E Mail Marketing Response Rates Improvement Strategy

Strategy to Improve the E-Mail Marketing Response Rates A company intends to improve its email marketing system to measure its response rates from its email advertisements by carrying out the evaluation process using different combination of "two (2) options of the three (3) key factors: E-Mail Heading (Detailed, Generic); Email Open (No, Yes); and E-Mail Body (Text, HTML). Each of the combinations in the design was repeated on two (2) different occasions." (Email Attachment, 2015 p 1).

The objective of this paper is to develop the email advertising strategy to assist the company to increase the response rates. Conducting a DOE ( design of experiment) to test a cause-and-effect relationship of the Company Business Processes 2. Using the data in the table 1, the paper develops graphical illustrations to test relationships of the company's business process. Fig 1: Sum of the Response Rate by Email Body and Email Open As being revealed in Fig 1, the response rates for the TEXT emails are higher than the response rates for the HTML emails.

Typically, the email receivers open larger number of emails sent through TEXT than through HTML. A sum of the response rates of TEXT email opened are 263 while the sum of the response rates for the HTML emails opened are 96. Fig 2: Sum of the Response Rate by Email Body and Email Heading Similarly, the fig 2 shows that the company is able to generate higher response rates from both the detailed and generic TEXT emails than detailed and generic HTML emails.

Fig 3: Sum of the Response Rate Email Heading and Email Open As being revealed in Fig 3, the detailed emails had higher response rates than generic emails. The sum of the response rates for the email opened for detailed emails are 200, however, the sum of the response rates for the generic emails are 159. 2. Determination of the Selected Graphical Display Tool The paper uses the Pivot Chart to view the table 1.

The benefits of the Pivot Chart is that it assists in analyzing the data in table 1 and assists in presenting the data in a graphical form. Moreover, the pivot chart is very easy to understand and assists in presenting the relationship of the factors affecting the email response rates. Regression Analysis The table 2 reveals the summary of the response rates of the Text, HTML, Generic and Detailed Emails. The sum of the response rates of text emails are higher than the sum of the response rates of the HTML emails.

Table 2: Summary of E-Mail Response Rate TEXT HTML Generic Detailed 46 27 46 34 34 32 56 68 56 23 25 22 68 33 21 19 38 25 38 38 38 22 59 80 59 21 27 32 80 19 23 33 SUM AVERAGE 52.37 25.25 36.87 40.75 The output of the regression analysis reveals that emails sent though text have higher response effects than emails sent through HTML. Moreover, the detailed emails have higher response effects than generic emails.

SUMMARY OUTPUT OF Emails TEXT AND HTML Response Rates Regression Statistics Multiple R 0,29765 R Square 0,088595 Adjusted R Square -0,06331 Standard Error 16,79014 Observations 8 ANOVA df SS MS F Significance F Regression 1 164,4218 164,4218 0,583245 0,473994 Residual 6 1691,453 281,9089 Total 7 1855,875 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95,0% Upper 95,0% Intercept 76,40771 32,02361 2,385981 0,054323 -1,95123 154,7667 -1,95123 154,7667 X Variable 1 -0,95179 1,246281 -0,7637 0,473994 -4,00133 2,09775 -4,00133 2,09775 SUMMARY OUTPUT of Generic and Detailed Emails Response Rate Regression Statistics Multiple R 0,90206 R Square 0,813712 Adjusted R Square 0,782665 Standard Error 7,098373 Observations 8 ANOVA df SS MS F Significance F Regression 1 1320,554 1320,554 26,20827 0,00218 Residual 6 302,3214 50,3869 Total 7 1622,875 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95,0% Upper 95,0% Intercept 11,08726 5,627816 1,970083 0,096339 -2,68351 24,85803.