Email Performance Analysis Exercise An online shoe retailer has only recently be

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, which will help segment the email list in ways that will help them save time, money, and better their customer relationship management
1. Which recipients should be removed from the email list, and why?
2. What is the best time of day to send emails? Why do you think that is?
3. Which offers seem to generate the best response? Why do you think that is?
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.
5. They will soon be running a sale on women’s high heels. Which recipients on the list should receive this email, and why?
The Email Performance Analysis Database provides information about the 16 sent emails and the resulting action of each of the 250 members of the email list. There are student and instructor versions for recording and grading answers respectively (as well as separate instructions for students). The information below will help both students and instructors understand the coding for every email.
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 template layout with 3 varying sections:
Chapter 8 1.png
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.