A company wishes to improve its e-mail marketing process, as measured

 

A company wishes to improve its e-mail marketing process, as measured by an increase in the response rate to e-mail advertisements. The company has decided to study the process by evaluating all combinations of two (2) options of the three (3) key factors, E-mail Heading (Detailed, Generic: E-Mail Open (No, Yes): and E-Mail Body (Text, HTML):. Each of the combinations in the design was repeated on two (2) different occasions. The factors studied and the measured response rates are summarized in the following table.

Table Improving E-Mao Response Rate

Run Heading E-Mail Open Body Replicate Response Rate

1 Generic No Text 1 45

2 Generic No Text 1 34

3 Generic Yes Text 1 56

4 Generic Yes Text 1 68

5. Generic No HTML 1 25 .

6 Detailed No HTML 1 22

7 Generic Yes HTML 1 21

8 Detailed Yes HTML 1 19

1 Generic No Text 2 38

2 Detailed No Text 2 38

3 Generic Yes Text 2 59

4 Detailed Yes Text 2 80

5 Generic No HTML 2 27

6 Detailed No HTML 2 32

7 Generic Yes HTML 2 23

8 Detailed Yes HTML 2 33

Write 2 or 3 page paper in which you answer the following questions

1Use the data shown in the table to conduct a design of experiment (DOE) in order to test cause-and-effect relationships in business processes for the company.

2) Determine the graphical display tool (e.g. Interaction Effects Chart, Scatter Chart, etc ) that you would use to present the results of the (DOE) that you produced in question 1. Provide a rationale response.

3) Recommend the main actions that the company could take in order to increase the response rate of its E-mail advertising. Provide a rationale for you response.

4) Propose one strategy for developing a process model for this company that will increase the response rate of its e-mail advertising and obtain effective business process. Provide rationale for response.

Course learning outcomes associated with this assignment

*Build regression model for improving business processes.

* Design experiments to test cause- and- effect relationships in business processes.

Regression Model is

y=b0+b1x1+b2x2+b3x3+b4x11x2+b5x1x3+b6x2x3+b7x1x2x3

y=77.6.25+1.9375×1+6.0625×2-13.5625×3/3.1875x1x2=0.6875x1x3-7.3125x2x3-2.4375x1x3x3

Graphical Analysis

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