ge of class width)

statistics and comment on

ts of sales dispersion for Chart Title
16 15
14

12

10

8 7
6
4
4 3
2 1 1
0
0-100 15 0-100 100-200 200-300 300-400 400-500 500-600
100-200 7
200-300 3
300-400 4
400-500 1
500-600 1
 1

500-600
Respondents willingness to pay is recorded as under

WTP max 35
35 min 10 Willingness to pay for the Hide n Seek bisc
collected from a sample of 107 online and
30 avg 16.70093
30 n 107 Tasks:
30 skew 1.385209
28 sd 4.895573 Create a price schedule and calculate the
27 histogram (Consider difference of Rs. 5 as
27
27 What single price would you recommend t
26 producing the biscuit was Rs. 18? (Best st
- TC = Profits)
25
25 Consider upper (Max) price point to be Rs
25
24
22
Steps
20
20 Sort the Data from Lowest to Highest
20 Prepare the histogram
19 Calculate the market share on a reverse cu
19 Calculate Revenue on basis of actual custo
19 the mid point formula
19
19
19
19
19
18
18
18
18
18
18
17
17
17
17
17
17
17
17
17
17
17
17
17
17
17
16
16
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16
16
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15
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15
15
15
15
15
15
15
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15
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14
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13
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13
13
13
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12
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12
12
12
12
11
10
10
10
10
10
10
10
10
 pay for the Hide n Seek biscuit pack of 200 gms, was 0 5
a sample of 107 online and offline users)
5 10
10 15
15 20
schedule and calculate the WTP by price point using the 20 25
nsider difference of Rs. 5 as class interval) 25 30
30 35
rice would you recommend the brand in case the marginal cost
biscuit was Rs. 18? (Best strategy is to maximize revenue (TR

er (Max) price point to be Rs. 40. Chart Title

50
45
45
40
40
35
rom Lowest to Highest
stogram 30
market share on a reverse cumulative basis 25
enue on basis of actual customers in the Class Interval using 20
ormula 15
10 8
5
5
0
0
Class In- 0-5 5-10 10-15 15-20 20-2
terval
 WTP Cum fre
Class Interval Freq 35
0-5 0 30
5-10 8 30
10-15 45 30
15-20 40 28
20-25 5 27
25-30 8 27
30-35 1 27
total 107 26
25
25
Chart Title 25
24
45 22
40 20
20
20
19
19
19
19
8 8 19
5 19
1 19
5-10 10-15 15-20 20-25 25-30 30-35 19
18
18
18
18
18
18
17
17
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17
17
17
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17
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16
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16
16
16
16
15
15
15
15
15
15
15
15
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15
14
14
14
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12
12
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10
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10
pareto index 1.160964
market A 1.222338 3.291667
market B 1.371576 2.484848
 Source of Manu Errors No of Defects Cum. Percentage
1 56% Poor Alignment 223 56% 17%
2 20% Paint flaw 78 75% 33%
3 9% Bad Weld 34 84% 50%
4 6% missing part 25 90% 67%
5 5% Cracked case 21 95% 83%
6 5% Electrical Short 19 100% 100%
Total 400

Source of Manu Errors

250 100% 100%
223
95% 90%
90%
200 84% 80%
75% 70%
150 60%
56%
50%
100 78 40%
30%
50 34 20%
25 21 19 10%
0 0%
Poor Paint flaw Bad Weld missing Cracked Electrical
Alignment part case Short

No of Defects Cum. Percentage

ercentage
Pareto Index
2.26 1 3.26 1.4503511428
1.68 1 2.68 1.9075693421
 Retailer Sales
No. Area A Area B Area A
1 1578 3598 44% 1 1578
2 150 1200 35% 2 1260
3 89 436 4% 3 150
4 93 396 3% 4 95
5 91 396 3% 5 93
6 43 306 3% 6 91
7 1260 305 2% 7 89
8 95 154 1% 8 43
9 42 141 1% 9 43
10 43 124 1% 10 43
11 39 92 1% 11 42
12 42 90 1% 12 42
13 43 45 1% 13 39
14 45 3608
15 45
16 40
No. Area B
49% 1 3598
16% 2 1200
6% 3 436
5% 4 396
5% 5 396
4% 6 306
4% 7 305
2% 8 154
2% 9 141
2% 10 124
1% 11 92
1% 12 90
1% 13 45
1% 14 45
1% 15 45
1% 16 40
7413
Cum.
44% 8% Pareto Index
79% 15% 5.11 1 6.11 1.109476194
83% 23% 3.59 1 4.59 1.192369383
85% 31%
88% 38%
91% 46%
93% 54%
94% 62%
95% 69%
97% 77%
98% 85%
99% 92%
100% 100%

Cum.
49% 6%
65% 13%
71% 19% Pareto Index
76% 25% 3.04 1 4.04 1.256088726
81% 31% 2.60 1 3.60 1.340258694
85% 38%
90% 44%
92% 50%
94% 56%
95% 63%
96% 69%
98% 75%
98% 81%
99% 88%
99% 94%
100% 100%
 Retailer Sales
1800 98% 99% 100%
94% 95% 97%
1578 91% 93% 90%
1600 88%
83% 85%
1400 79% 80%
1260
70%
1200
60%
1000
50%
800 44%
40%
600
30%
400 20%
200 150 95 93 91 89 43 43 43 42 42 39 10%
0 0%
1 2 3 4 5 6 7 8 9 10 11 12 13

Area A Cum.

4000 98% 99% 99% 100%

100%
94% 95% 96% 98%
3500 90% 92% 90%
85%
81% 80%
3000 76%
71% 70%
2500 65%
60%
2000 49% 50%
40%
1500
30%
1000
20%
500 10%
0 0%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Area B Cum.
Original Data

Customer Profit %
Customer 1 9026
Customer 2 8700
Customer 3 8300
Customer 5 5000
Customer 6 1800
Customer 8 1500
Customer 11 500
Customer 10 900
Customer 9 1200
Customer 12 200
Customer 4 7900
Customer 13 100
Customer 18 -2300
Customer 17 -700
Customer 19 -3100
Customer 20 -5400
Customer 7 1700
Customer 14 60
Customer 15 50
Customer 16 10
 Original Data
%customer Profit% Level
Customer Profit Cum Profit 0% 0.00% 100%
1 Customer 1 9026 9026 5% 25.46% 100%
2 Customer 2 8700 17726 10% 50.01% 100%
3 Customer 3 8300 26026 15% 73.42% 100%
4 Customer 4 7900 33926 20% 95.71% 100%
5 Customer 5 5000 38926 25% 109.82% 100%
6 Customer 6 1800 40726 30% 114.90% 100%
7 Customer 7 1700 42426 35% 119.69% 100%
8 Customer 8 1500 43926 40% 123.92% 100%
9 Customer 9 1200 45126 45% 127.31% 100%
10 Customer 10 900 46026 50% 129.85% 100%
11 Customer 11 500 46526 55% 131.26% 100%
12 Customer 12 200 46726 60% 131.82% 100%
13 Customer 13 100 46826 65% 132.11% 100%
14 Customer 14 60 46886 70% 132.27% 100%
15 Customer 15 50 46936 75% 132.42% 100%
16 Customer 16 10 46946 80% 132.44% 100%
17 Customer 17 -700 46246 85% 130.47% 100%
18 Customer 18 -2300 43946 90% 123.98% 100%
19 Customer 19 -3100 40846 95% 115.23% 100%
20 Customer 20 -5400 35446 100% 100.00% 100%

Chart Title
140%

120%

100%

80%

60%

40%

20%

0%
0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100
%

%customer Profit% Level

 Profit Max 132.44%

0% 95% 100
%
Customer ID Profit Customer ID Profit cum Profit
64 82 1 14 95 95
84 -85 2 9 94 189
9 94 3 57 92 281
12 65 4 54 91 372
2 48 5 59 91 463
90 -14 6 44 89 552
3 82 7 4 87 639
89 -58 8 29 87 726
20 69 9 15 87 813
68 60 10 65 86 899
43 54 11 47 84 983
52 77 12 28 84 1067
51 54 13 46 83 1150
13 68 14 64 82 1232
18 81 15 3 82 1314
96 -55 16 18 81 1395
85 -7 17 38 81 1476
48 72 18 5 78 1554
7 68 19 52 77 1631
40 52 20 45 75 1706
74 -56 21 63 74 1780
24 48 22 30 74 1854
4 87 23 48 72 1926
6 59 24 58 72 1998
34 62 25 60 71 2069
37 63 26 67 70 2139
88 -10 27 11 70 2209
72 -66 28 20 69 2278
5 78 29 27 69 2347
33 50 30 31 69 2416
27 69 31 17 69 2485
16 63 32 32 69 2554
31 69 33 50 69 2623
67 70 34 1 69 2692
47 84 35 13 68 2760
49 55 36 7 68 2828
69 60 37 55 67 2895
61 58 38 12 65 2960
23 48 39 36 65 3025
14 95 40 35 65 3090
76 -72 41 70 64 3154
11 70 42 37 63 3217
17 69 43 16 63 3280
28 84 44 22 63 3343
36 65 45 34 62 3405
54 91 46 19 62 3467
 83 -25 47 68 60 3527
86 -87 48 69 60 3587
92 -42 49 6 59 3646
63 74 50 41 59 3705
94 -65 51 61 58 3763
42 54 52 25 56 3819
70 64 53 49 55 3874
10 50 54 53 55 3929
35 65 55 43 54 3983
19 62 56 51 54 4037
38 81 57 42 54 4091
79 -57 58 40 52 4143
57 92 59 8 52 4195
29 87 60 26 52 4247
60 71 61 33 50 4297
56 46 62 10 50 4347
77 -10 63 66 49 4396
15 87 64 2 48 4444
80 -77 65 24 48 4492
59 91 66 23 48 4540
32 69 67 39 48 4588
22 63 68 21 47 4635
30 74 69 56 46 4681
45 75 70 62 46 4727
66 49 71 81 -2 4725
8 52 72 85 -7 4718
73 -74 73 88 -10 4708
39 48 74 77 -10 4698
25 56 75 90 -14 4684
81 -2 76 78 -15 4669
98 -19 77 97 -17 4652
55 67 78 98 -19 4633
75 -71 79 99 -22 4611
50 69 80 83 -25 4586
41 59 81 93 -35 4551
82 -63 82 100 -39 4512
65 86 83 91 -40 4472
99 -22 84 92 -42 4430
95 -49 85 95 -49 4381
53 55 86 96 -55 4326
1 69 87 74 -56 4270
21 47 88 79 -57 4213
100 -39 89 89 -58 4155
26 52 90 87 -58 4097
71 -91 91 82 -63 4034
78 -15 92 94 -65 3969
93 -35 93 72 -66 3903
91 -40 94 75 -71 3832
62 46 95 76 -72 3760
87 -58 96 73 -74 3686
58 72 97 80 -77 3609
97 -17 98 84 -85 3524
44 89 99 86 -87 3437
46 83 100 71 -91 3346
Customer Profit % Level
0% 0% 100%
1% 3% 100%
2% 6% 100%
3% 8% 100%
4% 11% 100%
5% 14% 100%
6% 16% 100%
7% 19% 100%
8% 22% 100%
9% 24% 100%
10% 27% 100%
11% 29% 100%
12% 32% 100%
13% 34% 100%
14% 37% 100%
15% 39% 100%
16% 42% 100%
17% 44% 100%
18% 46% 100%
19% 49% 100%
20% 51% 100%
21% 53% 100%
22% 55% 100%
23% 58% 100%
24% 60% 100%
25% 62% 100%
26% 64% 100%
27% 66% 100%
28% 68% 100%
29% 70% 100%
30% 72% 100%
31% 74% 100%
32% 76% 100%
33% 78% 100%
34% 80% 100%
35% 82% 100%
36% 85% 100%
37% 87% 100%
38% 88% 100%
39% 90% 100%
40% 92% 100%
41% 94% 100%
42% 96% 100%
43% 98% 100%
44% 100% 100%
45% 102% 100%
46% 104% 100%
47% 105% 100%
48% 107% 100%
49% 109% 100%
50% 111% 100%
51% 112% 100%
52% 114% 100%
53% 116% 100%
54% 117% 100%
55% 119% 100%
56% 121% 100%
57% 122% 100%
58% 124% 100%
59% 125% 100%
60% 127% 100%
61% 128% 100%
62% 130% 100%
63% 131% 100%
64% 133% 100%
65% 134% 100%
66% 136% 100%
67% 137% 100%
68% 139% 100%
69% 140% 100%
70% 141% 100%
71% 141% 100%
72% 141% 100%
73% 141% 100%
74% 140% 100%
75% 140% 100%
76% 140% 100%
77% 139% 100%
78% 138% 100%
79% 138% 100%
80% 137% 100%
81% 136% 100%
82% 135% 100%
83% 134% 100%
84% 132% 100%
85% 131% 100% Chart Title
86% 129% 100% 160%
87% 128% 100% 140%
88% 126% 100% 120%
89% 124% 100% 100%
90% 122% 100%
80%
91% 121% 100%
60%
92% 119% 100%
93% 117% 100% 40%
94% 115% 100% 20%
95% 112% 100% 0%
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65

Customer Profit %
 60%
40%
20%
0%
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65
96% 110% 100%
97% 108% 100%
98% 105% 100% Customer Profit %
99% 103% 100%
100% 100% 100%
 Chart Title

3 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101

tomer Profit % Level

3 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101

tomer Profit % Level

Qtr Qtr1 Qtr2 Qtr3 Qtr4 Product East North South West
Product A 26 16 27 23 Product A 17 35 11 29
Product B 39 47 31 30 Product B 27 55 28 37
Product c 211 41 19 22 Product c 34 31 21 17
Product D 17 27 16 37 Product D 23 25 27 22
Product E 44 33 24 18 Product E 31 29 31 28
Product F 41 13 37 37 Product F 20 15 41 52

Region East North South West

Qtr1 33 55 65 35
Qtr2 33 42 49 53
Qtr3 53 41 25 35
Qtr4 33 52 20 62
Product Region Year Sales
Product 2 North 2013 110
Product 3 South 2016 78
Product 6 South 2015 95
Product 3 South 2013 130
Product 3 West 2015 92
Product 4 East 2016 71
Product 1 North 2011 42
Product 5 South 2012 135
Product 5 South 2013 78
Product 3 South 2014 65
Product 3 North 2014 26
Product 2 North 2011 135
Product 5 East 2014 138
Product 1 South 2011 31
Product 2 South 2015 99
Product 4 West 2014 105
Product 3 South 2011 51
Product 5 North 2014 61
Product 5 South 2013 98
Product 5 North 2011 129
Product 4 North 2011 138
Product 3 North 2016 118
Product 5 North 2011 66
Product 2 South 2011 33
Product 6 South 2012 58
Product 6 North 2012 145
Product 3 West 2016 25
Product 2 North 2011 111
Product 4 East 2016 94
Product 1 East 2011 50
Product 4 East 2011 125
Product 3 East 2016 28
Product 3 West 2016 69
Product 6 North 2012 83
Product 4 East 2016 18
Product 5 West 2014 25
Product 1 West 2011 133
Product 2 East 2015 85
Product 6 West 2016 107
Product 1 North 2015 22
Product 5 South 2015 89
Product 6 North 2011 22
Product 5 South 2013 86
Product 4 West 2014 134
Product 2 West 2016 40
Product 4 East 2016 108
Product 6 North 2016 131
Product 6 South 2013 133
Product 2 West 2013 99
Product 4 West 2013 62
Product 3 North 2011 109
Product 2 North 2012 88
Product 2 South 2014 34
Product 6 North 2016 131
Product 3 South 2015 21
Product 4 North 2012 118
Product 3 West 2015 104
Product 5 North 2015 34
Product 1 North 2012 141
Product 5 North 2016 107
Product 2 North 2012 134
Product 4 North 2013 23
Product 1 West 2014 33
Product 3 East 2014 106
Product 2 East 2011 114
Product 4 East 2016 120
Product 3 West 2011 73
Product 5 North 2012 18
Product 5 West 2014 14
Product 1 East 2014 75
Product 6 West 2014 78
Product 2 South 2016 102
Product 3 East 2014 103
Product 5 South 2011 106
Product 6 East 2012 77
Product 6 South 2013 122
Product 3 South 2013 70
Product 4 East 2012 72
Product 1 West 2016 97
Product 5 North 2016 130
Product 4 North 2016 13
Product 2 North 2013 23
Product 1 North 2012 42
Product 4 North 2015 10
Product 6 West 2012 93
Product 6 North 2011 99
Product 2 West 2011 58
Product 4 East 2012 133
Product 3 South 2013 43
Product 2 West 2011 77
Product 6 East 2015 51
Product 4 South 2014 47
Product 2 East 2011 89
Product 5 East 2016 81
Product 4 West 2011 78
Product 3 East 2015 108
Product 4 North 2016 82
Product 4 North 2013 52
Product 6 West 2014 76
Product 4 North 2016 123
Product 5 West 2014 93
Product 3 North 2016 61
Product 5 North 2012 57
Product 4 South 2016 121
Product 2 North 2016 92
Product 1 North 2016 97
Product 5 West 2016 39
Product 6 South 2015 72
Product 2 South 2011 104
Product 1 East 2014 59
Product 3 East 2013 114
Product 2 North 2016 109
Product 1 West 2012 117
Product 5 North 2012 64
Product 6 North 2016 75
Product 4 West 2011 23
Product 1 South 2011 117
Product 3 East 2016 25
Product 3 West 2013 93
Product 6 West 2016 117
Product 4 South 2015 127
Product 4 North 2016 70
Product 5 North 2014 75
Product 2 West 2012 22
Product 3 South 2011 98
Product 6 East 2015 103
Product 2 East 2012 74
Product 1 East 2013 117
Product 6 East 2015 140
Product 5 East 2016 147
Product 3 South 2014 66
Product 5 South 2014 91
Product 4 East 2015 86
Product 3 South 2011 21
Product 5 North 2012 55
Product 4 East 2012 143
Product 4 West 2013 135
Product 1 West 2013 15
Product 4 North 2015 20
Product 3 West 2014 12
Product 4 East 2016 100
Product 6 North 2015 50
Product 5 East 2013 149
Product 6 North 2015 110
Product 3 North 2013 61
Product 3 West 2014 84
Product 6 West 2014 125
Product 2 South 2014 103
Product 2 South 2014 137
Product 4 South 2015 39
Product 1 North 2013 111
Product 4 South 2013 117
Product 3 South 2013 49
Product 4 South 2012 37
Product 6 East 2015 43
Product 5 West 2011 100
Product 6 South 2011 95
Product 5 West 2012 147
Product 5 North 2011 41
Product 1 East 2011 82
Product 6 West 2015 14
Product 5 West 2013 149
Product 3 South 2011 109
Product 2 West 2011 142
Product 5 West 2014 65
Product 2 South 2015 60
Product 4 North 2014 86
Product 2 South 2011 68
Product 2 West 2015 49
Product 3 North 2013 106
Product 5 South 2016 133
Product 2 North 2014 39
Product 5 West 2015 129
Product 5 South 2015 103
Product 3 East 2011 135
Product 3 East 2014 28
Product 5 East 2014 105
Product 2 West 2015 17
Product 3 North 2011 101
Product 5 North 2011 118
Product 2 West 2014 75
Product 5 West 2014 134
Product 3 East 2012 57
Product 4 North 2013 87
Product 3 East 2011 126
Product 1 South 2011 67
Product 6 West 2015 49
Product 6 North 2014 90
Product 6 East 2013 136
Product 5 West 2012 75
Product 2 North 2013 124
Product 6 East 2014 77
Product 5 South 2011 123
Product 5 East 2013 117
Product 1 East 2013 113
Product 3 North 2016 13
Product 1 West 2011 20
Product 5 North 2014 121
Product 6 South 2016 56
Product 4 East 2011 130
Product 6 North 2015 21
Product 3 South 2012 123
Sum of Sales Year
Product 2011 2012 2013 2014 2015 2016
Product 1 542 300 356 167 22 194
Product 2 931 318 356 388 310 343
Product 3 823 180 666 490 325 417
Product 4 494 503 476 372 282 920
Product 5 683 551 677 922 355 637
Product 6 216 456 391 446 748 617

Sum of Sales Column Labels Sum of Sales

Row Labels East North South West Row Labels
Product 1 496 455 215 415 Product 1
Product 2 362 965 740 579 Product 2
Product 3 830 595 924 552 Product 3
Product 4 1200 822 488 537 Product 4
Product 5 737 1076 1042 970 Product 5
Product 6 627 957 631 659 Product 6
 Sum of Sales Column Labels
Row Labels East North South West
2011 851 1111 1023 704
2012 556 945 353 454
2013 746 697 926 553
2014 691 498 543 1053
2015 616 267 705 454
2016 792 1352 490 494

Column Labels
East North South West
12% 9% 5% 11%
9% 20% 18% 16%
20% 12% 23% 15%
28% 17% 12% 14%
17% 22% 26% 26%
15% 20% 16% 18%
Product 2011 2012 2013 2014 2015 2016 Year East North South West
Product 1 542 300 356 167 22 194 2011 851 1111 1023 704
Product 2 931 318 356 388 310 343 2012 556 945 353 454
Product 3 823 180 666 490 325 417 2013 746 697 926 553
Product 4 494 503 476 372 282 920 2014 691 498 543 1053
Product 5 683 551 677 922 355 637 2015 616 267 705 454
Product 6 216 456 391 446 748 617 2016 792 1352 490 494

Product East North South West

Product 1 496 455 215 415
Product 2 362 965 740 579
Product 3 830 595 924 552
Product 4 1200 822 488 537
Product 5 737 1076 1042 970
Product 6 627 957 631 659

Region East North South West

Product 1 12% 9% 5% 11%
Product 2 9% 20% 18% 16%
Product 3 20% 12% 23% 15%
Product 4 28% 17% 12% 14%
Product 5 17% 22% 26% 26%
Product 6 15% 20% 16% 18%
Sales Funnel Multiplicative Model

Delhi Mumbai
Awareness Aware 438 333
Qualify Needs 51 65
Discovery Initial Meeting 45 22
Define needs 22 15
Evaluation Make Offer 22 14
Intent Final Proposal sent 10 5
Purchase Sales 5 4
Loyalty Repeat Sales 2 2

Delhi Mumbai
Awareness Aware 100% 100%
Qualify Needs 12% 20%
Discovery Initial Meeting 88% 34%
Define needs 49% 68%
Evaluation Make Offer 100% 93%
Intent Final Proposal sent 45% 36%
Purchase Sales 50% 80%
Loyalty Repeat Sales 40% 50%

Delhi Mumbai
Awareness Aware 1533 666
Qualify Needs 178.500 130.000
Discovery Initial Meeting 157.500 44.000
Define needs 77.000 30.000
Evaluation Make Offer 77.000 28.000
Intent Final Proposal sent 35.000 10.000
Purchase Sales 17.500 8.000
Loyalty Repeat Sales 7.000 4.000
7 4
0.00E+00 0.00E+00
Chennai
296 Q- How many potential customers have to be aware in case the
95 repeat purchase target is set to be ?
Delhi 7
45
Mumbai 4
29 Chennai 11
28
16
11
7

Chennai
100%
32%
47%
64%
97%
57%
69%
64%

Chennai
465 CV
149.240
70.693
45.557
43.986
25.135
17.280
10.997
11 ESS
1.14E-05 0.00 Minimize
 Delhi Mumbai Chennai
Aware 438 333 296 355.6667 485.00
Qualify Needs 51 65 95 70.33333 20% 95.90909
Initial Meeting 45 22 45 37.33333 53% 50.90909
Define needs 22 15 29 22 59% 30
Make Offer 22 14 28 21.33333 97% 29.09091
Final Proposal sent 10 5 16 10.33333 48% 14.09091
Sales 5 4 11 6.666667 65% 9.090909
Repeat Sales 2 2 7 3.666667 55% 5 Goal

All India= Target=5

5
 Mkt Share
Units Revenue Units Revenue
Zipper 25 375000 50% 40%
Twister 10 200000 20% 21%
Aone 7.5 187500 15% 20%
Bowlz 5 125000 10% 13%
Chien 2.5 50000 5% 5%
Market Total 50 937500 Correlation 98%
SD 16.56217 296331.7 95% Shown only 5% data is not releatable
Unit share and market share is highly correlated

Chart Title
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
0% 10% 20% 30% 40% 50% 60%
highly correlated
 Revenue 4-Firm HHI Units HHI
Sunfeast 300 51% 0.258546 5 22% 0.047259
Britania 200 34% 85% 0.11491 5 22% 0.047259
Good day 50 8% 0.007182 5 22% 0.047259
Parle G 25 4% 0.001795 4 17% 0.030246
Tiger 10 2% 0.000287 3 13% 0.017013
Oreo 5 1% 7.182E-05 1 4% 0.00189
Sum 590 0.382792 23 0.190926
Firms Sales Firms Sales MKT Shr Share
1 20 2 40 40%
2 40 1 20 20% 59%
3 15 3 15 15%
4 8 6 10 10%
5 2 4 8 8%
6 10 7 6 6%
7 6 5 2 2%
Sum 101
4Firms HHI
0.156847
0.285714 0.039212
0.022057
0.009803
0.006274
0.003529
0.000392
0.238114
 Surgeon purchase our scissor 1500
Surgeon purchase our brand 650
Total Surgeon 2000

Market Pen. 0.75

Brand Pen 0.325

Penetration Share 0.433333

 Operators Apr’18 Sep ’20 Operators Apr’18
Vodafone
Airtel 308.7 326.6 438.8
Idea
Vodafone Idea 438.8 295.5 Airtel 308.7
Jio 196.2 404.1 Jio 196.2
BSNL 112.4 118.9 BSNL 112.4
Total Base 1056.1 1145.1 Total Base 1056.1

Operators Sep ’20

Jio 404.1
Airtel 326.6
Vodafone
295.5
Idea
BSNL 118.9
Total Base 1145.1
Mkt Shr. 4Firm HHI

42% 0.172633

29% 71% 0.08544

19% 0.034513
11% 0.011327

0.303914

Mkt Shr. 4Firm HHI

35% 0.124535
29% 64% 0.081348

26% 0.066593
10% 0.010781

0.283257
 FAST FOOD
Pizza Fries Burgers Population
55 170 90 315
Papa J 21
P Hut 29
Dominos 5
KFC 55 22
Mac 60 55
Burger King 55 13
55 170 90
0.38181818182

Market Penetration 17% 54% 29%

Brand Penetration.
Papa J 7%
P Hut 9%
Dominos 2%
KFC 17% 7%
Mac 19% 17%
Burger King 17% 4%

Penetration Share Pizza Fries Burgers

Papa J 38%
P Hut 53%
Dominos 9%
KFC 32% 24%
Mac 35% 61%
Burger King 32% 14%
Market Share 100% 100% 100%
Dummy Beer Numeric Reach Analysis_BNG Sales of Cases (All Brands of Beer)
Bottle
330 650
Atria Hotel BLR 72 0
Sunnys BLR 13 0
Pub World BLR 33 0
37th Cresent BLR 0 0
3 Quarter Chinese BLR 0 0
Century Club 0 0
CHANCERY BLR 0 195
GUZZLERS IN BLR 0 0
Fusion Lounge BLR 0 463
Jimmis (Garuda) BLR (Bull & Bush) 0 0
Couch BLR 0 0
Solitaire BLR 0 371
Koshy's BLR 0 359
Gold Finch BLR 0 0
HARIMA BLR 0 82
Woodlands Hotel BLR 0 0
Purple Haze (Residency) BLR 0 0
Zero G BLR 0 0
St Marks Hotel BLR 0 0
Catholic Club 0 357
PRESS CLUB 0 0
Max Hyper Malleshwaram BLR 0 120
CHANCERY Pavillion BLR 0 215
BBQ Nation ( Lido Mall ) 0 145
Bangalore Club BLR 0 0
Bowring Institute 0 45
Sharloc BLR 0 0
Watson's ( vasanth nagar ) 0 0
Nikkis Pub BLR 0 260
Bangalore Golf Club 0 407
Sarayu BLR 0 370
1522 White Horse BLR 0 228
Rasa BLR 0 0
Lalit Ashoka BLR 0 0
Jayamahal Estate BLR 0 0
Neel BLR 0 0
Opus BLR 0 0
Take 5 Unit 1 BLR 0 245
Indiranagar Club 0 0
Millers 46 BLR 0 238
Copper Chimney BLR 0 484
Zuca BLR 0 0
Fortune- Cosmos BLR 0 0
Jimmis Indiranagar BLR 0 464
Aishwarya palace BLR 0 0
Downtown BLR 0 370
Cosmopolitan Club 0 471
Clark Exotica BLR 0 0
ANJAPPAR 5 UP 6 BLR 0 0
PURPLE HAZE KORMANGLA BLR 0 0
Koramangala club 0 219
Ramee Guest Line BLR 0 224
Max Hyper (Koramangala) BLR 0 0
MAX- B.G.Road BLR 0 0
Bay Leaf BLR 0 0
Spencer's Koramangala BLR 0 0
Manipal County BLR 0 441
Via milano BLR 0 0
Aloft Hotels ( Sarjapur road ) 0 0
lacasa Jayanagar BLR 0 0
Tilt ( Koramangala ) BLR 0 358
NGV Club 0 295
Dolphin BLR 0 5
JALSA BLR 0 361
MAIN LAND CHINA BLR 0 190
KGA Club BLR 0 0
Spice Curry BLR 0 291
Purple Haze (marathhalli) BLR 0 0
Evoma BLR 0 500
Golden Palms BLR 0 0
Spagitty Kitchen(Koramangala) BLR 0 386
Firangi Pani BLR 0 352
Shakti Hills Resorts BLR 0 245
The club BLR 0 341
Rayal Comforts BLR 0 245
H village BLR 0 203
Brigade Millenium BLR 0 248
TOTAL- MYSORE ROAD ( Closed ) 0 338
Inchara BLR 0 47
Hotel President BLR 0 0
Upper Deck BLR 0 0
Barbeque Nation 2 (Indira Ngr) BLR 0 0
MASALA BLR 0 365
J Cubes BLR 0 144
HOTEL ASHLESH 0 308
BLUE WATER 0 375
Vintage pub-Udupi 0 0
PARADISE BAR MALPE 0 391
R/S Enterprises 0 0
TAJ GARDEN RETRITE HOTEL 0 375
LIQUID LOUNGE BAR 0 0
AMAZON BAR 0 0
Manohar Ameen 0 158
FROTH ON TOP 0 0
GRAND MOURYA 0 0
Purple haze (Purple Inn -Mysore) 0 0
BHOPIES PUB 0 153
HOTEL METROPOLE 0 0
PAI VISTA 0 0
REGAALIS MYSORE 27 283
PALM MEADOWS BLR 65 0
HOTEL MONARCH 61 0
HOTEL PARKLANE 75 0
Roost Hotel 98 126
Ramashree california BLR 40 0
HOTEL RITZ 37 0
CHITHRAVANA RESORT 0 484
EMBASSY BAR 19 276
OLIVE GARDEN 40 138
SERAI 0 100
MAYURA HOYSALA 29 25
Khansama BLR 19 172
Oakwood BLR 0 0
Sanchos BLR 0 200
RETRO BLR 81 0
Guhantara BLR 0 0
S Hotel BLR 84 214
LALITHAMAHAL PALACE 0 0
FORTUNE VALLEY VIEW 0 0
TALLUR BAR MANIPAL 0 87
Secretary Golf Club 0 335
Ebony Bristro BLR 0 0
FW- MG BLR 0 460
GOLDFINCH 1 0
HOTEL MOTIMAHAL 51 253
Taj Manjuran 0 421
MAYUR NETRAVATHI BAR 0 0
CHILLIES BLR 0 0
Angsana Resorts BLR 0 14
Pebbles BLR 0 0
Road House 54 318
KSCA BLR 0 376
Tamarind BLR 27 294
ORANGE COUNTY 84 271
JUNGLE RESORT 0 0
Club Cabana BLR 12 0
Punjab Grill BLR 63 0
FW - 7th Blk ( Closed ) 9 35
Opus Creek BLR 76 0
Holiday Palms BLR 96 0
RK Resort BLR 0 0
Banjara BLR 0 10
SANDESH DE PRINCE 80 320
YOUNG ISLAND RESORT 92 0
Hotel spoorthi Prince 0 15
Haba Nero (ITPL) BLR 76 0
MAYA (ALIBI) BLR 0 0
Khaaja Chowk BLR 0 277
Ware Abouts 84 0
Ujwal p shetty 0 282
ORANGECOUNTY-RESORT 67 0
Puma Club BLR 85 203
Bell BLR 0 0
Citrine BLR 0 34
Four point sharton BLR 0 0
COCONUT GROOVE BLR 0 0
Indijoe (CH ) BLR 0 0
Century hotel BLR 0 0
M2S - JP/ TOTAL AIRPORT RD BLR 0 86
NO LIMITS BLR 0 0
Royal Orchid White Field BLR 25 0
ZAIKA BLR 0 478
zuri BLR 0 0
Toscano BLR 0 0
Deja Vu BLR 0 190
HOTEL ROOPA 86 0
GOLDEN LANDMARK HOTEL 0 0
Legends of Rock BLR 0 0
BARBEQUE NATION Kormangala BLR 69 0
Royal Orchid - Yelhanka BLR 5 0
Hotel Leela Palace BLR 26 286
Taj Vivanta, MG Road BLR 2 487
The Park BLR 16 140
The OBEROI BLR 33 0
Le Meridien BLR 46 0
Windsor Manor BLR 0 0
Royal Orchid - Manipal Centre BLR 86 201
Spencer's BLR 0 406
Regalis BLR 0 0
Tandoor BLR 79 0
Taj Gateway BLR 0 0
Olive BLR 6 47
Mainland China Church Stree BLR 85 222
Le Rock BLR 0 0
Ameeba(ITPL) BLR 45 0
Metro Cash & Carry (Kankpura) BLR 1 64
Country club BLR 0 173
Royal Orchid Hotel ( Old Airport Rd ) BLR 33 0
Up Beat BLR 0 0
RADHA HOMETEL BLR 66 0
Sports Bar BLR 0 0
Spencer's Indira Nagar BLR 0 87
J P Fortune wite field BLR 10 0
Taj Westend BLR 23 449
Metro Cash & Carry Y'PUR BLR 0 18
Infusion BLR 13 337
World Cuisine Network BLR 97 289
Cirrus BLR 0 268
STONES BLR 0 199
JUKE BOX BLR 0 204
Crowne Plaza BLR 43 0
extreem SPORTS BAR BLR 11 31
Bhagini-K R Puram BLR 0 28
Amanvana Resort 0 137
RUCHI THE PRINCE 0 0
SILENT SHORES 78 0
KEDKANI RESORT 0 213
Radha Regent BLR 0 189
May Flower Hotel 95 303
Banana Beach Bar BLR 0 0
Kriishton Suites BLR 12 0
Maharaja -Kushal ngr 20 0
Spencer'S Sarajapur BLR 0 102
PRIDE HOTEL BLR 12 0
V-Inn hotel-Jigani BLR 0 0
Windflower ROK 33 230
ITC Gardenia BLR 71 175
Musem Inn BLR 0 235
GRILL HOUSE BLR 2 425
Lemon Tree BLR 15 0
Cuppa Bangalore (Runway 70) 98 0
Lords Plaza BLR 68 0
WOODSTOCK BLR 0 204
SLK restaurant 26 0
Oval bar BLR 3 0
Muse Bangalore 0 276
Pizzaria ( Closed ) 74 458
ADARSH HAMILTON BLR 54 483
SPAR - Mangalore 0 167
OCEAN PEARL HOTEL 84 6
Boot Leggar BLR 56 179
Mercure BLR 0 455
Guttu 0 105
Royal Orchid 4 448
Blue Peacock Ventures BLR 0 0
Watson's BLR 92 0
LA MARVELLA BLR 0 485
Elite Royal BLR 0 270
LA CASA (Banasawadi) BLR 0 0
La Casa Sajapur Road BLR 59 1
Brewberry BLR 0 0
Fortune-Celestial BLR 44 58
Filling Station BLR 0 0
Clarion BLR (Lemon Tree Whitefield) 0 125
Soho Bar and Grill BLR 0 0
Brew Sky BLR 0 0
City Bar BLR 0 0
Maya International 15 0
Keys BLR 0 0
PERI DOT INN 0 347
Cloud Bar BLR (Fisherman Wharf) 49 167
Aloft Hotels BLR 0 243
Mahattan Hotels BLR 59 479
Coral Tree BLR 36 126
Golden Grill BLR 72 0
Cibo esca BLR 18 0
Casa De Bengaluru BLR 0 0
Hotel Maharaja 8 35
Eden Park BLR 96 0
ENIGMA BLR 0 0
Bhagini Sakarnagar BLR 0 0
Calypso BLR 47 103
Grigliato Restaurant BLR 53 0
FORTUNE HOTEL 0 338
Parika BLR 0 321
Lemon Tree (St John's Rd) BLR 76 0
Windflower Resorts BLR 0 0
La Classic BLR 0 0
LOVE SHACK (HIPPI TANDOORI) BLR 1 0
ROYAL ORCHID CENTRAL 25 470
Sheraton (May 2011) BLR 0 0
Toit BLR 0 0
Svenska BLR 0 443
E Zone BLR 0 303
Rewind BLR 0 0
DUG OUT BLR 0 0
TGIF BLR 74 53
Jimmis Jayangar BLR 59 458
Sunny's Indiranagar BLR (Bricklane) 0 0
R & B pecos BLR 0 0
Mojos BLR 0 52
pecos BLR 0 5
Movenpick ( June 2011) BLR 0 0
TGIF LIDO BLR 65 0
Mother Cluckers BLR 0 0
Smoke House Deli Bangalore 37 144
Hardrock Café BLR 38 130
Taj Yeshwanthpur BLR 17 193
F Bar BLR 76 439
Park Plaza(marhtahalli) BLR 63 0
Bikkers & Guzzlers Pub (Just another pub) BLR 51 0
Shitakea (Bangalore Central) BLR 0 245
Alila BLR 0 151
Shiro BLR 0 0
Black Jack BLR 18 468
Oye Amristar BLR 0 361
THE MARK BLR 38 391
Main Land China (Koramangala) BLR 14 269
Moscow Mule BLR 5 0
Chairmans club Jade BLR 0 0
Key's (White Field) BLR 0 280
Doff BLR 0 164
Eat @ Bangalore 0 397
Elim Resorts BLR 98 0
Peacock BLR 0 0
Novetel/ibis( June 2011) BLR 0 287
OYSTER BAY 58 462
GoldFinch Retreat BLR 53 0
Ranoosh/VKL Resorts BLR 0 0
Ameeba(ITPL) BLR 81 350
Island BLR 0 0
I am Monkey BLR 37 0
Beer Joint Pub BLR 0 316
Mocholic BLR 0 305
Jimis Koramangala BLR 0 0
Citrus BLR 73 0
Halycon BLR 0 353
Chillies ( Whitefield ) BLR 30 0
California Pizza ( Whitefield ) Blr 0 453
THE QUORUM HOTEL 98 0
London Street 0 0
Golfshire BLR 38 215
Bhakasura BLR 0 294
The Paul BLR 0 0
Fishermen Walf BLR 36 40
Mango Mist BLR 50 199
BBQ Nation ( White Field ) BLR 61 0
SOLITAIRE (HSR LAYOUT) BLR 8 81
Kanua Bangalore 52 0
Plan B loaded BLR 0 481
Total (Koramangala) BLR 0 387
Total Sarjapur BLR 20 0
Haba Nero (Indiranagar) BLR 8 0
TAJ GATEWAY MADIKERI 0 13
Tilt 2012 BLR 0 496
Bhagini Pavilion BLR 43 288
THAMARA, MADIKERI 18 0
Mishmash Bangalore 0 27
Tao Terrace Bangalore 0 418
Samarkhand BLR 10 0
Bhagini (Banaswadi) BLR 73 129
Kakori BLR 100 412
D3 (Hrudays' D3) Closed 98 0
AROMAS OF CHINA BLR 0 457
Ohris BLR 41 52
Barleys Bangalore 51 0
Marrriot BLR 0 357
Lounge 579 BLR 0 25
Barbeque Nation JP Nagar BLR 0 0
Punjabi By Nature 40 0
copper chimney In orbit mall BLR 79 188
Gopub BLR 61 154
Fenny BLR 0 276
Main Land China 0 0
Zaica ( Indiranagar ) BLR 35 0
Malgudi BLR 94 0
Studio Bar BLR 0 0
Bhagas BEL Road (25 Mar) BLR 0 128
COUNTRY INN HOTEL 0 0
President Hotel 0 0
1522 Kormangala 19 143
black pearl BLR 0 0
Indijoe Retro (OM RD) BLR 38 461
Prost BLR 0 0
Foodworld ( Vidyaranyapura ) BLR 0 139
RUH BLR 37 360
Cheers Coorg ( Closed ) 73 494
Newscafe Bangalore 0 0
One day licence 0 0
Humming Tree BLR 0 0
Bak Bak BLR (25th Hour) 0 103
Palazo BLR 0 114
Oriental Cuisines BLR 0 199
Zaica (June 10) 0 0
Zaffran BLR 2 313
Ibis Hotel Hosur BLR 0 12
ICON CLUB BLR 0 0
Abhimaani vasathi BLR 32 0
Total Mahadevapura BLR 0 0
Ista Hotel BLR (Hyatt) 83 95
Spar Old Madras Road BLR (Auchan) 20 0
Mahesh Lunch Home BLR 0 0
Taj Vivanta ITPL BLR 5 354
JW Marriott UB City BLR 0 0
Counter Culture BLR 4 175
The Platter BLR 0 83
100FT BLR 0 0
Euphoria BLR 49 0
Ritz Carlton BLR 54 201
copper chimney Phoenix mall BLR 54 444
Glass House BLR 0 0
Loft 38 BLR 0 166
Punjab Time BLR 47 0
Plan B BLR 0 0
Guhea BLR 11 0
Super pub(Tumkur) 44 0
South Indies Ventures BLR 23 0
Elango's BLR 13 406
Windmill Crafts Bangalore 42 6
The Pint Room BLR 84 0
Barebones 62 0
Club Mahindra, Virajpet 65 35
Fiat Café BLR 0 0
Mai-tai Bangalore 0 28
Monkey Bar Bangalore 0 25
Blimey Bangalore 6 0
Arbor Brewering Company Bangalore 73 365
Davnam Suites BLR 0 93
Cable Car Bangalore 38 0
Easy Tiger Kormangala 35 0
Bakasur Sarjapur BLR 52 0
Absolute Barbecues BLR 72 0
Premium Port Lounge Management Company Pvt Ltd 0 113
Fire House BLR 80 291
Xtreme Sports Bar 19 0
Skye BLR 0 0
Hilton Bangalore 38 0
THE LOCAL KAMANNA HALLI BLR 0 0
Habanero Kormangala ( kor ) BLR 0 0
Tap Water BLR 0 0
Blistering barnacles - Marathalli 0 0
Food world ( banaswadi ) 0 375
Mr.Hong BLR 0 0
Jugs BLR 0 0
P V R Bluo BLR 0 213
Big Pitcher Blr 61 0
Gillys Blr 0 12
Berrys ( Sarjapur road ) 0 0
Ibis, Richmond Town 0 0
Country INN & Suites Hotel 0 0
Food world ( Shadashivnagar ) 0 202
FAVA BLR 78 0
Social BLR 0 0
Regalis BLR 74 171
Serafina BLR 0 188
Indigo Live BLR 14 0
Howard Johnson Hotel BLR 13 134
High Ultra Lounge BLR 9 202
California Pizza ( Indiranagar ) Blr 0 233
CLUB MAHINDRA 0 135
Mavens Blr 93 0
What the F Blr 0 271
Soho Bar and Grill ( Kormangala ) 51 0
ITC Fortune PF Road 82 226
RELIANCE MART- WHITEFIELD BLR 0 314
Chameleon Indiranagar 57 162
Chillies Indiranagar 0 384
Zengi Restro Bar 23 0
Bar 380 Degree BLR 61 105
Taste of India BLR 0 424
Harry's Pub Phoenix Mall 12 265
Metro (Hosur Road) 0 0
Bakasur ( Kormangala ) 92 0
Total Rajajinagar 0 135
Blue Moustache BLR 0 190
Duet Pub BLR 15 0
Studio Bar 2 71 59
Reliance Market 64 0
Best Club 0 0
Jamuna Bar & Restaurant 0 0
Chefs Gallery 0 0
Soda Bottle Opener 0 0
Tiger Bar 0 0
Mangrove 41 153
SPAR Elements Mall 77 0
Blue Frog Bangalore 0 0
Hotel Radisson Blue 0 0
Beer Café 96 0
One day licence 0 0
Beer Café 0 0
Under Doggs 61 276
Barebones 0 291
Shngrilla Hotel 84 364
Hangover 0 64
Watson's ( JP Nagar ) 0 178
Three Dots & A Dash 0 64
Punjabi By Nature 0 253
Aloft Hotels ( Sarjapur road ) 76 419
One day licence 0 388
The Black pearl 0 257
Roots 14 27
Beer Café- Koramanagala 0 0
Sherlock’s Pub – Indiranagar 18 0
Happy Brew 42 0
Russh 0 82
Cases (All Brands of Beer) Calculate the relevant numeric reach for the given data
Can
330 500
25 33 130.00
0 20 33.00
0 39 72.00
54 0 54.00 Total 485
43 0 43.00 Present 443
23 50 73.00
67 0 262.00 Overall Presence 91% Total presence of brand
0 0 0.00
0 0 463.00 Presence of each SKU in those 91%
29 0 29.00 330 650 330
0 0 0.00 188 239 248
58 0 429.00
41 0 400.00 NR of SKU 42% 54% 56%
25 0 25.00
0 0 82.00
0 0 0.00
0 0 0.00
0 0 0.00
2 0 2.00
35 0 392.00
0 0 0.00
31 0 151.00
0 0 215.00
46 0 191.00
33 0 33.00
1 0 46.00
22 0 22.00
31 0 31.00
0 0 260.00
0 0 407.00
0 0 370.00
43 0 271.00
0 0 0.00
0 0 0.00
52 0 52.00
0 0 0.00
14 0 14.00
0 0 245.00
11 0 11.00
11 0 249.00
33 0 517.00
70 0 70.00
15 0 15.00
46 0 510.00
3 0 3.00
33 0 403.00
0 0 471.00
0 0 0.00
0 0 0.00
18 0 18.00
0 0 219.00
8 0 232.00
5 0 5.00
71 0 71.00
1 0 1.00
7 0 7.00
0 0 441.00
63 0 63.00
0 0 0.00
0 0 0.00
0 0 358.00
0 0 295.00
34 0 39.00
0 0 361.00
58 0 248.00
0 0 0.00
0 0 291.00
21 0 21.00
37 0 537.00
0 0 0.00
0 0 386.00
0 0 352.00
5 0 250.00
2 0 343.00
0 0 245.00
0 0 203.00
15 0 263.00
46 0 384.00
0 0 47.00
0 0 0.00
67 0 67.00
0 0 0.00
0 0 365.00
45 0 189.00
0 0 308.00
32 0 407.00
15 0 15.00
0 0 391.00
20 0 20.00
0 0 375.00
5 0 5.00
24 0 24.00
43 0 201.00
30 0 30.00
48 0 48.00
67 0 67.00
0 0 153.00
58 0 58.00
40 0 40.00
0 0 310.00
8 0 73.00
0 0 61.00
0 0 75.00
0 0 224.00
0 0 40.00
0 0 37.00
42 0 526.00
0 0 295.00
0 0 178.00
43 0 143.00
42 0 96.00
19 0 210.00
20 0 20.00
0 0 200.00
0 0 81.00
1 0 1.00
0 0 298.00
8 0 8.00
19 0 19.00
40 0 127.00
0 0 335.00
0 0 0.00
42 0 502.00
74 0 75.00
38 0 342.00
24 0 445.00
16 0 16.00
0 0 0.00
0 0 14.00
2 0 2.00
19 0 391.00
32 0 408.00
29 0 350.00
12 0 367.00
0 0 0.00
0 0 12.00
34 0 97.00
46 0 90.00
40 0 116.00
0 0 96.00
0 0 0.00
0 0 10.00
0 0 400.00
68 0 160.00
0 0 15.00
0 0 76.00
0 0 0.00
29 0 306.00
0 0 84.00
0 0 282.00
0 0 67.00
13 0 301.00
48 0 48.00
70 0 104.00
0 0 0.00
36 0 36.00
0 0 0.00
0 0 0.00
31 0 117.00
23 0 23.00
66 0 91.00
0 0 478.00
0 0 0.00
0 0 0.00
14 0 204.00
21 0 107.00
19 0 19.00
0 0 0.00
13 0 82.00
38 0 43.00
0 0 312.00
42 0 531.00
0 0 156.00
10 0 43.00
40 0 86.00
0 0 0.00
43 0 330.00
0 0 406.00
12 0 12.00
49 0 128.00
0 0 0.00
16 0 69.00
0 0 307.00
0 0 0.00
25 0 70.00
0 0 65.00
0 0 173.00
15 0 48.00
63 0 63.00
66 0 132.00
48 0 48.00
16 0 103.00
64 0 74.00
69 0 541.00
0 0 18.00
47 0 397.00
7 0 393.00
41 0 309.00
38 0 237.00
63 0 267.00
9 0 52.00
39 0 81.00
0 0 28.00
0 0 137.00
14 0 14.00
32 0 110.00
45 0 258.00
0 0 189.00
59 0 457.00
52 0 52.00
0 0 12.00
0 0 20.00
0 0 102.00
6 0 18.00
14 0 14.00
0 0 263.00
38 0 284.00
63 0 298.00
0 0 427.00
28 0 43.00
0 0 98.00
0 0 68.00
0 0 204.00
64 0 90.00
6 0 9.00
0 0 276.00
51 0 583.00
0 0 537.00
54 0 221.00
72 0 162.00
0 0 235.00
0 0 455.00
0 0 105.00
65 0 517.00
0 0 0.00
0 0 92.00
0 0 485.00
47 0 317.00
0 0 0.00
0 0 60.00
32 0 32.00
0 0 102.00
75 0 75.00
14 0 139.00
0 0 0.00
0 0 0.00
56 0 56.00
0 0 15.00
14 0 14.00
0 0 347.00
23 0 239.00
0 0 243.00
44 0 582.00
0 0 162.00
0 0 72.00
73 0 91.00
61 0 61.00
52 0 95.00
0 0 96.00
63 0 63.00
12 0 12.00
0 0 150.00
11 0 64.00
26 0 364.00
33 0 354.00
0 0 76.00
41 0 41.00
0 0 0.00
65 0 66.00
0 0 495.00
50 0 50.00
7 0 7.00
16 0 459.00
0 0 303.00
65 0 65.00
0 0 0.00
0 0 127.00
6 0 523.00
0 0 0.00
0 0 0.00
0 0 52.00
0 0 5.00
0 0 0.00
0 0 65.00
2 0 2.00
69 0 250.00
0 0 168.00
74 0 284.00
39 0 554.00
0 0 63.00
0 0 51.00
0 0 245.00
0 0 151.00
0 0 0.00
70 0 556.00
0 0 361.00
0 0 429.00
0 0 283.00
33 0 38.00
1 0 1.00
23 0 303.00
0 0 164.00
72 0 469.00
0 0 98.00
50 0 50.00
0 0 287.00
49 0 569.00
0 0 53.00
46 0 46.00
0 0 431.00
4 0 4.00
0 0 37.00
50 0 366.00
72 0 377.00
0 0 0.00
0 0 73.00
0 0 353.00
0 0 30.00
26 0 479.00
0 0 98.00
41 0 41.00
0 0 253.00
34 0 328.00
7 0 7.00
5 0 81.00
0 0 249.00
0 0 61.00
0 0 89.00
67 0 119.00
35 0 516.00
0 0 387.00
0 0 20.00
16 0 24.00
0 0 13.00
0 0 496.00
59 0 390.00
0 0 18.00
72 0 99.00
69 0 487.00
0 0 10.00
0 0 202.00
0 0 512.00
0 0 98.00
28 0 485.00
0 0 93.00
51 0 102.00
0 0 357.00
0 7 32.00
0 14 14.00
0 0 40.00
7 68 342.00
14 0 229.00
49 0 325.00
0 71 71.00
0 38 73.00
0 0 94.00
2 73 75.00
0 0 128.00
34 43 77.00
10 0 10.00
0 68 230.00
45 15 60.00
0 24 523.00
53 0 53.00
62 0 201.00
0 8 405.00
24 0 591.00
40 65 105.00
28 72 100.00
12 0 12.00
0 0 103.00
0 38 152.00
0 43 242.00
0 45 45.00
29 0 344.00
0 0 12.00
0 19 19.00
9 0 41.00
0 72 72.00
0 47 225.00
0 0 20.00
0 23 23.00
0 0 359.00
70 0 70.00
0 0 179.00
51 0 134.00
39 27 66.00
23 38 110.00
40 54 349.00
0 65 563.00
46 0 46.00
53 75 294.00
0 71 118.00
70 0 70.00
0 0 11.00
53 0 97.00
67 25 115.00
49 4 472.00
0 69 117.00
58 0 142.00
0 62 124.00
0 0 100.00
18 0 18.00
0 0 28.00
0 0 25.00
71 0 77.00
0 11 449.00
62 0 155.00
13 0 51.00
0 24 59.00
72 0 124.00
0 0 72.00
0 62 175.00
0 0 371.00
0 0 19.00
9 0 9.00
0 4 42.00
17 0 17.00
0 40 40.00
56 25 81.00
2 0 2.00
68 32 475.00
0 31 31.00
0 59 59.00
32 75 320.00
0 0 61.00
47 0 59.00
0 30 30.00
15 0 15.00
63 55 118.00
74 12 288.00
73 43 194.00
67 0 67.00
0 54 299.00
48 0 236.00
0 0 14.00
0 23 170.00
0 0 211.00
0 64 297.00
0 13 148.00
0 0 93.00
2 0 273.00
52 48 151.00
32 0 340.00
0 16 330.00
0 47 266.00
55 0 439.00
0 73 96.00
0 40 206.00
0 25 449.00
0 0 277.00
0 48 48.00
0 24 116.00
0 31 166.00
74 0 264.00
0 40 55.00
0 0 130.00
54 0 118.00
0 20 20.00
0 54 54.00
34 0 34.00
0 7 7.00
16 54 70.00
0 35 229.00
41 0 118.00
35 0 35.00
28 0 28.00
72 0 168.00
23 11 34.00
63 0 63.00
45 0 382.00
0 0 291.00
59 22 529.00
0 23 87.00
0 26 204.00
0 4 68.00
2 0 255.00
0 61 556.00
0 61 449.00
48 0 305.00
15 9 65.00
46 28 74.00
49 33 100.00
0 16 58.00
0 10 92.00
e given data

ence of brand

500
79

18%
Stores Potential Company Sales
A 12000 4550 38% 7
B 110000 5
C 19400 1365 7% NR 71%
D 247000 2200 1% WNR 4%
E 250000 7020 3%
F 105000 24050 23%
G 244000

987400 39185 4%
Loss opportunity 354000
Overall
Present
Present in large no of otlets
But Market extraction is less

Our Brand is present in 71% of market but the

market extraction is only 4%.
The numeric reach in outlet is 71% and
weighted is 4% indicating huge gap and
physical presence in sales made.
Also the manager will not go with Loss
opportunity but he must focus on D & E i.e.
should increase sales in that.
 All brand
Stores Brand Selling store Butter Sales / month (Rs) Units / month
1 0 710 387
2 1 110 110
3 1 70 42
4 1 175 95
5 0 750 110
6 1 41 55
7 0 710 210
8 0 280 177
9 1 550 386
10 1 100 386
11 1 110 169
12 1 190 72
13 1 510 380
14 1 125 358
15 0 155 239
16 0 110 193
17 1 70 132
18 1 80 69
19 1 300 384
20 1 540 360
21 0 750 372
22 0 530 392
23 1 150 104
24 1 690 397
25 1 210 381
8016 5960
 WNR(sales) WNR(units)
Total Stores 25 8016 5960
Present 17 4021 3880

NR 68% 50.2% 65%

Q1- Cal. Numeeric Reach
Q2 Cal. WNR
Q3 Cal. extraction share.
 Total Retailers
Alipurduar 4773
Bankura 4496
Birbhum 3207
Cooch Behar 2299
Dakshin Dinajpur 2432
Darjeeling 5604
Hooghly 4942
Howrah 3443
Jalpaiguri 5871
Jhargram 3215
Kalimpong 3026
Kolkata 10972
Malda 4285
Murshidabad 4014
Nadia 3587
North 24 Parganas 5152
Paschim
2682
Bardhaman
Total 74000
 Total of All Stores Our Brand Presence
Our Brand Retailers Sales (Rs. lacs) Units (Lacs) Store Sales (Rs Lacs) Units (Lacs)
1039 115.46 73 13.37 24
1247 139.5 18 38.67 6
1030 124.49 17 2.32 6
1024 227.05 14 119.61 9
1004 111.43 78 9.56 6
1032 136.57 34 8.73 22
1132 128.42 5 7.99 2
1651 194.96 6 9.36 2
1248 161.98 17 28.07 3
1225 206.53 35 19.05 14
1200 136.1 18 11.01 11
1053 479.14 23 133.31 17
1043 153.84 31 19.97 3
1026 112.2 20 20.76 9
1242 41.74 17 22.1 7
1313 131.98 92 9.79 39

1100 182.41 18 20.34 7

19609 2783.8 516 494.01 187
 Revenue
NR WNR
Calculate 22% 12%
1) Numeric Reach
2) Weighted Numeric Reach 28% 28%
32% 2%
Offer your comments 45% 53%
41% 9%
18% 6%
23% 6%
48% 5%
WNR 36% 21% 17%
18% 38% 9%
40% 8%
NR 26% 10% 28%
24% 13%
26% 19%
35% 53%
25% 7%

41% 11%
26% 18%

Chart Title
60%

50%

40%

30%
, [Y VALUE] , [Y VALUE]

20%
, [Y VALUE]
5% 10% 15% 20% , [Y VALUE]
25% 30%

, [Y VALUE]
 20%
, [Y VALUE]
5% 10% 15% 20% , [Y VALUE]
25% 30%

, [Y VALUE]
, [Y VALUE]
10%

, [Y VALUE]
, [Y VALUE] , [Y VALUE]

,
0%
 Chart Title
60%

, [Y VALUE] , [Y VALUE]

50%

40%

30%
, [Y VALUE]

20%
, [Y VALUE]
E]
25% 30% 35% 40% 45% 50% 55%

, [Y VALUE]
20%
, [Y VALUE]
E]
25% 30% 35% 40% 45% 50% 55%

, [Y VALUE]
UE] , [Y VALUE]
10%
, [Y VALUE]
, [Y VALUE]
, [Y VALUE]
, [Y VALUE]
VALUE]
, [Y VALUE]

, [Y VALUE]
0%
 Cust 1 Cust 2 Cust 3
Brnd A 250 550 300 1100
Brnd B 250 550 900 1700
brnd C 500 300 200 1000
Total 1000 1400 1400 3800
Cust Pop. 150 350 400 900

BDI
Cust 1 Cust 2 Cust 3
Brnd A 1.363636 1.285714 0.613636
Brnd B 0.882353 0.831933 1.191176
brnd C 3 0.771429 0.45

CDI 1.578947 0.947368 0.828947

Linear Regression For single Variable(Cal. Manually)

Predict demand for month of April and May

X Y
Months Million Cases x-X y-Y (x-X)*(y-Y) (x-X)2
Oct 1 130 -2.5 -42.5 106.25 6.25
Nov 2 135 -1.5 -37.5 56.25 2.25
Dec 3 150 -0.5 -22.5 11.25 0.25
Jan 4 180 0.5 7.5 3.75 0.25
Feb 5 190 1.5 17.5 26.25 2.25
Mar 6 250 2.5 77.5 193.75 6.25
Avg 3.5 172.5 397.5 17.5
Total 21 1035
N 6

m(slope) 22.71429
c(intercept) 93

Forecast
(manually) Forecast
April 7 252 252
May 8 274.7142857 289
 Linear Regression For single Variable(Cal.using For

X Y y=mx+c
Temp Million Cases Model ESS(Error sum of Square)
Oct 15 130 114.7376 232.941797929876
Nov 22 135 138.5221 12.4051846009753
Dec 29 150 162.3066 151.453138258591
Jan 39 180 196.2845 265.185930594914
Feb 41 190 203.0801 171.089291192643
Mar 46 250 220.0691 895.861121511397
Apr 47 223.4669 1728.9364640884
May 50 233.6602

m 3.3977900558
c 63.770718232

Apr 223.466850853823
May 233.660221021169
(Cal.using Forecast and Solver)

SUMMARY OUTPUT

Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations

ANOVA

Regression
Residual
Total

Intercept
Temp
47
50
Regression Statistics
0.9102780073406
0.82860605064799
0.78575756331
20.7902408841769
6

df SS MS
1 8358.5635359116 8358.5635359116
4 1728.9364640884 432.234116022099
5 10087.5

Coefficients Standard Error t Stat

63.7707182320442 26.1414550020158 2.43944792771201
3.39779005524862 0.7726632174139 4.39750460313251
223.466850828729
233.660220994475
 F Significance F
19.3380467345716 0.0117139213162

P-value Lower 95% Upper 95% Lower 95.0%

0.0712508241783122 -8.8095965510509 136.351033015139 -8.8095965510509
0.0117139213161984 1.25253304729353 5.54304706320371 1.25253304729353
 Upper 95.0%
136.351033015139
5.54304706320371
Base Data 3_Months
Shipments 4 Months
Jan 22 3 Months Wt
Feb 19 4 Months Wt
Mar 32 Derived Weights 3_Months
Apr 40
May 40
Shipments from Amazon
Jun 22 are listed in the
Jul 32 adjoining table, prepare
Aug 20 forecast for the next
Sep 25 month on the basis of
Oct 29 the above mentioned
Nov 24 methods
Dec 26

3-month 4-month

Shipments Ess
Jan 22 Jan 22
Feb 19 Feb 19
Mar 32 Mar 32
Apr 40 24.33333 245.4444 Apr 40
May 40 30.33333 93.44444 May 40 28.25
Jun 22 37.33333 235.1111 Jun 22 32.75
Jul 32 34 4 Jul 32 33.5
Aug 20 31.33333 128.4444 Aug 20 33.5
Sep 25 24.66667 0.111111 Sep 25 28.5
Oct 29 25.66667 11.11111 Oct 29 24.75
Nov 24 24.66667 0.444444 Nov 24 26.5
Dec 26 26 0 Dec 26 24.5
718.1111

4 month Weighted Avg is better

W3 0.667127
W2 0.25626
W1 0.076613
Shipment Model ESS 1.000001 1
Jan 22
Feb 19
Mar 32
Apr 40 27.90251 146.3492
May 40 36.34108 13.38773
Jun 22 39.38713 302.3124
Jul 32 27.99175 16.06608
Aug 20 30.05034 101.0093
Sep 25 23.22837 3.138673
Oct 29 24.25502 22.51485
Nov 24 27.28547 10.79429
Dec 26 25.35794 0.412243
615.9847

W4 0.927886
W3 0.072115
W2 0
Shipment Model W1 0
Jan 22 1.000001
Feb 19
Mar 32
Apr 40
May 40 39.42312 0.332792
Jun 22 21.88462 0.013312
Jul 32 40.00004 64.00064
Aug 20 22 4.000088
Sep 25 20.00002 24.9998
Oct 29 0 841
Nov 24 0 576
Dec 26 0 676
2186.347
 Shipments
45
40
35
30
25
20
15
10
5
0
1 2 3 4 5 6 7 8 9 10 11 12

W3 3
W2 2
W1 1
ESS 6
Jan 22
Feb 19
Mar 32
Apr 40 26 196
138.0625 May 40 33.83333 38.02778
115.5625 Jun 22 38.66667 277.7778
2.25 Jul 32 31 1
182.25 Aug 20 30 100
12.25 Sep 25 24.33333 0.444444
18.0625 Oct 29 24.5 20.25
6.25 Nov 24 26.16667 4.694444
2.25 Dec 26 25.83333 0.027778
476.9375 638.2222

Chart Title
45
40
35
30
25
20
15
10
5
0
1 2 3 4 5 6 7 8 9
 30
25
20
15
10
5
0
1 2 3 4 5 6 7 8 9

Column C Column D

1
 Sales
Gallons(mio)
Years yi
1 56
2 58
3 45
4 50
5 52
6 55
7 57
8 53
9 54
10 48
11 51
12 54
13 50
14 48
15 53
16 54
17 52
18 55
19 53
20 49

W3 0.270674
W2 0.068737
Gallons(mio) W1 0.6618
Years yi 1.00121 Gallons(mio)
1 56 Years
2 58 1
3 45 2
4 50 48.9254541 1.154649 3
5 52 51.88222233 0.013872 4
6 55 50.03074679 24.69348 5
7 57 53.50698851 12.20113 6
8 53 55.57814594 6.646836 7
9 54 53.88044172 0.014294 8
10 48 54.8086419 46.3576 9
11 51 49.82388498 1.383247 10
12 54 51.66753737 5.440382 11
13 50 52.23510442 4.995692 12
14 48 50.60613699 6.79195 13
15 53 49.81961162 10.11487 14
16 54 51.90844184 4.374616 15
17 52 52.37257799 0.138814 16
18 55 52.47108407 6.395416 17
19 53 54.58968359 2.527094 18
20 49 52.93094685 15.45234 19
21 50.95829551 148.6963 20
 W4 0.686679
W3 0
Gallons(mio) W2 0.177633
yi W1 0.134803
56 0.999115
58
45
50
52 52.18565 0.034467
55 51.51939 12.11467
57 52.71515 18.35998
53 55.11779 4.485018
54 53.17358 0.682976
48 54.61993 43.8235
51 50.05893 0.885608
54 51.75739 5.029304
50 52.88643 8.331479
48 49.86379 3.473728
53 49.42775 12.761
54 52.55502 2.087974
52 52.34722 0.12056
55 51.59242 11.61161
53 54.5041 2.262331
49 52.91028 15.29032
50.42686 141.3545
Demand Advertising Sales Promotion Trucks available Estimate the constant and predict
7 1 5 3 the sales if,
44 2 2 3
Advt =30, Sales promotion =39 and
54 1 2 1 Trucks available are 55
95 4 2 3
125 21 17 16
39 22 19 20
194 16 17 16
213 20 21 21
241 18 16 17
250 16 17 17 MS F
286 21 18 19 176182.3 30.1099
252 21 15 15 5851.309
260 22 19 20
290 21 22 19
300 20 22 19 t Stat P-value
320 19 22 21 -0.493115 0.627893
424 32 32 36 -0.141756 0.888847
462 35 36 33 0.717514 0.482265
512 33 30 36 1.094613 0.288118
516 32 31 32
552 36 35 33
567 36 34 36
30 39 55 C
h
a
r
t
T
C
i
ot
l
ul
me
n
C
 y=Adv(x1)+Sp(x2)+TA(x3)
Demand Advertising Sales Promotion Trucks available Model ESS
7 1 5 3 56.11958 2412.733
44 2 2 3 38.12751 34.48611
54 1 2 1 19.50927 1189.61
95 4 2 3 35.05113 3593.867
125 21 17 16 222.1881 9445.519
39 22 19 20 271.932 54257.31
194 16 17 16 229.879 1287.303
213 20 21 21 296.0558 6898.269
241 18 16 17 231.3962 92.23259
250 16 17 17 239.9572 100.8573
286 21 18 19 257.9073 789.1982
252 21 15 15 201.1406 2586.679
260 22 19 20 271.932 142.3721
290 21 22 19 279.8458 103.1072
300 20 22 19 281.384 346.5548
320 19 22 21 303.0786 286.3326
424 32 32 36 489.1016 4238.222
462 35 36 33 476.1909 201.382
512 33 30 36 476.5942 1253.571
516 32 31 32 443.3041 5284.687
552 36 35 33 469.1681 6861.124
567 36 34 36 493.9181 5340.962
30 39 55 722.0565 106746.4
 the constant and predict
s if,

0, Sales promotion =39 and

vailable are 55

Significance F
3.137E-07

Lower 95%Upper 95%Lower 95.0%

Upper 95.0%
-92.65604 57.42904 -92.65604 57.42904
-17.28796 15.10247 -17.28796 15.10247
-12.22839 24.91308 -12.22839 24.91308
-8.705288 27.64364 -8.705288 27.64364

Advertising -1.53819
Sales Promotion 5.484625
Trucks available 10.07821
+Sp(x2)+TA(x3) SUMMARY OUTPUT

Regression Statistics
Multiple R 0.913149
R Square 0.833841
Adjusted R 0.806147
Standard E 76.49385
Observatio 22

ANOVA
df SS
Regression 3 528547
Residual 18 105323.6
Total 21 633870.6

Coefficients
Standard Error
Intercept -17.6135 35.71886
Advertising-1.092742 7.708623
Sales Prom 6.342343 8.839326
Trucks avai 9.469177 8.650709
 MS F Significance F
176182.3 30.1099 3.137E-07
5851.309

t Stat P-value Lower 95%Upper 95%Lower 95.0%

Upper 95.0%
-0.493115 0.627893 -92.65604 57.42904 -92.65604 57.42904
-0.141756 0.888847 -17.28796 15.10247 -17.28796 15.10247
0.717514 0.482265 -12.22839 24.91308 -12.22839 24.91308
1.094613 0.288118 -8.705288 27.64364 -8.705288 27.64364
Month Demand Forecast(F(t)) ESS
t Yt Alpha 0.385471
1 213 203.4666667 90.88444 1-Alpha 0.614529
2 201 207.1414885 37.71788
3 198 204.7741239 45.88875 ESS 1133.152 Min
4 207 202.1628968 23.39757
5 220 204.0274589 255.1221
6 232 210.1844075 475.9201
7 210 218.5936819 73.85137
8 217 215.2810683 2.954726
9 212 215.9436663 15.5525
10 225 214.423498 111.8624
11 218.5004309
SUMMARY OUTPUT

Regression Statistics
Multiple R 0.52862
R Square 0.279439
Adjusted R Square 0.189368
Standard Error 9.407122
Observations 10

ANOVA
df SS MS F Significance F
Regression 1 274.5485 274.5485 3.102455 0.116203
Residual 8 707.9515 88.49394
Total 9 982.5

Coefficients
Standard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%
Upper 95.0%
Intercept 203.4667 6.426288 31.66162 1.078E-09 188.6476 218.2857 188.6476 218.2857
X Variable 1 1.824242 1.03569 1.761379 0.116203 -0.564063 4.212548 -0.564063 4.212548
Upper 95.0%
 Prepare a forecast using exponential smoothing
Months Despatches method for the adjoining data for shipments made
1 Jan 37.0 from a warehouse
2 Feb 40.0 1) Estimate the initial Forecast value
3 Mar 41.0 2) Derive the weights for a forecast
4 Apr 37.0 3) Predict the shipments for the next month
5 May 45.0 4) Exponential Smoothing
6 Jun 50.0
7 Jul 43.0
8 Aug 47.0
9 Sep 56.0
10 Oct 52.0
11 Nov 55.0
12 Dec 54.0

1 Jan 37.0
2 Feb 40.0
3 Mar 41.0
4 Apr 37.0
5 May 45.0
6 Jun 50.0
7 Jul 43.0
8 Aug 47.0
9 Sep 56.0
10 Oct 52.0
11 Nov 55.0
12 Dec 54.0
13 Jan
 SUMMARY OUTPUT

Regression Statistics
Multiple R 0.896304
R Square 0.803361
Adjusted 0.783697
Standard E3.224993
α 0.685365 Observatio 12
1-α 0.314635
ANOVA
df SS MS
Forecast ESS Regressio 1 424.9108 424.9108
35.21212 3.20 Residual 10 104.0058 10.40058
36.43747 12.69 Total 11 528.91667
38.8791 4.50
40.33269 11.11 ESS 264.27 Coefficients
Standard Error t Stat
38.04858 48.32 Intercept 35.21212 1.984846 17.74048
42.81284 51.66 X Variable 1.7237762 0.2696875 6.3917542
47.73867 22.45
44.49095 6.30
46.21057 95.83
52.9199 0.85
52.28943 7.35
54.14716 0.02
54.0463
 F Significance F
40.85452 7.92E-05

P-value Lower 95% Upper 95%Lower 95.0%

Upper 95.0%
6.91E-09 30.78961 39.63463 30.78961 39.63463
7.916E-05 1.122875 2.3246774 1.122875 2.3246774
 Prepare a Naive forecast for the given data and
Months Despatches
estimate the error sum of squares
1 Jan 37.0
2 Feb 40.0
3 Mar 41.0
4 Apr 37.0
5 May 45.0
6 Jun 50.0
7 Jul 43.0
8 Aug 47.0
9 Sep 56.0
10 Oct 52.0
11 Nov 55.0
12 Dec 54.0

1 Jan 37.0
2 Feb 40.0
3 Mar 41.0
4 Apr 37.0
5 May 45.0
6 Jun 50.0
7 Jul 43.0
8 Aug 47.0
9 Sep 56.0
10 Oct 52.0
11 Nov 55.0
12 Dec 54.0

Chart Title
60.0

50.0

40.0

30.0

20.0

10.0

0.0
1 2 3 4 5 6 7 8

Column I Column J
10.0

0.0
1 2 3 4 5 6 7 8

Column I Column J
ast for the given data and
of squares

Model ESS

37.0 9.0
40.0 1.0
41.0 16.0 Ess 287.0
37.0 64.0
45.0 25.0
50.0 49.0
43.0 16.0
47.0 81.0
56.0 16.0
52.0 9.0
55.0 1.0

Chart Title

5 6 7 8 9 10 11

Column I Column J
 5 6 7 8 9 10 11

Column I Column J
Base 37.42844 100 Trend Multiplicative Model
Trend 1.001494 3
Monthly Trend
1 0.884216
2 0.828512
3 1.041523 MonthNumber Month Month
4 0.992114 1 7/1/2009 7
5 1.032855 2 8/1/2009 8
6 1.09847 2 3 9/1/2009 9
7 1.164267 4 10/1/2009 10
8 1.115686 5 11/1/2009 11
9 0.936291 6 12/1/2009 12
10 1.00191 7 1/1/2010 1
11 0.938553 8 2/1/2010 2
12 0.965603 9 3/1/2010 3
10 4/1/2010 4
1 1 11 5/1/2010 5
12 6/1/2010 6
13 7/1/2010 7
14 8/1/2010 8
15 9/1/2010 9
16 10/1/2010 10
17 11/1/2010 11
18 12/1/2010 12
19 1/1/2011 1
20 2/1/2011 2
21 3/1/2011 3
22 4/1/2011 4
23 5/1/2011 5
24 6/1/2011 6
25 7/1/2011 7
26 8/1/2011 8
27 9/1/2011 9
28 10/1/2011 10
29 11/1/2011 11
30 12/1/2011 12
31 1/1/2012 1
32 2/1/2012 2
33 3/1/2012 3
34 4/1/2012 4

C
50.00
45.00
40.00
35.00 R² = 0.00028201580259779
30.00
25.00
20.00
15.00
50.00
45.00
40.00
35.00 R² = 0.00028201580259779
30.00
25.00
20.00
15.00
10.00
5.00
0.00
1 2 3 4 5 6 7 8 9 101112131

Column I
Linear (Colum
 Trend estimate (Forecasting)

Multiplicative: Constant*TrendMonthNum
Additive : Constant+Trend*MonthNu
AirlineMiles (billions) Model ESS
44.22 43.641826089 0.329 Estimate for both methods
42.40 41.883268722 0.264
34.68 35.201249934 0.277
37.32 37.72455537 0.165
34.58 35.391820269 0.665
36.46 36.466257457 0.000 Ess 5.598
33.49 33.442557766 0.002
30.72 31.382533142 0.441
39.37 39.509963972 0.020
37.76 37.691869698 0.005
38.88 39.298320579 0.172
41.90 41.857318698 0.002
44.02 44.430826088 0.167
42.81 42.640475786 0.030
36.13 35.837652869 0.086
39.18 38.40657711 0.604
36.67 36.031668521 0.409
37.43 37.125530445 0.091
34.33 34.047165327 0.079
31.83 31.949897546 0.016
40.51 40.22426409 0.080
38.51 38.373300515 0.018
40.43 40.008794399 0.177
42.57 42.614056612 0.002
45.07 45.234090408 0.026
42.78 43.411372386 0.396
36.70 36.485561323 0.046
38.70 39.100929112 0.158
36.83 36.683084582 0.021
37.49 37.796722422 0.092
34.31 34.662703581 0.122
33.26 32.527519323 0.543
40.78 40.951478031 0.029
38.81 39.067050909 0.068

Chart Title
50.00
45.00
40.00
35.00 R² = 0.00028201580259779
30.00
25.00
20.00
15.00
50.00
45.00
40.00
35.00 R² = 0.00028201580259779
30.00
25.00
20.00
15.00
10.00
5.00
0.00
1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031323334

Column I Column J
Linear (Column J) Linear (Column J)
mate (Forecasting)

e: Constant*TrendMonthNumber*MonthTrend
onstant+Trend*MonthNumber+MonthTrend

r both methods
Base 37.3788 100 Additive Model
Trend 0.059023 3
Monthly Trend
1 -4.457438
2 -6.62377
3 1.600955
4 -0.31903
5 1.28147 MonthNumMonth Month AirlineMiles (bi
6 3.793168 2 1 7/1/2009 7 44.22
7 6.290368 2 8/1/2009 8 42.40
8 4.458436 3 9/1/2009 9 34.68
9 -2.42952 4 10/1/2009 10 37.32
10 0.078045 5 11/1/2009 11 34.58
11 -2.35736 6 12/1/2009 12 36.46
12 -1.31532 7 1/1/2010 1 33.49
8 2/1/2010 2 30.72
8.333E-08 0 9 3/1/2010 3 39.37
10 4/1/2010 4 37.76
11 5/1/2010 5 38.88
12 6/1/2010 6 41.90
13 7/1/2010 7 44.02
14 8/1/2010 8 42.81
15 9/1/2010 9 36.13
16 10/1/2010 10 39.18
17 11/1/2010 11 36.67
18 12/1/2010 12 37.43
19 1/1/2011 1 34.33
20 2/1/2011 2 31.83
21 3/1/2011 3 40.51
22 4/1/2011 4 38.51
23 5/1/2011 5 40.43
24 6/1/2011 6 42.57
25 7/1/2011 7 45.07
26 8/1/2011 8 42.78
27 9/1/2011 9 36.70
28 10/1/2011 10 38.70
29 11/1/2011 11 36.83
30 12/1/2011 12 37.49
31 1/1/2012 1 34.31
32 2/1/2012 2 33.26
33 3/1/2012 3 40.78
34 4/1/2012 4 38.81
Model ESS
43.72819 0.237
41.95529 0.195
35.12636 0.203
37.69294 0.141 ESS 4.925
35.31656 0.548
36.41762 0.002
33.33453 0.023
31.22722 0.259
39.51097 0.020
37.65 0.013
39.30953 0.181
41.88025 0.000
Chart Title
44.43647 0.172 50.00
42.66356 0.022 45.00
35.83463 0.088 40.00
38.40122 0.612 35.00
36.02483 0.418 30.00

37.1259 0.090 25.00

20.00
34.04281 0.081
15.00
31.9355 0.012
10.00
40.21925 0.083
5.00
38.35828 0.022
0.00
40.01781 0.170 1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031323334
42.58853 0.000
Column J Column K
45.14475 0.005
43.37184 0.348
36.54291 0.024
39.1095 0.165
36.73311 0.009
37.83418 0.116
34.75109 0.191
32.64378 0.385
40.92752 0.021
39.06656 0.068
 22232425262728293031323334

mn K
 1 2
Diet Coke Price Respondents Diet Coke
mean -0.2375 0.264167 -11.6417 1 -3.8 6.6
Sd 5.527381 4.454547 2.589429 2 1 -1.6
3 4.6 -6
4 5.8 6
5 4.6 -6
6 -5.8 5.8
7 4.4 -4.8
8 -8.4 -2.8
9 6.8 -5.2
10 0.00 1.6
11 -6.8 -3.4
12 7.6 -5.2
13 -1 1.6
14 4.4 4.8
15 8.4 3.4
16 5.8 6.2
17 4.6 6
18 3.8 -6.6
19 1 -1.6
20 -4.4 -5.2
21 -2.5 -1.1
22 6.8 -4.2
23 -2 -2E-16
24 4.6 6
25 -7.2 -4.4
26 -7.6 -4.4
27 5.8 6
28 6.8 4.2
29 -5.8 -5.2
30 -6.8 -3.4
31 -6.8 -4.4
32 2 -4E-16
33 -7.6 -4.4
34 7.6 5.2
35 6.8 4.2
36 -6.8 -3.4
37 -4.8 5.8
38 -5.8 -5.2
39 -6.8 -3.4
40 -6.3 -4.9
41 1 1.6
42 6.8 5.2
43 -1 -1.6
44 4.6 6
45 -4.4 4.2
46 -5.8 5.8
47 -4.6 5.2
48 6.8 -4.2
49 -5.4 -3.4
50 -5.8 5.8
51 -2 -0.8
52 -4.6 -5.2
53 -1 -1.6
54 -5.8 5.8
55 -7.6 5
56 5.8 -6.6
57 -2 -0.8
58 -4.4 -5.2
59 -5.8 -5.2
60 2 0.8
61 -1 -1.6
62 -5.8 5.4
63 -1 -1.6
64 5.8 -6
65 -4.6 -5.2
66 6.6 -4
67 -7.6 -4.4
68 -4.4 -5.2
69 -1 -1.6
70 7.6 5.2
71 4.4 -4.8
72 -1.4 -1.2
73 -7.6 4.4
74 8.4 -3.4
75 4.4 5.2
76 4.6 6
77 -6.8 -4.4
78 -5.8 -5.8
79 -6.8 4.4
80 2 -4E-16
81 -5.2 5.2
82 -6.8 3.4
83 4.4 -5.2
84 6.8 5.2
85 5.8 6.6
86 2 -0.8
87 5.8 6
88 -6.8 4.4
89 -2 -0.8
90 2 0.8
91 2 -4E-16
92 -7.6 4.4
93 -1 -1.6
94 4.9 4.3
95 6.7 -4.1
96 -6.8 3.4
97 7.6 -5.2
98 -5.8 5.2
99 7.6 3.4
100 -5.8 5.2
101 -7.6 4.4
102 4.2 6.2
103 1 -1.6
104 -5.4 3.4
105 5.8 -6
106 3.8 7.2
107 2 0.8
108 4.4 5.8
109 -6.8 3.4
110 6.8 4.2
111 -1 -1.6
112 6.3 -5.5
113 8.4 -3.4
114 2 -0.8
115 -6.2 5.8
116 -6.8 4.4
117 6.8 -4.6
118 -6.6 3.4
119 -7.6 2.8
120 7.2 -5.2
 BY Eucledian Formula

3
Price Z_Diet Z_Coke Z_Price Dist_1 Dist_2 Dist_3 Dist_4 Dist_5 Min
-9.6 -0.64452 1.422329 0.788462 9.363348 0.253562 6.893254 3.058507 10.14844 0.253562
-16 0.223885 -0.41849 -1.68313 0.196595 9.212797 7.662066 9.033992 5.903539 0.196595
-11.2 0.875188 -1.40624 0.170565 5.775606 10.07659 4.164526 7.518864 0.310884 0.310884
-10 1.092289 1.287636 0.633988 9.678307 4.436556 10.77967 0 5.748874 0
-11.2 0.875188 -1.40624 0.170565 5.775606 10.07659 4.164526 7.518864 0.310884 0.310884
-8.8 -1.00635 1.242738 1.097411 10.83444 0.232903 5.992739 4.621079 11.1304 0.232903
-12.8 0.839005 -1.13685 -0.44733 3.28139 9.614163 4.917145 7.111551 0.912381 0.912381
-9.6 -1.47674 -0.68787 0.788462 7.841585 3.470445 0.390451 10.52641 7.874624 0.390451
-10 1.273207 -1.22665 0.633988 8.376187 10.64719 5.621527 6.354359 0.071833 0.071833
-16 0.042968 0.299881 -1.68313 0.459255 7.123218 8.79733 7.44575 7.799598 0.459255
-11.2 -1.18727 -0.82257 0.170565 4.634525 3.974752 0.336334 9.864114 6.180212 0.336334
-8.8 1.417941 -1.22665 1.097411 11.18893 11.54276 6.54328 6.642437 0.522302 0.522302
-16 -0.13795 0.299881 -1.68313 0.400339 6.776268 8.417648 7.858163 8.277473 0.400339
-12.8 0.839005 1.018248 -0.44733 4.442505 4.582664 9.658365 1.305975 5.363323 1.305975
-9.6 1.562675 0.703962 0.788462 10.31862 6.787052 10.56849 0.585799 3.458251 0.585799
-9.4 1.092289 1.332533 0.865699 10.95296 4.508388 11.0551 0.055706 6.125638 0.055706
-11.2 0.875188 1.287636 0.170565 7.227 3.787214 10.09105 0.261893 5.874562 0.261893
-10.8 0.730454 -1.54093 0.32504 6.387314 10.12904 3.579996 8.227184 0.502128 0.502128
-16 0.223885 -0.41849 -1.68313 0.196595 9.212797 7.662066 9.033992 5.903539 0.196595
-11.6 -0.75307 -1.22665 0.016091 3.988247 5.896741 0.504492 10.10877 4.273076 0.504492
-15.8 -0.40933 -0.30624 -1.60589 0.046074 7.373691 6.217397 9.812339 7.48099 0.046074
-11.2 1.273207 -1.00216 0.170565 6.090572 9.864114 5.856446 5.490653 0.061753 0.061753
-16 -0.31887 -0.0593 -1.68313 0.084353 7.204351 7.184213 9.174621 7.949974 0.084353
-11.2 0.875188 1.287636 0.170565 7.227 3.787214 10.09105 0.261893 5.874562 0.261893
-9.4 -1.25964 -1.04706 0.865699 8.113635 4.762304 0.092801 11.03604 6.63208 0.092801
-8.8 -1.33201 -1.04706 1.097411 9.505618 4.965271 0.282675 11.54276 7.272357 0.282675
-10 1.092289 1.287636 0.633988 9.678307 4.436556 10.77967 0 5.748874 0
-11.2 1.273207 0.883554 0.170565 7.106548 5.461552 10.00501 0.410774 3.956328 0.410774
-10 -1.00635 -1.22665 0.633988 6.80902 5.450791 0.012718 10.72593 5.268229 0.012718
-11.2 -1.18727 -0.82257 0.170565 4.634525 3.974752 0.336334 9.864114 6.180212 0.336334
-10 -1.18727 -1.04706 0.633988 6.839507 4.677192 0.020782 10.64719 6.109658 0.020782
-16 0.404803 -0.0593 -1.68313 0.450942 8.723076 8.833863 7.655896 6.169399 0.450942
-8.8 -1.33201 -1.04706 1.097411 9.505618 4.965271 0.282675 11.54276 7.272357 0.282675
-8.8 1.417941 1.108044 1.097411 12.44681 6.091965 11.6796 0.353063 5.344155 0.353063
-11.2 1.273207 0.883554 0.170565 7.106548 5.461552 10.00501 0.410774 3.956328 0.410774
-11.2 -1.18727 -0.82257 0.170565 4.634525 3.974752 0.336334 9.864114 6.180212 0.336334
-9.8 -0.82544 1.242738 0.711225 8.580673 0.056839 5.849406 3.685653 9.950543 0.056839
-10 -1.00635 -1.22665 0.633988 6.80902 5.450791 0.012718 10.72593 5.268229 0.012718
-11.2 -1.18727 -0.82257 0.170565 4.634525 3.974752 0.336334 9.864114 6.180212 0.336334
-10 -1.09681 -1.1593 0.633988 6.844806 5.149041 0 10.77967 5.675217 0
-16 0.223885 0.299881 -1.68313 0.583633 7.535631 9.242473 7.0988 7.387186 0.583633
-10 1.273207 1.108044 0.633988 9.634062 5.196396 10.75785 0.064984 4.893686 0.064984
-16 -0.13795 -0.41849 -1.68313 0.0133 8.453435 6.837242 9.793355 6.793826 0.0133
-11.2 0.875188 1.287636 0.170565 7.227 3.787214 10.09105 0.261893 5.874562 0.261893
-12.8 -0.75307 0.883554 -0.44733 3.291303 1.283801 5.460674 4.737882 8.730266 1.283801
 -8.8 -1.00635 1.242738 1.097411 10.83444 0.232903 5.992739 4.621079 11.1304 0.232903
-11.2 -0.78925 1.108044 0.170565 5.835542 0.261893 5.450212 3.787214 9.147426 0.261893
-11.2 1.273207 -1.00216 0.170565 6.090572 9.864114 5.856446 5.490653 0.061753 0.061753
-12.8 -0.93399 -0.82257 -0.44733 2.2948 4.90175 1.309155 9.728004 5.666107 1.309155
-8.8 -1.00635 1.242738 1.097411 10.83444 0.232903 5.992739 4.621079 11.1304 0.232903
-16 -0.31887 -0.23889 -1.68313 0.019847 7.655896 6.821365 9.690672 7.611315 0.019847
-11.2 -0.78925 -1.22665 0.170565 4.577667 5.712685 0.313889 10.07659 4.325572 0.313889
-16 -0.13795 -0.41849 -1.68313 0.0133 8.453435 6.837242 9.793355 6.793826 0.0133
-8.8 -1.00635 1.242738 1.097411 10.83444 0.232903 5.992739 4.621079 11.1304 0.232903
-7.6 -1.33201 1.063146 1.560833 13.71866 0.967107 5.853634 6.786642 12.77384 0.967107
-8.8 1.092289 -1.54093 1.097411 10.8977 11.63615 5.152571 8.215571 0.717525 0.717525
-16 -0.31887 -0.23889 -1.68313 0.019847 7.655896 6.821365 9.690672 7.611315 0.019847
-11.6 -0.75307 -1.22665 0.016091 3.988247 5.896741 0.504492 10.10877 4.273076 0.504492
-10 -1.00635 -1.22665 0.633988 6.80902 5.450791 0.012718 10.72593 5.268229 0.012718
-16 0.404803 0.120289 -1.68313 0.579955 8.336037 9.261218 7.204351 6.572564 0.579955
-16 -0.13795 -0.41849 -1.68313 0.0133 8.453435 6.837242 9.793355 6.793826 0.0133
-9.4 -1.00635 1.152942 0.865699 9.325417 0.055706 5.408345 4.476135 10.45072 0.055706
-16 -0.13795 -0.41849 -1.68313 0.0133 8.453435 6.837242 9.793355 6.793826 0.0133
-10 1.092289 -1.40624 0.633988 8.226913 10.72593 4.853145 7.256971 0.185197 0.185197
-11.2 -0.78925 -1.22665 0.170565 4.577667 5.712685 0.313889 10.07659 4.325572 0.313889
-11.6 1.237023 -0.95726 0.016091 5.377232 9.680023 5.869406 5.442307 0.168591 0.168591
-8.8 -1.33201 -1.04706 1.097411 9.505618 4.965271 0.282675 11.54276 7.272357 0.282675
-11.6 -0.75307 -1.22665 0.016091 3.988247 5.896741 0.504492 10.10877 4.273076 0.504492
-16 -0.13795 -0.41849 -1.68313 0.0133 8.453435 6.837242 9.793355 6.793826 0.0133
-8.8 1.417941 1.108044 1.097411 12.44681 6.091965 11.6796 0.353063 5.344155 0.353063
-12.8 0.839005 -1.13685 -0.44733 3.28139 9.614163 4.917145 7.111551 0.912381 0.912381
-16 -0.21032 -0.32869 -1.68313 0 8.066895 6.844806 9.678307 7.132318 0
-8.8 -1.33201 0.928452 1.097411 10.56997 0.353063 4.628794 6.220977 11.35239 0.353063
-9.6 1.562675 -0.82257 0.788462 9.49616 10.35103 7.210125 4.698083 0.305501 0.305501
-12.2 0.839005 1.108044 -0.21562 5.318852 4.127182 9.610081 0.818241 5.410324 0.818241
-11.2 0.875188 1.287636 0.170565 7.227 3.787214 10.09105 0.261893 5.874562 0.261893
-10 -1.18727 -1.04706 0.633988 6.839507 4.677192 0.020782 10.64719 6.109658 0.020782
-8.8 -1.00635 -1.36134 1.097411 9.431429 6.312632 0.263764 11.63615 5.752177 0.263764
-10 -1.18727 0.928452 0.633988 7.903862 0.064984 4.366901 5.325409 10.18969 0.064984
-16 0.404803 -0.0593 -1.68313 0.450942 8.723076 8.833863 7.655896 6.169399 0.450942
-10.6 -0.8978 1.108044 0.402277 6.885745 0.065473 5.234153 4.046412 9.553281 0.065473
-11.2 -1.18727 0.703962 0.170565 5.456981 0.410774 3.694698 5.751831 9.332962 0.410774
-12.2 0.839005 -1.22665 -0.21562 4.060977 9.577974 4.473758 7.107615 0.58847 0.58847
-10 1.273207 1.108044 0.633988 9.634062 5.196396 10.75785 0.064984 4.893686 0.064984
-8.8 1.092289 1.422329 1.097411 12.49423 4.717839 11.67175 0.232903 6.83757 0.232903
-16 0.404803 -0.23889 -1.68313 0.386435 9.174621 8.471014 8.171947 5.830741 0.386435
-10 1.092289 1.287636 0.633988 9.678307 4.436556 10.77967 0 5.748874 0
-10 -1.18727 0.928452 0.633988 7.903862 0.064984 4.366901 5.325409 10.18969 0.064984
-16 -0.31887 -0.23889 -1.68313 0.019847 7.655896 6.821365 9.690672 7.611315 0.019847
-16 0.404803 0.120289 -1.68313 0.579955 8.336037 9.261218 7.204351 6.572564 0.579955
-16 0.404803 -0.0593 -1.68313 0.450942 8.723076 8.833863 7.655896 6.169399 0.450942
-8.8 -1.33201 0.928452 1.097411 10.56997 0.353063 4.628794 6.220977 11.35239 0.353063
-16 -0.13795 -0.41849 -1.68313 0.0133 8.453435 6.837242 9.793355 6.793826 0.0133
-12.8 0.929464 0.906003 -0.44733 4.350753 4.957461 9.540533 1.341408 4.831831 1.341408
-11.4 1.255115 -0.97971 0.093328 5.727105 9.765272 5.856129 5.459683 0.108375 0.108375
-11.2 -1.18727 0.703962 0.170565 5.456981 0.410774 3.694698 5.751831 9.332962 0.410774
-8.8 1.417941 -1.22665 1.097411 11.18893 11.54276 6.54328 6.642437 0.522302 0.522302
-10 -1.00635 1.108044 0.633988 8.066895 0 5.149041 4.436556 10.09008 0
-10.8 1.417941 0.703962 0.32504 7.750321 6.135935 9.891188 0.542173 3.252234 0.542173
-10 -1.00635 1.108044 0.633988 8.066895 0 5.149041 4.436556 10.09008 0
-8.8 -1.33201 0.928452 1.097411 10.56997 0.353063 4.628794 6.220977 11.35239 0.353063
-11 0.802821 1.332533 0.247802 7.514596 3.472649 9.966993 0.234947 6.123271 0.234947
-16 0.223885 -0.41849 -1.68313 0.196595 9.212797 7.662066 9.033992 5.903539 0.196595
-12.8 -0.93399 0.703962 -0.44733 3.117256 1.337771 4.667519 5.615721 8.818858 1.337771
-10 1.092289 -1.40624 0.633988 8.226913 10.72593 4.853145 7.256971 0.185197 0.185197
-9.6 0.730454 1.557023 0.788462 10.54971 3.241947 10.74119 0.227357 7.460807 0.227357
-16 0.404803 0.120289 -1.68313 0.579955 8.336037 9.261218 7.204351 6.572564 0.579955
-11.6 0.839005 1.242738 0.016091 6.457799 3.805287 9.898981 0.447966 5.788462 0.447966
-11.2 -1.18727 0.703962 0.170565 5.456981 0.410774 3.694698 5.751831 9.332962 0.410774
-11.2 1.273207 0.883554 0.170565 7.106548 5.461552 10.00501 0.410774 3.956328 0.410774
-16 -0.13795 -0.41849 -1.68313 0.0133 8.453435 6.837242 9.793355 6.793826 0.0133
-10 1.182748 -1.294 0.633988 8.24146 10.56196 5.214539 6.673005 0.102693 0.102693
-9.6 1.562675 -0.82257 0.788462 9.49616 10.35103 7.210125 4.698083 0.305501 0.305501
-16 0.404803 -0.23889 -1.68313 0.386435 9.174621 8.471014 8.171947 5.830741 0.386435
-8.2 -1.07872 1.242738 1.329122 12.29715 0.506591 6.253334 5.198512 11.8414 0.506591
-10 -1.18727 0.928452 0.633988 7.903862 0.064984 4.366901 5.325409 10.18969 0.064984
-10.6 1.273207 -1.09196 0.402277 7.132318 10.09008 5.675217 5.748874 0 0
-11.6 -1.15109 0.703962 0.016091 4.838759 0.566026 3.856497 5.755212 9.251663 0.566026
-10.8 -1.33201 0.569268 0.32504 6.097242 0.491777 3.138722 6.488704 9.55276 0.491777
-9.4 1.345574 -1.22665 0.865699 9.723634 11.03604 6.023476 6.439471 0.23814 0.23814
 Cl
us
Match te
2 th
1 e
5 da
ta
4
of
5 Z_Diet Z_Coke Z_Price
th
2 72 -0.21032 -0.32869 -1.68313
eR
5 100 -1.00635 1.108044 0.633988
es
3 40 -1.09681 -1.1593 0.633988
po
5 27 1.092289 1.287636 nd
0.633988
1 117 1.273207 -1.09196 en
0.402277
3 ts
5 in
5
1
gr
4 ou
4 Mini Dist. 37.91902 ps
4 usi
4 ng
5 Eu
1 cli
3 de
an
1
dis
5 ta
1 nc
4 e
3 m
3 etr
4 ic
4 an
d
3
st
3 an
3 da
1 rdi
3 zin
4 g
4 th
3 e
2 da
ta
3
3
3
1
4
1
4
2
2
2
5
3
2
1
3
1
2
2
5
1
3
3
1
1
2
1
5
3
5
3
3
1
4
5
1
2
5
4
4
3
3
2
1
2
2
5
4
4
1
4
2
1
1
1
2
1
4
5
2
5
2
4
2
2
4
1
2
5
4
1
4
2
4
1
5
5
1
2
2
5
2
2
5
 A B C D E F G H I J K L M N O P Q R S T
1 Customer Lifetime Value
2
3
4
5 Discount 0.1 Managing Customers as Investments
There are 100 customers and the company serves
6 retention rate 0.8 Gupta and Lehmann
them with a discount rate of 10%. The retention of the
7 customers is 80% over the previous year.
8 Years Customers Discounted value of earnin Customers 100
9 1 0 100 1 1) Prepare a discount table for a 50 year period
10 2 1 80 0.9090909 2) Prepare a retention discount matrix for the data.
11 Managing Customers as Investments 3 2 64 0.8264463
12 Gupta and Lehmann 4 3 51.2 0.7513148 Use the following model for calculating the margin
13 5 4 40.96 0.6830135 multiple values
14 6 5 32.768 0.6209213
r/(1-r)+d
15 7 6 26.2144 0.5644739
16 8 7 20.97152 0.5131581
17 9 8 16.777216 0.4665074
18 10 9 13.421773 0.4240976
19 11 10 10.737418 0.3855433
20 12 11 8.5899346 0.3504939
21 13 12 6.8719477 0.3186308
22 14 13 5.4975581 0.2896644
23 15 14 4.3980465 0.2633313
24 16 15 3.5184372 0.239392
25 17 16 2.8147498 0.2176291
26 18 17 2.2517998 0.1978447
27 19 18 1.8014399 0.1798588
28 20 19 1.4411519 0.163508
29 21 20 1.1529215 0.1486436
30 22 21 0.9223372 0.1351306
31 23 22 0.7378698 0.122846
32 24 23 0.5902958 0.1116782
33 25 24 0.4722366 0.1015256
34 26 25 0.3777893 0.092296
35 27 26 0.3022315 0.0839055
36 28 27 0.2417852 0.0762777
37 29 28 0.1934281 0.0693433
38 30 29 0.1547425 0.0630394
39 31 30 0.123794 0.0573086
40 32 31 0.0990352 0.0520987
41 33 32 0.0792282 0.0473624
42 34 33 0.0633825 0.0430568
43 35 34 0.050706 0.0391425
44 36 35 0.0405648 0.0355841
45 37 36 0.0324519 0.0323492
46 38 37 0.0259615 0.0294083
47 39 38 0.0207692 0.0267349
48 40 39 0.0166153 0.0243044
49 41 40 0.0132923 0.0220949
50 42 41 0.0106338 0.0200863
51 43 42 0.0085071 0.0182603
52 44 43 0.0068056 0.0166002
53 45 44 0.0054445 0.0150911
54 46 45 0.0043556 0.0137192
55 47 46 0.0034845 0.012472
56 48 47 0.0027876 0.0113382
57 49 48 0.0022301 0.0103074
58 50 49 0.0017841 0.0093704
 Churn And Retention will be found by a Churn Retention mod
C Churn 0.25
R Retention 0.75 1-C
i Discount 0.12

Margin Multiple 2.027027 2.027027 0.6 0.65 0.7

0.1 1.20 1.44 1.75
0.11 1.18 1.41 1.71
0.12 1.15 1.38 1.67
0.13 1.13 1.35 1.63
0.14 1.11 1.33 1.59
0.15 1.09 1.30 1.56
und by a Churn Retention model

0.75 0.8 0.85 0.9

2.14 2.67 3.40 4.50
2.08 2.58 3.27 4.29
2.03 2.50 3.15 4.09
1.97 2.42 3.04 3.91
1.92 2.35 2.93 3.75
1.88 2.29 2.83 3.60
N = Number of Purchases
t= Time of last purchase
T = Time ellapsed between acquisition of customer and present time

T* = t/T

T N t T*
1 1 1 1
2 0 0
3 0 0
4 0 0
5 1 5 1
6 1 6 1
7 0 0
8 0 0
9 1 9 1
10 0 0
Prob. of
he being
alive 0.6561
and present time
Customers 1 and 2 have been with a company for 12 months. Customer 1
has made four purchases and Customer 2 has made two purchases. Each customer’s
last purchase was at the end of month 8.

Which customer is most likely to still be active? Can you explain this result?
 Customer 1 Customer 2
1 1 1 0
2 1 0 2
3 1 3 0
4 0 0
5 1 5 0
6 0 0
7 0 0
8 1 1 8 8
9 0 0
10 0 0
11 0 0
12 0 0
0.197531 0.444444

So customer 2
will buy more
in coming
time
To find Aggregate Churn

Person Years Still Here? Quits Chances to Quit

1 2 no 1 3
2 2 no 1 3
3 3 no 1 4
4 1 no 1 2
5 4 yes 0 4
6 4 yes 0 4
7 3 yes 0 3
8 2 yes 0 2
9 5 yes 0 5
10 2 no 1 3
Churn 0.1515
1-Churn 0.8485 Retention
We will estimate churn rate (which is 1 -retention rate) as
Number of Quits/Total Chances to Quit. Churn
Retention

Person Years Still Here? Quits Chances of Quits

1 7 no 1 8
2 6 no 1 7
3 4 no 1 5
4 1 no 1 2
5 7 no 1 8
6 8 no 1 9
7 3 no 1 4
8 7 no 1 8
9 8 no 1 9
10 1 no 1 2
11 7 no 1 8
12 1 no 1 2
13 1 yes 0 1
14 1 no 1 2
15 6 no 1 7
16 1 no 1 2
17 3 no 1 4
18 6 no 1 7
19 2 no 1 3
20 5 no 1 6
21 4 yes 0 4
22 18 no 1 19
23 1 no 1 2
24 3 no 1 4
25 1 no 1 2
26 5 no 1 6
27 5 no 1 6
28 1 no 1 2
29 1 no 1 2
30 1 no 1 2
31 1 no 1 2
32 3 no 1 4
33 9 no 1 10
34 1 no 1 2
35 11 no 1 12
36 23 no 1 24
37 8 no 1 9
38 1 no 1 2
39 2 no 1 3
40 1 yes 0 1
41 6 no 1 7
42 9 no 1 10
43 8 no 1 9
44 5 no 1 6
45 3 no 1 4
46 3 no 1 4
47 3 no 1 4
48 3 no 1 4
49 23 no 1 24
50 3 no 1 4
51 1 no 1 2
52 1 no 1 2
53 1 no 1 2
54 9 yes 0 9
55 8 no 1 9
56 2 no 1 3
57 2 no 1 3
58 12 no 1 13
59 1 yes 0 1
60 8 no 1 9
61 1 no 1 2
62 2 no 1 3
63 1 no 1 2
64 11 no 1 12
65 3 no 1 4
66 7 no 1 8
67 3 no 1 4
68 10 no 1 11
69 18 no 1 19
70 2 yes 0 2
71 18 no 1 19
72 1 no 1 2
73 9 no 1 10
74 3 no 1 4
75 1 no 1 2
76 2 no 1 3
77 13 no 1 14
78 1 no 1 2
79 1 no 1 2
80 1 yes 0 1
81 5 yes 0 5
82 1 no 1 2
83 6 yes 0 6
84 2 no 1 3
85 6 no 1 7
86 8 no 1 9
87 7 no 1 8
88 8 no 1 9
89 7 no 1 8
 90 4 no 1 5
91 1 yes 0 1
92 1 no 1 2
93 18 no 1 19
94 4 no 1 5
95 1 yes 0 1
96 7 no 1 8
97 5 no 1 6
98 8 no 1 9
99 13 no 1 14
100 1 no 1 2
101 8 no 1 9
102 5 no 1 6
103 1 no 1 2
104 8 no 1 9
105 1 no 1 2
106 9 yes 0 9
107 2 no 1 3
108 1 no 1 2
109 5 no 1 6
110 1 no 1 2
111 2 no 1 3
112 2 no 1 3
113 27 no 1 28
114 1 yes 0 1
115 1 no 1 2
116 1 no 1 2
117 12 no 1 13
118 2 no 1 3
119 2 yes 0 2
120 4 no 1 5
121 1 no 1 2
122 1 no 1 2
123 7 no 1 8
124 3 no 1 4
125 25 no 1 26
126 1 no 1 2
127 7 no 1 8
128 7 no 1 8
129 14 no 1 15
130 7 no 1 8
131 1 no 1 2
132 22 no 1 23
133 4 no 1 5
134 1 no 1 2
135 1 no 1 2
136 4 no 1 5
137 2 no 1 3
138 1 no 1 2
139 17 no 1 18
140 4 no 1 5
141 1 no 1 2
142 6 no 1 7
143 13 yes 0 13
144 1 no 1 2
145 10 no 1 11
146 1 no 1 2
147 17 no 1 18
148 4 no 1 5
149 1 no 1 2
150 3 no 1 4
151 9 no 1 10
152 4 no 1 5
153 2 no 1 3
154 34 yes 0 34
155 5 no 1 6
156 12 no 1 13
157 11 no 1 12
158 2 no 1 3
159 6 no 1 7
160 2 no 1 3
161 1 no 1 2
162 2 no 1 3
163 1 no 1 2
164 1 no 1 2
165 11 no 1 12
166 6 no 1 7
167 17 no 1 18
168 1 no 1 2
169 3 no 1 4
170 5 yes 0 5
171 2 yes 0 2
172 1 no 1 2
173 8 yes 0 8
174 3 yes 0 3
175 2 no 1 3
176 12 no 1 13
177 3 yes 0 3
178 1 no 1 2
179 16 no 1 17
180 9 no 1 10
181 10 no 1 11
182 1 no 1 2
183 4 no 1 5
184 9 no 1 10
185 1 no 1 2
186 4 no 1 5
187 2 no 1 3
188 1 no 1 2
189 3 no 1 4
190 6 no 1 7
191 2 no 1 3
192 7 no 1 8
193 6 no 1 7
194 1 no 1 2
195 4 no 1 5
196 3 no 1 4
197 2 no 1 3
198 6 no 1 7
199 1 no 1 2
200 3 no 1 4
201 2 no 1 3
202 12 no 1 13
203 1 no 1 2
204 2 no 1 3
205 3 no 1 4
206 10 no 1 11
207 6 yes 0 6
208 1 no 1 2
209 8 no 1 9
210 3 no 1 4
211 1 no 1 2
212 6 no 1 7
213 14 no 1 15
214 1 no 1 2
215 14 no 1 15
216 5 no 1 6
217 7 no 1 8
218 1 no 1 2
219 9 no 1 10
220 8 no 1 9
221 1 no 1 2
222 5 no 1 6
223 16 no 1 17
224 16 no 1 17
225 3 no 1 4
226 1 no 1 2
227 2 no 1 3
228 9 no 1 10
229 1 no 1 2
230 7 no 1 8
231 1 no 1 2
232 2 no 1 3
233 4 yes 0 4
234 2 no 1 3
235 2 no 1 3
236 1 no 1 2
237 7 yes 0 7
238 9 no 1 10
239 5 no 1 6
240 2 no 1 3
241 3 no 1 4
242 1 no 1 2
243 6 no 1 7
244 1 no 1 2
245 1 no 1 2
246 1 yes 0 1
247 2 yes 0 2
248 3 no 1 4
249 1 no 1 2
250 1 no 1 2
251 1 no 1 2
252 8 no 1 9
253 3 no 1 4
254 1 no 1 2
255 1 no 1 2
256 10 no 1 11
257 1 no 1 2
258 4 no 1 5
259 8 no 1 9
260 1 no 1 2
261 15 no 1 16
262 9 no 1 10
263 1 no 1 2
264 4 no 1 5
265 2 no 1 3
266 3 no 1 4
267 3 no 1 4
268 5 no 1 6
269 1 no 1 2
270 7 no 1 8
271 12 no 1 13
272 5 no 1 6
273 11 no 1 12
274 2 no 1 3
275 1 no 1 2
276 20 no 1 21
277 10 no 1 11
278 1 no 1 2
279 13 no 1 14
280 4 no 1 5
281 2 no 1 3
282 10 yes 0 10
283 1 no 1 2
284 1 no 1 2
285 4 no 1 5
286 1 no 1 2
287 2 no 1 3
288 1 no 1 2
289 4 no 1 5
290 1 yes 0 1
291 1 no 1 2
292 8 no 1 9
293 14 no 1 15
294 8 no 1 9
295 1 no 1 2
296 7 no 1 8
297 3 no 1 4
298 1 no 1 2
299 1 no 1 2
300 3 no 1 4
301 10 no 1 11
302 24 no 1 25
303 4 no 1 5
304 1 no 1 2
305 12 no 1 13
306 1 no 1 2
307 17 yes 0 17
308 8 yes 0 8
309 4 no 1 5
310 1 no 1 2
311 1 no 1 2
312 1 no 1 2
313 9 no 1 10
314 1 no 1 2
315 9 yes 0 9
316 1 no 1 2
317 1 no 1 2
318 7 no 1 8
319 11 no 1 12
320 4 no 1 5
321 5 no 1 6
322 1 no 1 2
323 13 no 1 14
324 14 no 1 15
325 1 no 1 2
326 3 no 1 4
327 3 no 1 4
328 14 no 1 15
329 6 no 1 7
330 2 no 1 3
331 15 no 1 16
332 1 no 1 2
333 9 no 1 10
334 11 yes 0 11
335 1 no 1 2
336 3 no 1 4
337 3 no 1 4
338 1 no 1 2
339 20 no 1 21
340 1 no 1 2
341 3 yes 0 3
342 3 no 1 4
343 25 no 1 26
344 4 no 1 5
345 19 no 1 20
346 1 no 1 2
347 13 no 1 14
348 4 no 1 5
349 11 yes 0 11
350 1 no 1 2
351 4 no 1 5
352 4 no 1 5
353 1 no 1 2
354 2 no 1 3
355 2 no 1 3
356 9 no 1 10
357 1 yes 0 1
358 7 yes 0 7
359 3 no 1 4
360 2 no 1 3
361 4 no 1 5
362 3 yes 0 3
363 13 no 1 14
364 1 no 1 2
365 3 yes 0 3
366 11 no 1 12
367 6 no 1 7
368 14 no 1 15
369 3 yes 0 3
370 6 no 1 7
371 10 no 1 11
372 10 no 1 11
373 1 yes 0 1
374 1 no 1 2
375 10 no 1 11
376 2 no 1 3
377 1 no 1 2
378 4 no 1 5
379 2 no 1 3
380 3 no 1 4
381 3 no 1 4
382 6 no 1 7
383 3 no 1 4
384 1 no 1 2
385 10 no 1 11
386 20 no 1 21
387 1 no 1 2
388 5 no 1 6
389 2 no 1 3
390 8 no 1 9
391 7 no 1 8
392 4 no 1 5
393 11 no 1 12
394 3 no 1 4
395 20 no 1 21
396 2 no 1 3
397 9 no 1 10
398 10 yes 0 10
399 12 yes 0 12
400 5 no 1 6
401 1 no 1 2
402 25 no 1 26
403 1 no 1 2
404 2 no 1 3
405 1 no 1 2
406 2 no 1 3
407 22 no 1 23
408 1 no 1 2
409 19 no 1 20
410 5 no 1 6
411 2 no 1 3
412 12 no 1 13
413 10 no 1 11
414 15 no 1 16
415 1 no 1 2
416 8 no 1 9
417 10 no 1 11
418 5 no 1 6
419 4 no 1 5
420 22 no 1 23
421 4 yes 0 4
422 21 no 1 22
423 1 no 1 2
424 1 no 1 2
425 3 yes 0 3
426 6 no 1 7
427 1 no 1 2
428 29 no 1 30
429 4 no 1 5
430 6 no 1 7
431 8 yes 0 8
432 2 no 1 3
433 10 no 1 11
434 7 no 1 8
435 1 no 1 2
436 3 no 1 4
437 7 no 1 8
438 5 yes 0 5
439 4 yes 0 4
440 1 no 1 2
441 12 no 1 13
442 12 no 1 13
443 16 no 1 17
444 15 no 1 16
445 1 no 1 2
446 9 no 1 10
447 4 no 1 5
448 3 no 1 4
449 8 no 1 9
450 5 no 1 6
451 1 no 1 2
452 14 no 1 15
453 11 no 1 12
454 1 no 1 2
455 2 no 1 3
456 7 no 1 8
457 3 no 1 4
458 6 no 1 7
459 8 no 1 9
460 1 yes 0 1
461 17 no 1 18
462 8 no 1 9
463 4 no 1 5
464 2 yes 0 2
465 1 no 1 2
466 4 no 1 5
467 2 no 1 3
468 3 no 1 4
469 2 no 1 3
470 1 no 1 2
471 7 no 1 8
472 5 no 1 6
473 4 no 1 5
474 5 no 1 6
475 16 no 1 17
476 14 no 1 15
477 6 no 1 7
478 3 no 1 4
479 5 no 1 6
480 15 yes 0 15
481 5 no 1 6
482 3 no 1 4
483 2 yes 0 2
484 2 no 1 3
485 4 no 1 5
486 3 no 1 4
487 21 no 1 22
488 7 no 1 8
489 4 no 1 5
490 1 no 1 2
491 5 no 1 6
492 11 no 1 12
493 4 no 1 5
494 4 no 1 5
495 10 no 1 11
496 15 no 1 16
497 2 no 1 3
498 5 no 1 6
499 1 no 1 2
500 1 no 1 2
501 2 no 1 3
502 1 no 1 2
503 1 no 1 2
504 15 no 1 16
505 8 no 1 9
506 9 no 1 10
507 2 no 1 3
508 13 no 1 14
509 4 yes 0 4
510 1 no 1 2
511 11 no 1 12
512 14 no 1 15
513 6 no 1 7
514 1 no 1 2
515 16 no 1 17
516 5 no 1 6
517 2 no 1 3
518 1 no 1 2
519 13 no 1 14
520 1 no 1 2
521 1 no 1 2
522 13 no 1 14
523 4 yes 0 4
524 1 no 1 2
525 9 no 1 10
526 3 no 1 4
527 9 no 1 10
528 7 no 1 8
529 1 yes 0 1
530 11 no 1 12
531 4 no 1 5
532 5 no 1 6
533 28 no 1 29
534 12 no 1 13
535 8 no 1 9
536 11 no 1 12
537 8 no 1 9
538 2 no 1 3
539 1 no 1 2
540 1 yes 0 1
541 1 no 1 2
542 3 no 1 4
543 3 no 1 4
544 6 no 1 7
545 1 no 1 2
546 3 no 1 4
547 13 no 1 14
548 3 no 1 4
549 1 no 1 2
550 1 no 1 2
551 1 yes 0 1
552 1 no 1 2
553 1 no 1 2
554 6 no 1 7
555 1 no 1 2
556 1 no 1 2
557 8 no 1 9
558 4 no 1 5
559 3 no 1 4
560 9 yes 0 9
561 1 no 1 2
562 4 no 1 5
563 1 no 1 2
564 21 no 1 22
565 5 no 1 6
566 2 no 1 3
567 4 no 1 5
568 8 no 1 9
569 1 no 1 2
570 8 no 1 9
571 5 no 1 6
572 1 no 1 2
573 1 no 1 2
574 2 no 1 3
575 1 no 1 2
576 26 no 1 27
577 10 no 1 11
578 2 no 1 3
579 3 yes 0 3
580 18 no 1 19
581 1 no 1 2
582 7 no 1 8
583 1 no 1 2
584 4 no 1 5
585 13 no 1 14
586 5 no 1 6
587 1 no 1 2
588 3 no 1 4
589 5 no 1 6
590 4 no 1 5
591 1 no 1 2
592 6 no 1 7
593 5 no 1 6
594 10 no 1 11
595 1 no 1 2
596 1 no 1 2
597 6 no 1 7
598 5 no 1 6
599 4 no 1 5
600 6 no 1 7
601 5 no 1 6
602 6 no 1 7
603 1 no 1 2
604 1 no 1 2
605 2 no 1 3
606 7 no 1 8
607 1 no 1 2
608 4 no 1 5
609 1 no 1 2
610 13 no 1 14
611 1 no 1 2
612 1 no 1 2
613 3 no 1 4
614 1 no 1 2
615 3 no 1 4
616 4 no 1 5
617 1 no 1 2
618 6 no 1 7
619 4 yes 0 4
620 1 no 1 2
621 9 no 1 10
622 16 no 1 17
623 1 no 1 2
624 1 no 1 2
625 1 no 1 2
626 3 no 1 4
627 1 no 1 2
628 1 no 1 2
629 15 yes 0 15
630 7 no 1 8
631 1 no 1 2
632 1 no 1 2
633 2 yes 0 2
634 6 no 1 7
635 4 no 1 5
636 7 no 1 8
637 5 no 1 6
638 28 no 1 29
639 10 no 1 11
640 3 no 1 4
641 16 no 1 17
642 2 no 1 3
643 1 no 1 2
644 10 no 1 11
645 3 no 1 4
646 17 no 1 18
647 1 no 1 2
648 14 no 1 15
649 13 no 1 14
650 7 no 1 8
651 15 no 1 16
652 7 no 1 8
653 1 no 1 2
654 1 no 1 2
655 8 no 1 9
656 5 no 1 6
657 9 no 1 10
658 4 yes 0 4
659 18 no 1 19
660 3 no 1 4
661 1 no 1 2
662 1 no 1 2
663 4 no 1 5
664 2 no 1 3
665 1 yes 0 1
666 1 no 1 2
667 1 no 1 2
668 7 no 1 8
669 5 no 1 6
670 23 no 1 24
671 4 no 1 5
672 1 no 1 2
673 4 no 1 5
674 6 no 1 7
675 1 no 1 2
676 3 yes 0 3
677 1 no 1 2
678 8 no 1 9
679 2 no 1 3
680 1 no 1 2
681 1 no 1 2
682 3 no 1 4
683 1 no 1 2
684 12 yes 0 12
685 1 no 1 2
686 5 no 1 6
687 2 no 1 3
688 5 no 1 6
689 2 no 1 3
690 12 no 1 13
691 2 no 1 3
692 1 no 1 2
693 1 no 1 2
694 1 no 1 2
695 24 no 1 25
696 1 no 1 2
697 15 no 1 16
698 13 yes 0 13
699 1 no 1 2
700 2 no 1 3
701 16 no 1 17
702 7 yes 0 7
703 9 no 1 10
704 3 no 1 4
705 3 no 1 4
706 14 yes 0 14
707 7 no 1 8
708 9 no 1 10
709 1 no 1 2
710 2 yes 0 2
711 3 no 1 4
712 1 yes 0 1
713 8 no 1 9
714 4 no 1 5
715 1 no 1 2
716 10 yes 0 10
717 4 no 1 5
718 14 no 1 15
719 4 no 1 5
720 3 yes 0 3
721 2 no 1 3
722 3 no 1 4
723 1 no 1 2
724 2 no 1 3
725 2 no 1 3
726 1 no 1 2
727 1 yes 0 1
728 1 no 1 2
729 3 no 1 4
730 2 no 1 3
731 3 no 1 4
732 1 no 1 2
733 1 no 1 2
734 2 no 1 3
735 1 no 1 2
736 1 no 1 2
737 6 yes 0 6
738 7 no 1 8
739 23 no 1 24
740 12 no 1 13
741 22 no 1 23
742 9 no 1 10
743 11 no 1 12
744 1 no 1 2
745 5 no 1 6
746 1 no 1 2
747 19 no 1 20
748 6 no 1 7
749 2 no 1 3
750 1 no 1 2
751 21 no 1 22
752 1 no 1 2
753 29 no 1 30
754 1 yes 0 1
755 7 no 1 8
756 2 no 1 3
757 6 no 1 7
758 1 no 1 2
759 8 no 1 9
760 8 no 1 9
761 9 no 1 10
762 19 no 1 20
763 6 no 1 7
764 4 no 1 5
765 6 no 1 7
766 4 no 1 5
767 3 no 1 4
768 15 no 1 16
769 6 no 1 7
770 6 no 1 7
771 1 no 1 2
772 7 yes 0 7
773 3 yes 0 3
774 21 no 1 22
775 36 no 1 37
776 1 no 1 2
777 2 no 1 3
778 14 no 1 15
779 12 no 1 13
780 2 no 1 3
781 5 no 1 6
782 4 no 1 5
783 2 yes 0 2
784 1 yes 0 1
785 4 no 1 5
786 6 no 1 7
787 3 no 1 4
788 1 no 1 2
789 2 no 1 3
790 1 no 1 2
791 10 no 1 11
792 3 no 1 4
793 2 no 1 3
794 4 yes 0 4
795 5 no 1 6
796 1 no 1 2
797 10 no 1 11
798 1 yes 0 1
799 1 no 1 2
800 1 no 1 2
801 5 no 1 6
802 1 no 1 2
803 1 no 1 2
804 2 no 1 3
805 10 no 1 11
806 2 no 1 3
807 5 no 1 6
808 5 no 1 6
809 4 no 1 5
810 3 no 1 4
811 2 no 1 3
812 1 no 1 2
813 6 no 1 7
814 6 no 1 7
815 2 no 1 3
816 5 no 1 6
817 9 no 1 10
818 2 no 1 3
819 1 no 1 2
820 11 no 1 12
821 1 no 1 2
822 3 no 1 4
823 1 no 1 2
824 5 yes 0 5
825 45 no 1 46
826 15 no 1 16
827 3 no 1 4
828 1 no 1 2
829 11 no 1 12
830 10 no 1 11
831 32 no 1 33
832 2 yes 0 2
833 2 no 1 3
834 5 no 1 6
835 1 no 1 2
836 5 yes 0 5
837 5 no 1 6
838 1 no 1 2
839 5 no 1 6
840 3 no 1 4
841 5 no 1 6
842 3 yes 0 3
843 1 no 1 2
844 32 yes 0 32
845 11 no 1 12
846 2 yes 0 2
847 2 no 1 3
848 2 no 1 3
849 1 no 1 2
850 16 no 1 17
851 8 no 1 9
852 7 no 1 8
853 6 no 1 7
854 2 no 1 3
855 4 no 1 5
856 12 no 1 13
857 5 no 1 6
858 10 yes 0 10
859 4 no 1 5
860 17 no 1 18
861 1 no 1 2
862 20 no 1 21
863 6 no 1 7
864 5 yes 0 5
865 9 no 1 10
866 7 no 1 8
867 4 no 1 5
868 1 no 1 2
869 7 no 1 8
870 3 no 1 4
871 5 no 1 6
872 2 no 1 3
873 5 yes 0 5
874 9 no 1 10
875 1 no 1 2
876 1 no 1 2
877 1 no 1 2
878 4 no 1 5
879 1 no 1 2
880 9 no 1 10
881 7 no 1 8
882 3 no 1 4
883 1 no 1 2
884 4 no 1 5
885 4 no 1 5
886 1 no 1 2
887 4 no 1 5
888 18 no 1 19
889 19 no 1 20
890 7 no 1 8
891 1 no 1 2
892 1 no 1 2
893 6 no 1 7
894 2 no 1 3
895 1 no 1 2
896 1 no 1 2
897 2 no 1 3
898 5 no 1 6
899 2 no 1 3
900 14 no 1 15
901 9 no 1 10
902 2 no 1 3
903 1 yes 0 1
904 17 no 1 18
905 24 no 1 25
906 2 no 1 3
907 1 no 1 2
908 4 no 1 5
909 5 no 1 6
910 1 no 1 2
911 2 no 1 3
912 1 no 1 2
913 11 no 1 12
914 1 no 1 2
915 6 no 1 7
916 8 no 1 9
917 2 no 1 3
918 11 no 1 12
919 3 no 1 4
920 2 no 1 3
921 13 no 1 14
922 10 no 1 11
923 6 no 1 7
924 17 no 1 18
925 3 no 1 4
926 7 no 1 8
927 5 no 1 6
928 6 no 1 7
929 8 no 1 9
930 16 no 1 17
931 14 no 1 15
932 12 no 1 13
933 1 no 1 2
934 2 no 1 3
935 3 no 1 4
936 10 yes 0 10
937 6 no 1 7
938 12 no 1 13
939 19 no 1 20
940 39 no 1 40
941 3 no 1 4
942 2 yes 0 2
943 4 no 1 5
944 6 no 1 7
945 5 no 1 6
946 11 no 1 12
947 18 no 1 19
948 31 no 1 32
949 1 no 1 2
950 7 yes 0 7
951 1 no 1 2
952 13 no 1 14
953 1 no 1 2
954 1 no 1 2
955 8 no 1 9
956 12 yes 0 12
957 1 no 1 2
958 13 no 1 14
959 1 no 1 2
960 1 no 1 2
961 8 no 1 9
962 17 no 1 18
963 5 no 1 6
964 6 no 1 7
965 15 no 1 16
966 1 no 1 2
967 11 no 1 12
968 6 no 1 7
969 1 no 1 2
970 1 no 1 2
971 2 no 1 3
 972 6 no 1 7
973 1 no 1 2
974 6 no 1 7
975 1 no 1 2
976 5 no 1 6
977 6 no 1 7
978 1 no 1 2
979 1 no 1 2
980 12 no 1 13
981 7 no 1 8
982 5 no 1 6
983 3 no 1 4
984 4 no 1 5
985 27 no 1 28
986 1 no 1 2
987 6 no 1 7
988 2 no 1 3
989 20 yes 0 20
990 1 no 1 2
991 9 yes 0 9
992 7 no 1 8
993 1 no 1 2
994 4 no 1 5
995 11 no 1 12
996 10 no 1 11
997 11 no 1 12
998 3 no 1 4
999 2 no 1 3
1000 4 no 1 5
 0.134575
0.865425

Chances of Quits
 Support
Total Trans 120
Apple only 55 0.458
oranges only 30 0.250
Grapes only 25 0.208
Apple,oranges 23 0.41818 Oranges
Apple,Grapes 10 0.4 Apple
Grapes,oranges 17 0.68 Oranges

Lift(A,O) 1.672727
A,G 0.872727
O,G 2.72
0.766667 Apple
0.181818 Grapes Confidence
0.566667 Grapes
 Points
Recency 20 if less than 3 months
10 if less than 6 months
6 if less than 9 months
3 if less than 12 months

1 if less than 24 months

Recency 3 Frequency 5 Monetary 3

0.1 Value of Purchase

Weight Weight
Recency Frequency Points
Weight(R Weight(P
Customer (Times (frequenc $Spent
ecency) oints)
(months) purchased) y)
A 3 20 60 4 20 80 1722
F 20 1 20 5 20 100 50
P 6 10 60 7 20 140 150
M 9 6 54 1 5 5 1654
K 13 1 13 1 5 5 1202
O 15 1 15 7 20 140 190
B 10 3 30 7 20 140 1510
D 6 10 60 5 20 100 2000
E 2 20 40 4 20 80 1567
 Data for Customers

Frequenc
Recency
y (Times
Customer $ spent
purchase
(months)
d)

A 3 4 1722
F 20 5 50
Value of Purchase P 6 7 150
M 9 1 1654
K 13 1 1202
O 15 7 190
B 10 7 1510
D 6 5 2000
E 2 4 1567

Total
Weight
Weight Rank
20 160 5
5 125 7
15 215 1
20 79 8
20 38 9
19 174 4
20 190 2
20 180 3
20 140 6
Sales Price Ad P*A Model ESS
22845 8 1 8 24339.34 2233050.93
20417 9 8 72 20472.77 3109.84
23761 5 3 15 23893.06 17439.30
22674 4 12 48 21890.89 613261.05
22782 7 5 35 22697.73 7100.64
23807 5 3 15 23893.06 7405.97
18924 10 9 90 19390.28 217414.77
21855 9 5 45 22107.22 63615.93
21749 10 4 40 22417.39 446742.06
22683 4 12 48 21890.89 627438.03
20968 6 11 66 20814.94 23427.60
22202 10 2 20 23628.23 2034136.82
23241 6 5 30 22993 61508.45
19004 10 9 90 19390.28 149210.36
23978 4 1 4 24550.71 327998.44
20497 8 9 72 20465.62 984.89
22322 9 3 27 23196.86 765378.84
22628 8 4 32 22886.69 66922.41
21051 10 6 60 21206.54 24193.82
24515 3 3 9 24241.16 74989.85
22126 10 2 20 23628.23 2256700.04
22141 5 11 55 21473.82 445134.95
21151 9 7 63 21017.58 17799.66
22558 5 10 50 21776.22 611178.49
21734 7 8 56 21426.9 94311.18
22137 6 9 54 21541 355267.86
23368 5 7 35 22683.44 468626.77
24572 3 7 21 23516.36 1114369.73
23732 5 4 20 23590.65 19979.07
24717 3 6 18 23697.56 1039254.91
21618 8 7 56 21434 33838.45
24346 3 9 27 23154 1420945.79
24041 3 11 33 22791.57 1561079.06
18068 10 10 100 18784.86 513881.89
22820 8 1 8 24339.34 2308392.91
22842 8 3 24 23370.91 279744.71
23166 6 6 36 22630 287314.87
20979 9 7 63 21017.58 1488.77
22499 9 2 18 23741.68 1544248.60
21026 9 7 63 21017.58 70.82
24599 3 6 18 23697.56 812591.41
23676 5 1 5 24497.87 675467.86
22855 6 7 42 22267 345774.86
21756 10 4 40 22417.39 437433.63
20976 10 6 60 21206.54 53150.36
22111 10 2 20 23628.23 2301991.99
21038 6 11 66 20814.94 49756.11
23050 6 6 36 22630 176414.79
24054 4 7 28 23099.9 910307.11
22184 7 7 49 21850.51 111215.10
24024 4 2 8 24308.91 81173.45
24255 3 1 3 24603.55 121490.20
23635 5 1 5 24497.87 744542.08
20533 10 7 70 20601.12 4640.55
24313 3 1 3 24603.55 84421.89
24347 3 2 6 24422.36 5678.50
24102 3 11 33 22791.57 1717230.71
24482 3 2 6 24422.36 3557.42
15799 10 12 120 17574 3150665.90
21597 6 10 60 21177.95 175604.69
22450 9 3 27 23196.86 557798.85
18978 8 11 88 19497.19 269554.50
20687 7 10 70 20579.67 11518.70
20773 7 10 70 20579.67 37374.64
23681 5 5 25 23288.25 154254.63
22191 10 2 20 23628.23 2065634.92
24244 4 4 16 23825.31 175304.95
22617 8 4 32 22886.69 72734.67
23139 6 6 36 22630 259098.92
22154 5 11 55 21473.82 462650.74
23364 4 10 40 22374.49 979122.08
22942 7 4 28 23121.35 32165.22
21639 6 10 60 21177.95 212569.07
22633 7 6 42 22274.12 128792.92
23145 5 8 40 22381 583647.85
23384 4 10 40 22374.49 1019102.32
22232 10 2 20 23628.23 1949462.92
22820 5 9 45 22078.63 549635.07
18850 10 9 90 19390.28 291899.85
24627 3 8 24 23335.16 1668839.51
23091 7 1 7 24392.18 1693076.14
24034 4 2 8 24308.91 75575.26
23002 7 4 28 23121.35 14243.62
19346 7 12 84 19732.45 149344.24
23127 7 1 7 24392.18 1600686.99
24508 3 8 24 23335.16 1375543.61
23864 5 3 15 23893.06 844.36
19054 8 11 88 19497.19 196414.17
22178 10 2 20 23628.23 2103171.94
23862 5 4 20 23590.65 73629.38
22339 8 5 40 22402.48 4029.50
21580 9 6 54 21562.4 309.64
23114 7 3 21 23545 185725.35
21066 6 11 66 20814.94 63031.51
23126 7 1 7 24392.18 1603218.36
21993 5 11 55 21473.82 269552.38
22952 5 9 45 22078.63 762781.74
24233 4 6 24 23341.7 794412.51
20346 9 8 72 20472.77 16069.61
24658 3 6 18 23697.56 922442.16
21884 7 8 56 21426.9 208941.56
22610 7 6 42 22274.12 112813.56
22232 10 2 20 23628.23 1949462.92
18847 9 10 90 19383.13 287433.91
20109 7 11 77 20156.06 2214.91
20331 6 12 72 20451.93 14624.21
23713 5 5 25 23288.25 180414.79
21883 9 5 45 22107.22 50275.50
23460 4 10 40 22374.49 1178323.23
21093 8 8 64 20949.83 20496.97
22595 5 10 50 21776.22 670399.14
23652 4 9 36 22616.3 1072682.86
19690 10 8 80 19995.7 93452.24
23815 5 5 25 23288.25 277468.33
21002 6 11 66 20814.94 34991.73
21661 8 7 56 21434 51507.35
21572 9 6 54 21562.4 92.10
22366 9 3 27 23196.86 690327.22
21630 5 12 60 21171.41 210304.45
22106 6 9 54 21541 319274.16
22643 8 4 32 22886.69 59386.60
23951 4 1 4 24550.71 359653.86
23403 6 3 18 23719 99861.24
24059 4 2 8 24308.91 62454.78
23387 6 2 12 24082 483048.52
22033 6 9 54 21541 242106.81
20002 7 11 77 20156.06 23735.35
21516 5 12 60 21171.41 118742.01
22572 8 4 32 22886.69 99032.10
22552 8 4 32 22886.69 112019.84
22927 7 5 35 22697.73 52562.59
23223 6 5 30 22993 52904.13
24287 3 1 3 24603.55 100206.72
24600 3 3 9 24241.16 128768.11
21517 5 12 60 21171.41 119432.19
23672 5 6 30 22985.84 470812.68
22034 6 9 54 21541 243091.90
20464 9 8 72 20472.77 76.84
22007 10 3 30 23022.81 1031869.29
16957 9 12 108 18293.49 1786208.97
22740 8 2 16 23855.12 1243502.22
22576 5 10 50 21776.22 639646.54
24257 3 10 30 22972.77 1649254.15
16825 9 12 108 18293.49 2156466.67
20463 6 12 72 20451.93 122.53
21541 6 10 60 21177.95 131806.85
21884 9 5 45 22107.22 49828.05
22047 9 5 45 22107.22 3626.69
24270 4 5 20 23583.5 471277.14
24248 4 5 20 23583.5 441555.30
22737 8 3 24 23370.91 401840.60
23271 6 5 30 22993 77288.99
22653 8 4 32 22886.69 54612.73
24576 3 7 21 23516.36 1122830.83
18095 8 12 96 19013 842670.87
23815 5 2 10 24195.46 144752.27
22886 7 5 35 22697.73 35443.83
23843 5 5 25 23288.25 307750.48
21046 10 6 60 21206.54 25774.25
20544 8 9 72 20465.62 6143.89
20384 6 12 72 20451.93 4614.57
21130 6 11 66 20814.94 99263.29
23495 5 7 35 22683.44 658634.83
18869 10 9 90 19390.28 271730.31
23943 4 7 28 23099.9 710817.88
24761.47
7.760383 P A company is currently using a sales model of
0.611444 A
-60.6033 P*A Sales = c0+c1P+c2A+c3(P*A)
What is the predicted value in case the company was to Pri
SUM 82110063.44 product at 12 and spend 8 in advertising?

Would the results be different if the model adopted was

Sales = c0 + c1P + c2A + c3(P*A)+ c4 P2 + c5A

Which model is better predictor of sales? Why?

es model of

*A)
e the company was to Price the
rtising?

e model adopted was

3(P*A)+ c4 P2 + c5A2

sales? Why?
Chapter 8
Problem 1

Cart Price
Week Notice? Coupon? Reduction? Sales
1 Yes Yes 0 36
2 Yes Yes 1 38
3 Yes Yes 2 40
4 Yes No 0 40
5 Yes No 1 42
6 Yes No 2 44
7 No Yes 0 12
8 No Yes 1 20
9 No Yes 2 30
10 No No 0 8
11 No No 1 16
12 No No 2 33

Sum

Cart Price
Week Notice? Coupon? Reduction? Sales Model ESS
1 1 1 0 36 35.99537 2.14E-05
2 1 1 1 38 38.00132 1.74E-06
3 1 1 2 40 40.00726 5.28E-05
4 1 0 0 40 39.9934 4.35E-05
5 1 0 1 42 41.99935 4.24E-07
6 1 0 2 44 44.00529 2.8E-05
7 0 1 0 12 11.99911 8.01E-07
8 0 1 1 20 19.9975 6.25E-06
9 0 1 2 30 29.99338 4.38E-05
10 0 0 0 8 8.0072 5.18E-05
11 0 0 1 16 16.0056 3.13E-05
12 0 0 2 33 32.99267 5.38E-05
 For 12 straight weeks, you have observed the sales (in number
of cases) of canned tomatoes at Mr. D's Supermarket . (See
the file Gr o ce r y . xl s x.) Each week, you keep track of the
following:
Was a promotional notice for canned tomatoes placed in all
shopping carts?
Was a coupon for canned tomatoes given to each customer?
Was a price reduction (none, 1, or 2 cents off) given?

Use this data to determine how the preceding factors influence

sales. Predict sales of canned tomatoes during a week in which
you use a shopping cart notice, a coupon, and reduce price by
1 cent.

Constant 0.017266
Cart
Notice? 0.026467
Coupon? -0.00306
Price
Reductio
n? 0.008462
Sales 0.998742

0.000336 Minimise

Chart Title
100
90
80
70
60
50
40
30
20
10
0
1 2 3 4 5 6 7 8 9 10 11 12

Column G Column H