Case Study: Improving E-Mail Marketing Response
Case Study: Improving E-Mail Marketing Response
Introduction
Email marketing play an important role in bringing in new customers and retaining the existing ones. The size of an email has a profound effect on the response rate to the email (Kent & Brandal, 2003). There are many other factors that may affect the response rate. In the case under discussion, a company is looking to increase the response rate to its marketing emails. They have identified three factors that may be affecting the response rate. These factors are: E-Mail Heading, Opening of Email and Email Body. The company studied these three factors and came up with the following results as presented in the Table 1.
Table 1
We would be analyzing the data from the Table 1 to carry out a design experiment. The results of the experiment would be presented in a graphical display to give us a clear picture of it. Recommendations would be provided to improve the email response rate. Towards the end of the discussion, a process model will be presented in a strategic manner to allow the company to improve their marketing response time.
Design of Experiment (DOE)
For this design experiment we can prioritize the importance of the three factors from Table 1. This is the body type is the most important factor followed by email opening and then the heading type. Plain text is suggested to bring in more responses than the emails that have HTML embedded body. HTML codes may have different tags that make them heavier than plain text (Mikhailov & Wills, 2000). This could be one for the factors they have less response rate as the receivers may need more time to open html embedded emails than plain text. The second factor is whether the email was opened or not. It is obvious that unless an email is opened, it won’t be responded to. The generic headers had a higher response than the detailed heading. The interaction effects charts (IEC) in the next section would provide a detailed overview of the processing of the above discussed information from the Table 1.
Graphical Display Tool for DOE Results
The interaction Effects Chart or IEC presented in the bellow would provide the management a clear view of how the three factors related to each other.
Run | Heading (x1) |
Email Open (x2) |
Body(x3) | x1 x2 | x1x3 | x2x3 | x1x2x3 | Repeat Rate 1 |
1 | Generic(-) | No(-) | Text(-) | + | + | + | – | 46 |
2 | Detailed(+) | No(-) | Text(-) | – | – | + | + | 34 |
3 | Generic(-) | Yes(+) | Text(-) | – | + | – | + | 56 |
4 | Detailed(+) | Yes(+) | Text(-) | + | – | – | – | 68 |
5 | Generic (-) | No(-) | HTML(+) | + | – | – | + | 25 |
6 | Detailed(+) | No(-) | HTML(+) | – | + | – | – | 22 |
7 | Generic(-) | Yes(+) | HTML(+) | – | – | + | – | 21 |
8 | Detailed(+) | Yes(+) | HTML(+) | + | + | + | + | 19 |
sum+ | 163 | 179.5 | 101 | 168 | 152.5 | 126 | 145.5 | |
sum- | 147.5 | 131 | 209.5 | 142.5 | 158 | 184.5 | 165 | |
ave + | 40.75 | 44.875 | 25.25 | 42 | 38.125 | 31.5 | 36.375 | |
ave- | 36.875 | 32.75 | 52.375 | 35.625 | 39.5 | 46.125 | 41.25 | |
effect | 3.875 | 12.125 | -27.125 | 6.375 | -1.375 | -14.63 | -4.875 |
Figure 1
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B x C Interaction
B: Email Open; BLO: No, BHI: yes C: Email Heading; CLO: Generic, CHI: Detailed |
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C LO | C HI | ||||||||
B LO | 1 | 42 | 36 | ||||||
2 | 26 | 27 | |||||||
Avg | 34 | 31.5 | |||||||
B HI | 1 | 57.5 | 74 | ||||||
2 | 22 | 26 | |||||||
Avg | 39.75 | 50 | |||||||
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Figure 2
A x C Interaction
A: Email Body; ALO: Text, AHI: HTML |
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C LO | C HI | |||||
A LO | 1 | 42 | 36 | |||
2 | 57.5 | 74 | ||||
Avg | 49.75 | 55 | ||||
A HI | 1 | 26 | 27 | |||
2 | 22 | 26 | ||||
Avg | 24 | 26.5 |
Figure 3
Recommendations
The company should use an email strategy where the body of the email is in plain text with detailed heading. Research has indicated that using that including the names of the people who are contacted in different forms of communications could increase response rate as it personalized the communication (San José-Cabezudo, 2014). This is what is recommended here for the company under discussion.
Overall Strategy
The company should carry on collecting data strategically related to the three factors and run the same analysis so that they are aware of the different preferences of their customers and can bring about the desired changes to their email communication. The company should carry out more research and standardize their email template based on this research. From what can suggest from the present data in Table 1 and our experimental analysis, an email template with detailed header, plain text body and the first and last name of the receivers i.e. customer is the best one. Customers who complete an order that was initiated from an email sent to him/her should be sent a survey about their experience. These surveys can contribute to future improvements.