Analysis of Marketing Dashboard for Online Referral Websites
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This memorandum provides an analysis of the marketing dashboard for online referral websites, including graphs and data on visitor details, product details, referral websites, and top products. It concludes with insights on visitor trends, top-selling products, and referral site performance.
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Running head: MEMORANDUM MEMORANDUM Name of the Student: Name of the University: Author Note:
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1MEMORANDUM MEMORANDUM The graphs shown in the dashboards represent the sale of products from various online referral websites and the number of visitors or customers that visit these sites. The graphs are divided into five categories which are the visitor graphs, product graphs, referral sites graph, top products purchased but not displayed together chart and the top products displayed together but not purchased graph. Figure1Visitor details in yearly, daily and hourly format. The visitor graphs keep tracks of customers who visited these sites from 2004 to 2005. The visitor deviation per day is shown comparing the results with the previous year. The results are demonstrated in the form of a graph. The second graph shows the same thing but this time for each day in the given month. The last graph also shows the same thing but in a per hour basis for a given day. Figure2Product details and revenue The five sections of the dashboard shows different types of data. The first set of three graphs show the standard deviation of visitors that visit the referral site. The second section along with the graphs show the top 10 products that generated the maximum revenue. The data is
2MEMORANDUM shown as per the last 30 days and displays both the viewed percentage and the revenue percentage. Figure3Referral websites details The third section shows the top 10 referral sites that has the maximum sale records. The graph for each of the site is displayed along with important data like referral count, referral percentage and average revenue. The data shown is of the last 12 months or one year. The section also shows the referral increase or decrease compared to the last year.
3MEMORANDUM Figure4Top 10 product details The fourth section consists of the top 10 set of products that were purchased together but were not kept on display together. The percentage of sale for these products are also given. No graph is provided here but just the data. The last section shows the top 10 products that were displayed together but were not purchased together. The sale percentage of those products are also shown. It can be concluded from the above observations that the number of visitors increased from April 2004 to February 2005. The highest number of visitors are seen during the 4thday of the month and lowest during 10thday of the month. The products like business casual shirts had the highest revenue. The summer dress has the lowest. The most viewed product is skirt and the lowest is oxford shirt. Thewww.clothingconnection.comhas the highest referrals with a 57% increase since last year and thewww.nobrainer.comhas the lowest with -5% decrease since last year. The lowest drop was seen bywww.getthere.comwith a -43% decrease since last year. From the dashboard it can be concluded that the white Oxford shirt and the Chino tan pants are the products that are mostly purchased together and also has the second highest sale. The blue dress pants and the black sports tee are never purchased together as per the dashboard.
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4MEMORANDUM To conclude, business casual black skirts, oxford white shirt, oxford blue shirt and men’s pant chino beige are the most purchased products from the websites.
5MEMORANDUM Bibliography 26133 - Create a sample marketing analysis dashboard for use in a portlet. (2019). Retrieved fromhttp://support.sas.com/kb/26/133.html Obermaier, J. F., Stam, K., & Lizardi, R. (2018).Employing User-Centered Design to AcceleratetheConstructionofaBusinessIntelligenceDashboard(Doctoral dissertation). Gounder, M. S., Iyer, V. V., & Al Mazyad, A. (2016, March). A survey on business intelligencetoolsforuniversitydashboarddevelopment.In20163rdMEC International Conference on Big Data and Smart City (ICBDSC)(pp. 1-7). IEEE. Mahajan, S., Parekh, M., Patel, H., & Patil, S. (2017, March). BRB dashboard: A web-based statisticaldashboard.In2017InternationalConferenceonInnovationsin Information, Embedded and Communication Systems (ICIIECS)(pp. 1-6). IEEE.