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...

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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 1800000000000000300 1910000003000300000 2000000330030000300 2110030022222222222 2210000000000000000 2310000003003000000 2410000222222222222 2510330000000300000 2600003003000000033 2701111111111111111 2810333003000000000 2910003000000300000 3010005000000000000 3110000000050000000 3210000000222222222 3300000000000000000 3400000400000040403 3510000003030300000 3603000000030000030 3710040000000300006 3810000003000000000 3903000300030000300 4010003000003030000 4110000000000000000 4204400000340040000 4300000000000000300 4400000000030000000 4510000003004000000 4600000300033000030 4710030003000003000 4800000430040000040 4900000000030030330 5000000000000030030 5100000300000000300 5210000000004000303 5313000000000000000 5400000300050600003 5510000000000300030 5600300030000003000 5700000005000000000 5810000000000000000 5900000300030004000 6000000000000000003 6100003000040000300 6210030300003300000 6310030000000430000 6410000033500340000 6500003000000000035 6600000400000003030 6700003000300300000 6800004000000000000 6911111111111111111 7010000030000000000 7110000000000000000 7210000003000300000 7300000000030000000 7410300003000330000 7500030033333000330 7600000300300000000 7710000000300300000 7801111111111111111 7903000406430000000 8000300000030000000 8111111111111111111 8210030000000000000 8310000000000300000 8400000004030000000 8503003000030000000 8610050000004000000 8704540400000340000 8810000030004000000 8910000040000000000 9000033303300300000 9100000003003300000 9200000030000000330 9301111111111111111 9410000000000400000 9503000000030000303 9600003300300004000 9710300000000300000 9800000300000003003 9900000000000000000 10010300003003000000 10103000000030030000 10200000000000003000 10300000000300003000 10404400000000000030 10500000000000000300 10600003003000000030 10700000000000000000 10801111111111111111 10910030030000000000 11001111111111111111 11104000000000030430 11210330000000300000 11300000030000030300 11400400004000000000 11503050400000000000 11603003300300000030 11715000330000000000 11800300000030000030 11910040030303003300 12000000000300003000 12100000000030000030 12203000300300003000 12300000005003330000 12400003004400000400 12510000030000000000 12600000000300000000 12710000000000000000 12800000000000000000 12910000003003000000 13010000035000000000 13113030000000000030 13200000000000000030 13310030000000000000 13400000000000030300 13500000022222222222 13600000000000000300 13700040400000000004 13800300033000003000 13900000000000022222 14010003003000000000 14103300300030000030 14203400030400003003 14300004000000600030 14410000030000000000 14501111111111111111 14600000000000000000 14703300000005030000 14800000000000000000 14900000000330030000 15000000000030003300 15103000000033000000 15210000003030000000 15310000000000303000 15400000003000000040 15510000033000030000 15600000000040003000 15700000000040000004 15810450030000000000 15903000030030000000 16011111111111111111 16100000000304000300 16200000000040000003 16300000000000000003 16400000000000000000 16500030000030000330 16610330000003000000 16700000400040003450 16800030000030000000 16903000000330030000 17000030000000303000 17103003000000000003 17200000000000000000 17310030000000300000 17400000300030000040 17500030000000003030 17600000030030030000 17703000000030000003 17800300000030000030 17903003030000003000 18000000000030300033 18100000000030030000 18200000000030000003 18303004000300040033 18410000000000000000 18500003000000000000 18600000000030000000 18700000000000303003 18800000030030000003 18900000000000003000 19010000330000000000 19111111111111111111 19210300040030000000 19300003003003304400 19410030003000400000 19500000000000000000 19603003300000000000 19700004000000004000 19800000000000000435 19900003000000000034 20010300030000000000 20110300000003300000 20200003000300000330 20310300030000003000 20410000004000300000 20503003000000003000 20610000050003000000 20703004000400000430 20803000000030000000 20901111111111111111 21004004000030004000 21100033000000033000 21210000033000000000 21300000300000000030 21400503000030050000 21500000000400000043 21610000000000000000 21710034300000000000 21800000053000000400 21900000000000004300 22010000034000000000 22100000004000000000 22210000033000000000 22300000303033300030 22410000000000000000 22500000033000000000 22610300300000000600 22700000000000003300 22813000030000000000 22900000300300000003 23011111111111111111 23100000000000000000 23200000000040040000 23310000030000000000 23410000000000300000 23503300006030000000 23613000003000300000 23700000000000000000 23800003030300300340 23900003000000000000 24000000053030003030 24100030300000000000 24210000030000000000 24310000040000000000 24410002222222222222 24510300000000000000 24603000000000000000 24710000030006000000 24800000000050033000 24900400000030000000 25010000000004000000
Answered 1 days AfterMar 12, 2023

Answer To: EMAIL MARKETINGDatabase Analysis ExerciseOpen the Snappos excel file (email list). Snappos is a...

Asif answered on Mar 13 2023
29 Votes
3
Marketing Management
Name and Number
Date of Submission
Answer 1: Respondents Removed from the Ema
il List
Based on the given data, it can be said that the respondents who Hard Bounced (CODE: 1) should be removed from the email list because their all emails addresses are not valid, accurate and do not exist. They are unlikely to receive any upcoming emails, even if Snappos tries to resend them. On the other hand, Soft bounces with code 2 can be retired, therefore they must not be detached from the list at this point (Fedorchenko & Ponomarenko, 2019). Overall, it can be said that respondents with a hard bounce (coded as 1) and respondents with two or more soft bounces (coded as 2) respondents should be removed from the email list.
Answer 2: Best Time of Day to Send Emails
In order to determine the best time of the day to send emails, there will need to analyze the response rates for each time day. Therefore, the response will be calculated as the total number of clicks divided by the total number of delivered emails.
Response Rate...
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