2Improving Email Marketing ResponseAbstractIn this case study, we will evaluate and determine from the data that has been collected a company’s email marketing process that is being measured by the response rate it is receiving from emails. Two options for three factors will be used to make this determination. The first factor is the heading with the options of Generic/Detail. The second factor is Email Open with the options of Yes/No. The third factor is Body with the options of Text/HTML.To accomplish this, we will conduct a design of experiment (DOE) to test the cause and effect relationships in this marketing effort for the company. If we took the one factor at a time (OFAT) or the trial and error approach, we might be spending a considerable amount of time trying to determine the best way to improve this process. If there were only one factor to consider, then OFAT or trial and error would be perfectly fine.
IMPROVING E-MAIL MARKETING RESPONSE 2E-mail marketing is increasingly recognized in modern business as one of the most cost-effective internet marketing tools because of its high response rate. The advantage of e-mail marketing lies in the ability to connect the marketers with their customers and interact with them in real time. Digital processing and low costs allow business to send out huge number of emails (Rettie, 2002). Not surprisingly that e-mail marketing is such a hot topic among marketers.The Design of ExperimentThe design of experiment (DOE) is a method for determining the relationship between factors that affect the process and the output of the process. Statistics sometimes calls it “multivariate experimental design and analysis” (Figard, 2009). In other words, this systematic method is used to find cause-and-effect relationships. An understanding of it requires knowledge of experimentation concepts and some statistical tools. Using DOE, it is possible to find the actual optimum of a process, accounting for cooperation and identification the most important inputs into the process. The most commonly used DOE terms include hypothesis testing, controllable and uncontrollable input factors, replication, interaction and blocking (Figard, 2009). In order to verify the cause-and-effect relationships in the business processes of a given table, we need to conduct Three Factor Experiment. It is applied in most design experiments, because it is universal and can be used for many factors. In this design, all