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Read the Excel and the Word doc firstDo the calculation and explanation in the Excel detaillyFinal answers need to be in the excel!!!
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Email ID
Time of Day
Offer
S1
S2
S3
Delivered
Opened
Male
Open Rate
1
4
5
3
1
6
89
5
2
4
3
8
4
7
89
15
3
2
2
7
2
9
89
21
4
3
6
2
10
8
88
6
5
1
4
4
1
3
87
6
6
2
1
10
3
5
86
25
7
3
1
8
7
10
86
25
8
1
5
1
8
3
84
3
9
3
4
6
9
1
84
5
10
2
2
9
3
8
84
18
11
3
5
7
9
5
84
26
12
3
5
2
10
1
84
5
13
2
3
4
3
6
84
4
14
3
2
5
6
10
84
3
15
4
2
2
5
7
84
2
16
1
6
1
3
4
84
2
Coding Key
Time of Day
1 Early Morning
2 Late Morning
3 Afternoon
4 Evening
5
6
7
8
9
10
Section
Offer
Women’s athletic shoes
BOGO
Women’s dress flats
20% off
Women’s high heels
30% off
50% off
Women’s sandals
Women’s slippers
New
Free shippingWomen’s boots
Men’s athletic shoes
Men’s sandals
Men’s dress shoes
Men’s boots
Response Key
0 Delivered, unopened
1 Hard bounce
2 Soft bounce
3 Delivered, opened
4 Section 1 clicked
5 Section 2 clicked
6 Section 3 clicked
Gender
0 Female
1 Male
Question 1
Which recipients should be
Hard bounces:
Multiple soft bounces in a row:
No response for two months:
Question 2
Time of Day
Early Morning
Late Morning
Afternoon
Evening
What is the best time of da
Open Rate
12,5%
13,4%
16,2%
14,4%
Question 3
Offer
BOGO
20% off
30% off
50% off
New products
Free shipping
Which offers generate the b
Open Rate
Question 4
Snappos is looking to segm
Matching
Open
Rates
gender
Females
Males
Click
Rate
Matching
gender
Females
Males
Question 5
Snappos will soon be runni
Rank
Segment
1
2
3
4
5
6
Male
Clicks
Click Rate Delivered
Female
Open Rate
Opened
Tota
Clicks
Click Rate Total Recipients
Bounced
1
148
32
5
250
13
1
148
15
7
250
13
5
148
11
3
250
13
2
148
30
7
250
14
0
148
32
9
250
15
4
147
17
2
250
17
4
147
21
9
250
17
1
147
24
5
250
19
1
147
54
11
250
19
7
147
10
3
250
19
3
147
15
2
250
19
1
146
23
6
250
20
0
146
28
6
250
20
1
146
30
8
250
20
0
146
39
8
250
20
1
146
27
6
250
20
Which recipients should be removed from the email list?
unces in a row:
two months:
What is the best time of day to send emails?
Click Rate
Why do you think that is?
More emails check in the afternooon, People taking break
Which offers generate the best response?
Click Rate
Why do you think that is?
People are price sensative, Highest discount
Snappos is looking to segment this email list. Should they put men in one segment and women in the other and only send emails featuring the prop
Opposite
Explain why?
pen Rates
gender
Depends on the event, Reduce frequency/ Optimize the frequency of
sending opposite gender email
lick Rate
Opposite
gender
Depends on the event, Reduce frequency/ Optimize the frequency of
sending opposite gender email
Snappos will soon be running a sale on women’s high heels. Which segmentation practice is best (rank from 1-most effective to 6-least effective)?
Unopened
Total
Opened
Open Rate
Clicks
Click Rate
200
37
14,8%
6
207
30
12,0%
8
205
32
12,8%
8
200
36
14,4%
9
197
38
15,2%
9
191
42
16,8%
6
187
46
18,4%
13
204
27
10,8%
6
172
59
23,6%
12
203
28
11,2%
10
190
41
16,4%
5
202
28
11,2%
7
198
32
12,8%
6
197
33
13,2%
9
189
41
16,4%
8
201
29
11,6%
7
y send emails featuring the proper gendered shoe to those lists?
Recipients
Gender Opens Clicks Email 1
1
0
3
1
2
1
1
0
3
0
2
2
4
0
3
2
5
0
6
3
6
0
0
0
7
0
4
0
8
1
1
0
9
1
2
0
10
0
4
0
11
0
1
0
12
1
3
0
13
1
3
1
14
1
1
1
15
0
2
0
16
0
4
0
17
1
3
1
18
0
1
0
19
1
2
0
20
0
4
0
21
1
1
0
22
1
0
0
23
1
2
0
24
1
0
0
25
1
3
0
26
0
4
0
27
0
0
0
28
1
4
0
29
1
2
0
30
1
1
1
31
1
1
1
32
1
0
0
33
0
0
0
34
0
4
3
35
1
3
0
36
0
3
0
37
1
3
2
38
1
1
0
39
0
4
0
40
1
3
0
41
1
0
0
42
0
5
4
43
0
1
0
44
0
1
0
45
1
2
1
46
0
4
0
Email 2
0
0
0
3
0
1
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
3
0
0
3
0
0
4
0
0
0
0
Email 3
0
0
0
0
0
1
0
0
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
3
0
1
3
0
0
0
0
0
0
0
0
0
0
0
0
0
4
0
0
0
0
Email 4
0
0
0
0
0
1
0
0
0
0
0
0
0
4
0
0
3
0
0
0
3
0
0
0
3
0
1
3
0
0
0
0
0
0
0
0
4
0
0
0
0
0
0
0
0
0
Email 5
0
0
4
0
0
1
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
1
3
3
5
0
0
0
0
0
0
0
0
0
3
0
0
0
0
0
0
Email 6
3
0
0
4
3
1
0
0
0
3
0
0
0
0
3
0
3
0
0
3
0
0
0
2
0
0
1
0
0
0
0
0
0
4
0
0
0
0
3
0
0
0
0
0
0
3
Email 7
0
0
0
0
0
1
0
0
0
0
0
0
0
0
3
0
0
0
0
3
2
0
0
2
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
5
1
0
0
3
0
0
0
4
0
0
0
0
0
3
0
2
0
3
2
0
3
1
3
0
0
0
0
0
0
3
0
0
3
0
0
0
0
0
0
3
0
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
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75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
1
0
0
0
0
1
1
0
1
0
0
1
0
0
0
1
1
1
0
0
0
0
1
1
1
1
0
1
0
0
1
0
0
0
1
1
1
0
0
1
0
1
1
0
0
0
0
1
0
3
4
4
2
2
3
1
4
2
3
1
0
3
1
3
4
3
5
3
3
3
1
0
1
0
2
1
4
8
2
2
0
5
2
0
1
1
2
3
2
6
2
1
6
3
3
0
1
4
0
3
0
0
0
1
0
2
0
0
1
0
1
0
1
0
1
2
1
1
0
1
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
1
0
2
5
1
1
0
0
0
0
1
0
0
0
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
1
3
0
1
0
0
0
3
0
4
0
0
0
0
0
1
0
3
0
0
0
0
0
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
3
0
0
0
1
0
3
1
0
0
0
0
0
5
0
0
0
0
0
1
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
3
0
0
0
0
0
1
0
0
0
0
0
3
0
0
1
0
0
1
3
0
0
0
5
4
0
0
3
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
3
0
3
4
1
0
0
0
0
0
0
0
0
1
0
0
1
0
0
0
3
0
0
0
0
3
0
0
1
0
0
0
4
0
0
3
0
0
3
0
0
0
0
3
0
0
3
0
0
0
4
0
0
1
0
0
0
0
0
0
3
0
1
4
0
1
0
0
0
0
0
4
0
0
3
0
0
1
0
0
0
3
0
0
0
0
0
0
0
3
0
0
0
0
0
0
0
3
0
0
0
0
1
3
0
0
0
0
3
0
0
1
0
0
1
0
0
0
0
0
0
3
4
0
0
3
1
0
0
3
0
0
0
0
0
0
0
0
0
5
0
0
0
0
0
0
3
0
0
0
0
1
0
0
3
0
3
3
0
0
1
6
0
1
0
0
4
0
0
0
0
0
3
3
0
1
0
0
96
97
98
99
100
101
102
103
104
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112
113
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125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
0
1
0
0
1
0
0
0
0
0
0
0
0
1
0
0
1
0
0
0
0
1
0
1
0
0
0
0
0
1
0
1
0
1
1
1
0
1
0
0
0
0
0
0
1
0
0
0
1
4
2
3
0
3
3
1
2
3
1
3
0
0
2
0
4
3
3
2
3
5
3
3
6
2
2
4
4
4
1
1
0
0
2
2
3
1
1
2
0
1
3
4
0
2
5
6
3
1
1
0
0
0
0
0
0
0
2
0
0
0
0
0
0
2
0
0
2
2
0
1
0
1
0
0
0
1
3
0
0
0
0
0
1
0
0
0
0
0
0
3
0
0
0
0
2
2
0
0
0
0
0
0
3
0
0
4
0
0
0
1
0
1
4
0
0
0
3
3
5
0
0
0
0
3
0
0
0
0
0
0
0
0
3
0
0
0
0
0
0
0
0
0
3
3
0
0
0
3
0
0
3
0
0
0
4
0
0
0
1
0
1
0
3
0
4
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
3
4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
3
1
0
3
0
0
5
0
0
0
4
0
0
0
0
0
0
0
0
0
0
0
3
0
3
0
0
0
4
0
0
0
0
0
0
0
3
0
0
0
0
0
0
0
0
0
3
0
1
0
1
0
0
0
0
0
3
0
0
0
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
4
0
3
0
3
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
0
4
3
3
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
3
1
0
0
3
0
0
0
3
0
3
0
0
0
0
0
3
0
0
0
0
3
0
0
0
0
2
0
0
3
0
0
0
3
0
3
0
0
0
0
3
0
0
0
0
0
3
0
1
0
1
0
0
0
4
0
0
0
0
0
0
0
0
5
4
0
0
0
0
3
5
0
0
0
0
2
0
0
3
0
3
0
0
0
0
145
146
147
148
149
150
151
152
153
154
155
156
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158
159
160
161
162
163
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174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
0
0
0
0
0
0
0
1
1
0
1
0
0
1
0
1
0
0
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
1
1
0
0
0
4
0
3
3
3
2
2
2
3
2
2
3
3
0
3
2
1
0
4
3
5
2
4
3
3
0
2
3
3
3
3
3
4
4
2
2
6
0
1
1
3
3
1
2
0
3
6
0
0
1
0
0
0
0
0
0
1
0
1
2
2
0
0
1
1
0
0
0
0
4
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
1
2
1
0
3
0
0
0
3
0
0
0
0
0
0
0
3
1
0
0
0
0
0
0
0
0
3
0
3
0
0
0
0
0
3
0
3
0
0
0
3
0
0
0
0
0
0
0
1
0
0
1
0
3
0
0
0
0
0
0
0
0
0
0
4
0
1
0
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
1
3
0
1
0
0
0
0
0
0
0
0
0
0
0
0
5
0
1
0
0
0
0
3
3
0
3
0
3
0
0
3
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
0
0
0
3
0
0
0
4
0
3
0
0
0
0
0
1
0
3
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
4
0
0
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
1
0
0
1
0
0
0
0
0
0
0
0
0
3
0
0
3
3
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
3
0
0
0
0
0
0
0
0
3
0
3
1
4
0
1
0
0
0
0
0
0
3
0
3
3
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
3
194
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EMAIL PERFORMANCE ANALYSIS EXERCISE
Email Performance Analysis Exercise
An online shoe retailer has only recently begun their email marketing efforts. They have
collected 250 email addresses and have been sending emails twice a week to their entire email
list for the last eight weeks. They have made no efforts to clean, segment, or optimize their
email list in any way, but they realize–as you do–that the better the segmentation, the more
effective their email marketing will be. Your job is to analyze the email data to answer the
following questions, to segment the email list in ways that will help the retailer save time,
money, and better their customer relationship management.
1. Which recipients should be removed from the email list?
(Hint: Look for Hard bounces, Multiple soft bounces in a row, and No response for two
months)
2. What is the best time of day to send emails? Why do you think that is?
3. Which offers generate the best engagement? Why do you think that is?
(Hint: Compare the open rates and click rates of each offer to determine which
generates the best engagement.)
4. The retailer is looking to segment this email list. Should it put men in one segment and
women in the other and only send emails featuring the proper gendered shoe to those
lists? Explain why or why not.
(Hint: First compare the open rates of male and female to the gendered products.
Next compare the click rate to male and female to the gendered products.
Explain what you have learned when matching products and the intended gender, and
whether they should segment by gender.)
5. The retailer will soon be running a sale on women’s high heels. Rank the following
segmentation practices from 1-most effective to 6-least effective to determine who
should receive this email.
●
●
●
●
●
●
Has a high open Rate generally for emails
Clicked Section 1 of Email 1; Section 2 of Email 6, 10, 14, or 16; or Section 3 of Email 5
or 8
Opened Email 1 (which featured women’s high heels)
Is a woman
Has a high open Rate for emails featuring women’s shoes
Has a high click-through Rate on sections featuring women’s shoes
Assignment Instructions
➔ Download the Email Performance Report Database. The database provides
information about the 16 sent emails and the resulting action of each of the 250
members of the email list.
➔ Read the section below entitled “Information about Coding Emails”
➔ Answer the questions above in the “Email Overview” sheet.
➔ Make sure your functions are visible for grading.
➔ Include your written explanations in the boxes provided.
Information About the Emails
The coding key for the emails is as follows:
Key
Time of Day
Offer
Category
1
Early Morning
BOGO
Women’s athletic shoes
2
Late Afternoon
20% off
Women’s dress flats
3
Afternoon
30% off
Women’s high heels
4
Evening
50% off
Women’s sandals
5
New products
Women’s slippers
6
Free shipping
Women’s boots
7
Men’s athletic shoes
8
Men’s sandals
9
Men’s dress shoes
10
Men’s boots
Each of the 16 emails had the same layout with three visual sections:
Each section featured one of ten possible shoe categories. Emails were sent at various times of
the day. The subject line of each email featured an offer and highlighted the product category in
section 1.
Email 1 has the following properties:
Time of Day
4
Offer
5
Section 1 (S1)
3
Section 2 (S2)
1
Section 3 (S3)
6
This means this email was sent in the evening. The subject line talked about new products,
specifically new women’s high heels. Women’s high heels were pictured in section 1; women’s
athletic shoes were pictured in section 2; and women’s boots were pictured in section 3.
Email Response
Below is the response key.
0
Delivered, unopened
1
Hard bounce
2
Soft bounce
3
Delivered, opened
4
Section 1 clicked
5
Section 2 clicked
6
Section 3 clicked
Most emails were delivered, but unopened (which is typical of email lists). Emails could also
bounce via hard or soft bounce, or be delivered (but result in no clicks). Recipients who opened
the email and clicked on one of the sections are coded 4, 5, or 6 to indicate which section they
clicked. *NOTE: Responses marked as having clicked on a specific section (Response
keys 4,5,6) should be counted with the “Delivered, opened” data.
Purchase answer to see full
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