EMAIL MARKETINGDatabase Analysis ExerciseOpen the Snappos excel file (email list). Snappos is a hypothetical online shoe retailer (like Zappos). Snappos has only recently begun their email...

Very basic assignment, but I'm overburdened this entire weekend and beginning of the week.


EMAIL MARKETING Database Analysis Exercise Open the Snappos excel file (email list). 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 women’s high heels. Women’s high heels were pictured in field 1; women’s athletic shoes were pictured in field 2; and women’s 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 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 fields are coded 4, 5, or 6 to indicate which field they clicked. Analyze the email data to answer the following questions. 1. Which respondents should be removed from the email list? 2. What is the best time of day to send emails? 3. Which offers generate the best response? 4. Snappos 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? 5. Snappos will soon be running a sale on women’s high heels. Which recipients on the list should receive this email? Sheet1 Email Key Time of DayOfferCategoryToD4423123132332341 1Early MorningBOGOWomen's athletic shoesOffer5326411542553226 2Late Morning20% offWomen's dress flatsF138724108169724521 3Afternoon30% offWomen's high heelsF2142101378939103653 4Evening50% offWomen's sandalsF3679835103185161074 5NewWomen's slippers 6Free shippingWomen's bootsRespondentGender (1=Male)Email 1Email 2Email 3Email 4Email 5Email 6Email 7Email 8Email 9Email 10Email 11Email 12Email 13Email 14Email 15Email 16 7Men's athletic shoes100000300000300040 8Men's sandals210000003000000000 9Men's dress shoes300004000004000000 10Men's boots403000400000000004 500000305040030340 601111111111111111 700000000030030033 Response Key810000000003000000 0Delivered, unopened910000003000300000 1Hard bounce1003000300000030003 2Soft bounce1100003000000000000 3Delivered, opened1210000000033300000 4Field 1 clicked1310300004000300000 5Field 2 clicked1410040000222222222 6Field 3 clicked1500000330000000000 1600000000330300003 1710030300004000000 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