A week ago, I was working on a project for my Accounting Information Systems course (COMM 335) which involves building a customer sign-up system for Netflix.ca. Netflix is a company that offers an online platform for streaming on-demand video over the internet through a monthly subscription at a flat rate. As I was working through the project, I recognized that throughout the database that I was creating, there was a table for each form that stores all the user inputs such as movie data, ratings, reviews, user preferences, and time and date watched. As I worked through my database, I can’t help but recognize the applications and connections that a database system such as Netflix member data base has with marketing information systems.
Marketing information system is a set of procedures and methods that apply to the regular, planned collection, analysis, and presentation of information that then may be used in marketing decisions. In the case with my project, my back-end table stores these user information in Netflix’s data warehouses. Having these data warehouses allow the Netflix management and marketing team to utilize data mining, which is the use of a variety of statistical analysis tools to uncover previous unknown patterns in the user data stored in these databases or relationships among variables by examining the most efficient and effective way to market relevant products and movies to different consumer targets. Not only will data mining aid in improving their brand name, it will bring in more customer satisfaction and profits and providing relevant program recommendations that fit the consumer’s needs.
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