Case Study 2: Improving E-Mail Marketing Response

  1. Use 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.

To code the data, the following indicators were used

FactorLow LevelHigh Level
Email HeadingGeneric (-)Detailed (+)
Email OpenNo ( -)Yes (+)
Email BodyText (-)HTML (+)

As such, the table when coded appeared as follows.

NoE-Mail HeadingEmail OpenEmail BodyResponse RateAverage
146, 3842
2+34, 3836
3+56, 5957.5
4++68, 8074
5+25, 2726
6++22, 5227
7++21, 2322
8+++19, 3326

To analyze the data, it was taken into account that the experiment was a three-factor experiment that required a 2x2x2 factorial design.  As such, the experiment has eight combinations to be tested. Chi tests were also conducted on the data.

  • 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 conducted in Question 1. Provide a rationale for your response. 

The right graphical display tool, in this case, are tables.

Case Processing Summary
 NMarginal Percentage
EmailHeading450.0%
+450.0%
EmailBody450.0%
+450.0%
EmailOpen450.0%
+450.0%
Valid8100.0%
Missing0 
Total8 
Subpopulation8a 
a. The dependent variable has only one value observed in 8 (100.0%) subpopulations.
Coefficients
 ModelUnstandardized Coeff.Standardized Coeff.tSig. 
 BStd. EBeta 
  (Constant)48.18816.495 2.921.014 
 Heading3.8755.423.110.714.490 
 Email open12.1255.423.3442.236.047 
 Body-27.1255.423-.769-5.001.000 
 Replicate4.8755.423.138.899.388 
 a. Dependent Variable: Response 
Parameter Estimates
 
EmailHeadingaBStd. ErrorWalddfSig.Exp(B)95% Confidence Interval for Exp(B)
Lower BoundUpper Bound
Intercept.5161.767.0851.770   
Average-.013.042.1011.751.987.9091.071
a. The reference category is: +.

Recommendations

            From the above analysis, it is clear that open emails had the steepest positive slope. This indicates that they provided the most positive response (Schmee & Oppenlander, 2012). Owing to this fact, the company should use open emails. To get more positive results, this analysis suggests that the company should build a more target audience, which would define these statistics even better.

Overall Strategy

To derive maximum benefit, the study should use the alignment model strategy. This strategy is critical in ensuring that the mission and vision of the company are aligned with the resources and capabilities of a company. Consequently, the company will experience efficiency in processes.

References

Schmee, J., & Oppenlander, J. E. (2012). JMP means business: statistical models for management. New York: SAS Institute.

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