BACKGROUND INFORMATION : Open the Snappos email database. Snappos is a hypothetical online shoe retailer (like Zappos). Snappos has only recently begun their email marketing efforts. They have collected 250 email addresses and have been sending bi-weekly emails 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. The database provides information about the 16 sent emails and the resulting action of each of the 250 members of the email list.

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 fields:

Each field 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 field 1. Email 1 has the following properties:

ToD	4
Offer	5
F1	3
F2	1
F3	6

This means this email was sent in the evening. The subject line talked about new products, specifically new womens high heels. Womens high heels were pictured in field 1; womens athletic shoes were pictured in field 2; and womens boots were pictured in field 3.

Email Response

Below is the response key.

0	Delivered, unopened
1	Hard bounce
2	Soft bounce
3	Delivered, opened
4	Field 1 clicked
5	Field 2 clicked
6	Field 3 clicked

QUESTION:

1. Calculate the Open Rate and Click-Through Rate for each Offer. Which offers generate the best response?

Offer	Open Rate	Click-Through Rate
1. BOGO
2. 20% off
3. 30% off
4. 50% off
5. New products
6. Free shipping