The main focus of my thesis is to build a recommendation engine. Nowadays this topic has become more relevant as companies have been trying to get to know the customers and customize their offers.
Customization can be a real competitive advantage on various markets. Recommendation engine enables companies to track and record the behavior of their consumers and target them with unique offers.
I plan to create an application which can send text messages to the players of an online gaming site with special offers. I have daily contact with the company and I am allowed to access and use the necessary data since I am an intern at the company.
The application will be created for an online computer game company. The application will store the different activities of the user. A personal database will be available about all users. Based on that information we will be able to analyze the different user’s behavior, and target them with different advertisements. The database will be based on the SAP HANA in memory database solution.
As a first step I will gather the business requirements, decide the applicable technical architecture which includes defining the components and interfaces to implement the solution. As a next step the engine will be developed and validated. Different models will be build first with HANA built-in libraries, then with the help of R data mining language. The final solution will be evaluated and next steps will be defined as roadmap items for the next version.
The thesis will help SAP’s customer to gain insight into their customers purchasing behavior. This will benefit the enterprise and enable them to leverage cross selling or upselling opportunities.