I have worked in ecommerce for the past ten years. An issue I noticed and wanted to understand in order to minimize it was abandoned carts. At some point during their purchasing process, people would stop and not complete the purchase. What part of the process caused them to abandon their purchase? Was it shipping cost or taxes? By delving into this issue, I thought it would create an opportunity to hone in on the most search products in order to keep those products stocked. Through research and analytics, I could begin by gathering information through queries in the database, web logs, Google Analytics, and heat maps.

“Businesses need databases to provide information that will help the company run the business more efficiently and help managers and employees make better decisions. If a company wants to know which product is the most popular or who is its most profitable customer, the answer lies in the data” (Education, 1/2018, p. 198).

Multidimensional data analysis is what would be the next step to discover which products are selling best at which stores, during what time of the year to keep them in stock and for determining at which point of the process just before purchase the customer stops.

“Predictive analytics are used in organizing marketing campaigns because they are able to help determine customer responses or purchases, as well as promote cross-sell opportunities. Predictive models help businesses attract, retain and grow their most profitable customers. Improving operations. Many companies use predictive models to forecast inventory and manage resources. Predictive analytics enables organizations to function more efficiently” (SAS, 2018).

By gathering and analyzing this data I would be able to determine the steps to take to solve my problem and take advantage of the opportunities.

Education, P. (1/2018). MGT 608 – Managerial Support Systems (2018) [VitalSource Bookshelf version]. Retrieved from vbk://9781323829110

SAS. (2018) Predictive Analytics: What is it and why does it matter? Retrieved from: https://www.sas.com/en_us/insights/analytics/predictive-analytics.html