E-Mail Marketing Response Regression Model

Question: Build regression models for improving business processes. Design experiments to test cause-and-effect relationships in business processes. Use technology and information resources to research issues in business process improvement. Write clearly and concisely about business process improvement using proper writing mechanics. Answer: Improving E-Mail Marketing Response The e-mail marketing process is based on the content and value that the brand is competent to provide to the existing subscribers. The email marketing is one productive and cost effective method that gathers instant sales from existing customers and builds an everlasting relationship, which is core to any successful businesses (Nagengast, 2015). This case study will throw light on the improvement of email marketing process by conducting a design of experiment (DOE) to validate the cause-and-effect relationship in the business practices of the organization. Working for Design of Experiment (DOE) in Excel The design of experiments (DOE) was carried out in Excel. The design of experiments was done on two options with three factors, namely A = "E-mail heading" (Generic and Detailed), B = "E-mail body" (Test and HTML) and C = "E-mail open" (Yes or No). To calculate the main effects in "E-mail heading" (Generic and Detailed) = A; Generic was given -1 value and Detailed was given a +1 value. However the same was done with Email body and Email open such that -1 value was given for No option and +1 value for Yes option and Text was given -1 value and HTML +1 value in Email Body. To find the main effects, responses were multiplied with each factor individually and sorted later to carry out the main plots of positive and negative averages on each factor. The responses were replicated that is why 8 (and not 16) divided sums of each factor. The interactions were then calculated between the factors as A*B, B*C and A*C and later were multiplied with responses to get the coefficients of interactions. Subsequently, multivariate regressions were carried out to get the regression coefficients on each interaction and a residual plot was fitted. However, after working on the design of experiments (DOE), the maximum interaction was shown on A*B (Email heading * Email body) and negative interaction was shown on B*C (Email heading * Email Open). Rationale for the Response The Design of Experiment (DOE) is considered in this study due to the systematic relationship that the experiment carries out affecting the output and practices of that process. This branch of statistics not only deals with conducting, planning, analyzing or implementing but also involving certain factors by altering the levels of another variable. This is also known as One-Factor-at-a-Time (OFAT) approach (Asq.org, 2016). The design of the experiment is performed and evaluated on two options with three factors namely A = "E-mail heading" (Generic and Detailed), B = "E-mail body" (Test and HTML) and C = "E-mail open" (Yes or No). However, the data was replicated and performed on response rates. The Excel tool was used to carry out the analysis and is depicted below in Figure 1 and Figure 2. Figure 1 was done to analyze the low and high values for the most significant factor. Therefore, the most important factor is A and B as they have the steepest graphs. Figure 2 depicts the multivariate regression coefficients. However, the maximum the coefficient the better is the interaction. Nevertheless, the positive are shown in A and B and the interaction of A*B. Main Actions The main action that the company should undertake to increase the response rate would be from E-mail heading and E-mail body as the interaction will attract the existing customers by creating an endless relationship for bringing success to the company. The both graphs above even prove that Email body and Email heading are the key factors individually, and the interaction between creates a positive impact on the marketing process. The six main recommended actions that can increase the response rates are. Through the process of sending e-mails only to the target audience; Using an effectively branded domain name e-mail address to show attract and maintain reliability; Creating an intriguing subject line as subject lines is the best way to get away with; Specifically, including a persuasive copy so that the recipient reads the complete message; Having a strong call to action to see that the reader gets what he wants. Review follow-ups to see how many prospects will respond to further e-mails (Wagner, 2013). Strategy One overall strategy that can be developed for increasing the response rate of advertising through e-mail is "Permission Marketing." Godin coined permission marketing in 1993, which highlights the consumer's consent to receive the marketing information. However, this idea is not novel but was introduced to maintain the privacy issues in marketing. The email advertising will not only receive consumer's permission but will also help them to market them (Gupta, 2015). The key to permission marketing helps in getting insight into interests of the customers and knowing the information needs. The marketing is particularly relevant to internet marketing because of messages that have low marginal cost. The core process targets the relevance of permission messages by segmenting a target population for getting maximum responses and increasing conversion rates. Moreover, it facilitates consumer preferences to communication (McCollough, 2015). Permission-based e-mail marketing strategy is considered powerful compared to any other strategy because the consumer is requesting the information from the advertiser rather directly exposing to it. Thus, advertisers can gain effective budgets as the beneficiary who answers has already stated a level of interest. Not to be mistaken, this form is different from uncalled-for commercial e-mail knew by "spam" which the consumers are facing on a daily basis in their e-mail (Sigurdsson, et al., 2013). References Asq.org,. (2016).What Is Design of Experiments (DOE)? | ASQ. Retrieved 2 March 2016, from https://asq.org/learn-about-quality/data-collection-analysis-tools/overview/design-of-experiments.html Gupta, N. (2015). Permission marketing: antecedents, impact and future.International Journal of Teaching and Case Studies,6(4), 281-289. McCollough, L. (2015). Permission Marketing: What It Is And Why It's Better (Than The Other Kind Of Marketing).Texas dental journal,132(11), 926. Nagengast, B. (2015).Simple Steps to Successful Email Marketing.StreamSend. Retrieved 2 March 2016, from https://www.streamsend.com/news5/ Sigurdsson, V., Menon, R. V., Sigurdarson, J. P., Kristjansson, J. S., Foxall, G. R. (2013). A test of the behavioral perspective model in the context of an e-mail marketing experiment.The Psychological Record,63(2), 295. Wagner, E. (2013).6 Ways to Increase Your Email Response Rates - i7 Marketing.i7 Marketing. Retrieved 2 March 2016, from https://www.i7marketing.com/internetmarketing/6-ways-increase-email-response-rates/